Fast NODD GRIB Aggregations¶

Overview¶

In this tutorial we are going to demonstrate building fast kerchunk aggregations of NODD grib2 weather forecasts. This workflow primarily involves xarray-datatree, pandas and the new grib_tree function released in kerchunk v0.2.3.

About the Dataset¶

In this demo we will be looking at GRIB2 files generated by NOAA Global Ensemble Forecast System (GEFS). This dataset is a weather forecast model made up of 21 separate forecasts, or ensemble members. GEFS has global coverage and is produced four times a day with forecasts going out to 16 days. It is updated 4 times a day, every 6 hours starting at midnight.

More information on this dataset can be found here

Prerequisites¶

Concepts	Importance	Notes
Kerchunk Basics	Required	Core
Pandas Tutorial	Required	Core
Kerchunk and Xarray-Datatree	Required	IO
Xarray-Datatree Overview	Required	IO

Time to learn: 30 minutes

Motivation¶

As we know that kerchunk provides a unified way to represent a variety of chunked, compressed data formats (e.g. NetCDF/HDF5, GRIB2, TIFF, …) by generating references. This task flow has ability to build large aggregations from NODD grib forecasts in a fraction of the time using the idx files.

Imports¶

In [1]:

import copy
import fsspec
import pandas as pd
import xarray as xr
import datetime
from kerchunk.grib2 import (
    AggregationType,
    build_idx_grib_mapping,
    extract_datatree_chunk_index,
    grib_tree,
    map_from_index,
    parse_grib_idx,
    reinflate_grib_store,
    scan_grib,
    strip_datavar_chunks,
)

Building the Aggregation directly from the GRIB files¶

We are using the newly implemented Kerchunk grib_tree function to build a hierarchical data model from a set of scanned grib messages.This data model can be opened directly using either zarr or xarray datatree. This way of building the aggregation is very slow. Here we're going to use xarray-datatree to open and view it:

In [2]:

s3_files = [
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af006",
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af012",
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af018",
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af024",
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af030",
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af036",
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af042",
]

In [3]:

# converting the references into the hierarchical datamodel
grib_tree_store = grib_tree(
    [
        group
        for f in s3_files
        for group in scan_grib(f, storage_options=dict(anon=True))
    ],
    remote_options=dict(anon=True),
)

/home/rsignell/miniforge3/envs/grib-idx/lib/python3.12/site-packages/kerchunk/combine.py:376: UserWarning: Concatenated coordinate 'time' contains less than expectednumber of values across the datasets: [1483250400]
  warnings.warn(

In [4]:

# Transforming the output to datatree to view it. This tree model the variables
s3_dt = xr.open_datatree(
    fsspec.filesystem(
        "reference",
        fo=grib_tree_store,
        remote_protocol="s3",
        remote_options={"anon": True},
    ).get_mapper(""),
    engine="zarr",
    consolidated=False,
)

In [5]:

# In this tree model, the variables are organized into hierarchical groups, first by "stepType" and then by "typeOfLevel."
s3_dt

Out[5]:

<xarray.DatasetView> Size: 0B
Dimensions:  ()
Data variables:
    *empty*

xarray.DataTree

Groups: (33)
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Convective available potential energy
cape
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (time: 1, step: 7, latitude: 181, longitude: 360) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: cape (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: pressureFromGroundLayer
pressureFromGroundLayer
Groups: (0)
Dimensions:
time: 1
step: 7
latitude: 181
longitude: 360
Coordinates: (6)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
cape
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
cape
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Convective available potential energy
GRIB_numberOfPoints :
65160
GRIB_paramId :
59
GRIB_shortName :
cape
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
pressureFromGroundLayer
GRIB_units :
J kg**-1
GRIB_uvRelativeToGrid :
0
long_name :
Convective available potential energy
standard_name :
unknown
units :
J kg**-1
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
pressureFromGroundLayer
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Convective available potential energy
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Categorical freezing rain
cfrzr
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (time: 1, step: 7, latitude: 181, longitude: 360) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: cfrzr (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
time: 1
step: 7
latitude: 181
longitude: 360
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
cfrzr
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
cfrzr
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Categorical freezing rain
GRIB_numberOfPoints :
65160
GRIB_paramId :
260030
GRIB_shortName :
cfrzr
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
(Code table 4.222)
GRIB_uvRelativeToGrid :
0
long_name :
Categorical freezing rain
standard_name :
unknown
units :
(Code table 4.222)
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Categorical freezing rain
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Categorical ice pellets
cicep
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (time: 1, step: 7, latitude: 181, longitude: 360) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: cicep (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
time: 1
step: 7
latitude: 181
longitude: 360
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
cicep
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
cicep
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Categorical ice pellets
GRIB_numberOfPoints :
65160
GRIB_paramId :
260031
GRIB_shortName :
cicep
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
(Code table 4.222)
GRIB_uvRelativeToGrid :
0
long_name :
Categorical ice pellets
standard_name :
unknown
units :
(Code table 4.222)
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Categorical ice pellets
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Convective inhibition
cin
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (time: 1, step: 7, latitude: 181, longitude: 360) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: cin (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: pressureFromGroundLayer
pressureFromGroundLayer
Groups: (0)
Dimensions:
time: 1
step: 7
latitude: 181
longitude: 360
Coordinates: (6)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
cin
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
cin
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Convective inhibition
GRIB_numberOfPoints :
65160
GRIB_paramId :
228001
GRIB_shortName :
cin
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
pressureFromGroundLayer
GRIB_units :
J kg**-1
GRIB_uvRelativeToGrid :
0
long_name :
Convective inhibition
standard_name :
unknown
units :
J kg**-1
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
pressureFromGroundLayer
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Convective inhibition
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Categorical rain
crain
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (time: 1, step: 7, latitude: 181, longitude: 360) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: crain (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
time: 1
step: 7
latitude: 181
longitude: 360
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
crain
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
crain
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Categorical rain
GRIB_numberOfPoints :
65160
GRIB_paramId :
260029
GRIB_shortName :
crain
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
(Code table 4.222)
GRIB_uvRelativeToGrid :
0
long_name :
Categorical rain
standard_name :
unknown
units :
(Code table 4.222)
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Categorical rain
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Categorical snow
csnow
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (time: 1, step: 7, latitude: 181, longitude: 360) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: csnow (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
time: 1
step: 7
latitude: 181
longitude: 360
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
csnow
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
csnow
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Categorical snow
GRIB_numberOfPoints :
65160
GRIB_paramId :
260032
GRIB_shortName :
csnow
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
(Code table 4.222)
GRIB_uvRelativeToGrid :
0
long_name :
Categorical snow
standard_name :
unknown
units :
(Code table 4.222)
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Categorical snow
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Geopotential height
gh
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 36MB Dimensions: (time: 1, step: 7, isobaricInhPa: 10, latitude: 181, longitude: 360) Coordinates: * isobaricInhPa (isobaricInhPa) float64 80B 10.0 50.0 100.0 ... 925.0 1e+03 * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step, isobaricInhPa) int64 560B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:0... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step, isobaricInhPa) datetime64[ns] 560B ... Data variables: gh (time, step, isobaricInhPa, latitude, longitude) float64 36MB ... Attributes: typeOfLevel: isobaricInhPa
isobaricInhPa
Groups: (0)
Dimensions:
time: 1
step: 7
isobaricInhPa: 10
latitude: 181
longitude: 360
Coordinates: (7)
isobaricInhPa
(isobaricInhPa)
float64
10.0 50.0 100.0 ... 925.0 1e+03
long_name :
pressure
positive :
down
standard_name :
air_pressure
stored_direction :
decreasing
units :
hPa
array([ 10., 50., 100., 200., 250., 500., 700., 850., 925., 1000.])
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step, isobaricInhPa)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[70 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step, isobaricInhPa)
datetime64[ns]
...
long_name :
time
standard_name :
time
[70 values with dtype=datetime64[ns]]
Data variables: (1)
gh
(time, step, isobaricInhPa, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
geopotential_height
GRIB_cfVarName :
gh
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Geopotential height
GRIB_numberOfPoints :
65160
GRIB_paramId :
156
GRIB_shortName :
gh
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
isobaricInhPa
GRIB_units :
gpm
GRIB_uvRelativeToGrid :
0
long_name :
Geopotential height
standard_name :
geopotential_height
units :
gpm
[4561200 values with dtype=float64]
Attributes: (1)
typeOfLevel :
isobaricInhPa
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Geopotential height
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Mean surface latent heat flux
mslhf
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: mslhf (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
mslhf
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
mslhf
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Mean surface latent heat flux
GRIB_numberOfPoints :
65160
GRIB_paramId :
235034
GRIB_shortName :
mslhf
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
W m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Mean surface latent heat flux
standard_name :
unknown
units :
W m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Mean surface latent heat flux
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Mean surface sensible heat flux
msshf
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: msshf (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
msshf
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
msshf
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Mean surface sensible heat flux
GRIB_numberOfPoints :
65160
GRIB_paramId :
235033
GRIB_shortName :
msshf
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
W m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Mean surface sensible heat flux
standard_name :
unknown
units :
W m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Mean surface sensible heat flux
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Pressure reduced to MSL
prmsl
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 meanSea float64 8B ... number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: prmsl (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: meanSea
meanSea
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
meanSea
()
float64
...
[1 values with dtype=float64]
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
prmsl
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
prmsl
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Pressure reduced to MSL
GRIB_numberOfPoints :
65160
GRIB_paramId :
260074
GRIB_shortName :
prmsl
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
meanSea
GRIB_units :
Pa
GRIB_uvRelativeToGrid :
0
long_name :
Pressure reduced to MSL
standard_name :
unknown
units :
Pa
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
meanSea
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Pressure reduced to MSL
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Precipitable water
pwat
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: atmosphereSingleLayer float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 ... 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 d... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: pwat (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: atmosphereSingleLayer
atmosphereSingleLayer
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
atmosphereSingleLayer
()
float64
...
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
pwat
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
pwat
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Precipitable water
GRIB_numberOfPoints :
65160
GRIB_paramId :
3054
GRIB_shortName :
pwat
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
atmosphereSingleLayer
GRIB_units :
kg m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Precipitable water
standard_name :
unknown
units :
kg m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
atmosphereSingleLayer
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Precipitable water
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Relative humidity
r
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 36MB Dimensions: (isobaricInhPa: 10, latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * isobaricInhPa (isobaricInhPa) float64 80B 10.0 50.0 100.0 ... 925.0 1e+03 * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step, isobaricInhPa) int64 560B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:0... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step, isobaricInhPa) datetime64[ns] 560B ... Data variables: r (time, step, isobaricInhPa, latitude, longitude) float64 36MB ... Attributes: typeOfLevel: isobaricInhPa
isobaricInhPa
Groups: (0)
Dimensions:
isobaricInhPa: 10
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
isobaricInhPa
(isobaricInhPa)
float64
10.0 50.0 100.0 ... 925.0 1e+03
long_name :
pressure
positive :
down
standard_name :
air_pressure
stored_direction :
decreasing
units :
hPa
array([ 10., 50., 100., 200., 250., 500., 700., 850., 925., 1000.])
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step, isobaricInhPa)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[70 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step, isobaricInhPa)
datetime64[ns]
...
long_name :
time
standard_name :
time
[70 values with dtype=datetime64[ns]]
Data variables: (1)
r
(time, step, isobaricInhPa, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
relative_humidity
GRIB_cfVarName :
r
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Relative humidity
GRIB_numberOfPoints :
65160
GRIB_paramId :
157
GRIB_shortName :
r
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
isobaricInhPa
GRIB_units :
%
GRIB_uvRelativeToGrid :
0
long_name :
Relative humidity
standard_name :
relative_humidity
units :
%
[4561200 values with dtype=float64]
Attributes: (1)
typeOfLevel :
isobaricInhPa
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Relative humidity
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: 2 metre relative humidity
r2
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: heightAboveGround float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: r2 (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: heightAboveGround
heightAboveGround
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
heightAboveGround
()
float64
...
long_name :
height above the surface
positive :
up
standard_name :
height
units :
m
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
r2
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
relative_humidity
GRIB_cfVarName :
r2
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
2 metre relative humidity
GRIB_numberOfPoints :
65160
GRIB_paramId :
260242
GRIB_shortName :
2r
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
heightAboveGround
GRIB_units :
%
GRIB_uvRelativeToGrid :
0
long_name :
2 metre relative humidity
standard_name :
relative_humidity
units :
%
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
heightAboveGround
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
2 metre relative humidity
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Snow depth
sde
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: sde (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
sde
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
lwe_thickness_of_surface_snow_amount
GRIB_cfVarName :
sde
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Snow depth
GRIB_numberOfPoints :
65160
GRIB_paramId :
3066
GRIB_shortName :
sde
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
m
GRIB_uvRelativeToGrid :
0
long_name :
Snow depth
standard_name :
lwe_thickness_of_surface_snow_amount
units :
m
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Snow depth
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Surface downward long-wave radiation flux
sdlwrf
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: sdlwrf (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
sdlwrf
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
sdlwrf
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Surface downward long-wave radiation flux
GRIB_numberOfPoints :
65160
GRIB_paramId :
260097
GRIB_shortName :
sdlwrf
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
W m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Surface downward long-wave radiation flux
standard_name :
unknown
units :
W m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Surface downward long-wave radiation flux
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Surface downward short-wave radiation flux
sdswrf
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: sdswrf (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
sdswrf
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
sdswrf
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Surface downward short-wave radiation flux
GRIB_numberOfPoints :
65160
GRIB_paramId :
260087
GRIB_shortName :
sdswrf
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
W m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Surface downward short-wave radiation flux
standard_name :
unknown
units :
W m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Surface downward short-wave radiation flux
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Water equivalent of accumulated snow depth (deprecated)
sdwe
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: sdwe (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
sdwe
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
sdwe
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Water equivalent of accumulated snow depth (deprecated)
GRIB_numberOfPoints :
65160
GRIB_paramId :
260056
GRIB_shortName :
sdwe
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
kg m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Water equivalent of accumulated snow depth (deprecated)
standard_name :
unknown
units :
kg m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Water equivalent of accumulated snow depth (deprecated)
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Volumetric soil moisture content
soilw
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: soilw (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: depthBelowLandLayer
depthBelowLandLayer
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (6)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
soilw
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
soilw
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Volumetric soil moisture content
GRIB_numberOfPoints :
65160
GRIB_paramId :
260185
GRIB_shortName :
soilw
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
depthBelowLandLayer
GRIB_units :
Proportion
GRIB_uvRelativeToGrid :
0
long_name :
Volumetric soil moisture content
standard_name :
unknown
units :
Proportion
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
depthBelowLandLayer
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Volumetric soil moisture content
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Surface pressure
sp
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: sp (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
sp
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
surface_air_pressure
GRIB_cfVarName :
sp
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Surface pressure
GRIB_numberOfPoints :
65160
GRIB_paramId :
134
GRIB_shortName :
sp
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
Pa
GRIB_uvRelativeToGrid :
0
long_name :
Surface pressure
standard_name :
surface_air_pressure
units :
Pa
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Surface pressure
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Soil temperature
st
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: st (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: depthBelowLandLayer
depthBelowLandLayer
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (6)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
st
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
st
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Soil temperature
GRIB_numberOfPoints :
65160
GRIB_paramId :
228139
GRIB_shortName :
st
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
depthBelowLandLayer
GRIB_units :
K
GRIB_uvRelativeToGrid :
0
long_name :
Soil temperature
standard_name :
unknown
units :
K
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
depthBelowLandLayer
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Soil temperature
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Surface upward long-wave radiation flux
sulwrf
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (2)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 nominalTop float64 8B ... number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: sulwrf (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: nominalTop
nominalTop
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
nominalTop
()
float64
...
[1 values with dtype=float64]
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
sulwrf
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
sulwrf
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Surface upward long-wave radiation flux
GRIB_numberOfPoints :
65160
GRIB_paramId :
260098
GRIB_shortName :
sulwrf
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
nominalTop
GRIB_units :
W m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Surface upward long-wave radiation flux
standard_name :
unknown
units :
W m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
nominalTop

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: sulwrf (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
sulwrf
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
sulwrf
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Surface upward long-wave radiation flux
GRIB_numberOfPoints :
65160
GRIB_paramId :
260098
GRIB_shortName :
sulwrf
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
W m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Surface upward long-wave radiation flux
standard_name :
unknown
units :
W m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Surface upward long-wave radiation flux
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Surface upward short-wave radiation flux
suswrf
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: suswrf (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
suswrf
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
suswrf
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Surface upward short-wave radiation flux
GRIB_numberOfPoints :
65160
GRIB_paramId :
260088
GRIB_shortName :
suswrf
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
W m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Surface upward short-wave radiation flux
standard_name :
unknown
units :
W m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Surface upward short-wave radiation flux
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Temperature
t
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 36MB Dimensions: (isobaricInhPa: 10, latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * isobaricInhPa (isobaricInhPa) float64 80B 10.0 50.0 100.0 ... 925.0 1e+03 * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step, isobaricInhPa) int64 560B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:0... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step, isobaricInhPa) datetime64[ns] 560B ... Data variables: t (time, step, isobaricInhPa, latitude, longitude) float64 36MB ... Attributes: typeOfLevel: isobaricInhPa
isobaricInhPa
Groups: (0)
Dimensions:
isobaricInhPa: 10
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
isobaricInhPa
(isobaricInhPa)
float64
10.0 50.0 100.0 ... 925.0 1e+03
long_name :
pressure
positive :
down
standard_name :
air_pressure
stored_direction :
decreasing
units :
hPa
array([ 10., 50., 100., 200., 250., 500., 700., 850., 925., 1000.])
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step, isobaricInhPa)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[70 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step, isobaricInhPa)
datetime64[ns]
...
long_name :
time
standard_name :
time
[70 values with dtype=datetime64[ns]]
Data variables: (1)
t
(time, step, isobaricInhPa, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
air_temperature
GRIB_cfVarName :
t
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Temperature
GRIB_numberOfPoints :
65160
GRIB_paramId :
130
GRIB_shortName :
t
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
isobaricInhPa
GRIB_units :
K
GRIB_uvRelativeToGrid :
0
long_name :
Temperature
standard_name :
air_temperature
units :
K
[4561200 values with dtype=float64]
Attributes: (1)
typeOfLevel :
isobaricInhPa
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Temperature
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: 2 metre temperature
t2m
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: heightAboveGround float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: t2m (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: heightAboveGround
heightAboveGround
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
heightAboveGround
()
float64
...
long_name :
height above the surface
positive :
up
standard_name :
height
units :
m
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
t2m
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
air_temperature
GRIB_cfVarName :
t2m
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
2 metre temperature
GRIB_numberOfPoints :
65160
GRIB_paramId :
167
GRIB_shortName :
2t
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
heightAboveGround
GRIB_units :
K
GRIB_uvRelativeToGrid :
0
long_name :
2 metre temperature
standard_name :
air_temperature
units :
K
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
heightAboveGround
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
2 metre temperature
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Total Cloud Cover
tcc
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: avg
avg
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: atmosphere float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: tcc (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: atmosphere
atmosphere
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
atmosphere
()
float64
...
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
tcc
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
tcc
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Total Cloud Cover
GRIB_numberOfPoints :
65160
GRIB_paramId :
228164
GRIB_shortName :
tcc
GRIB_stepType :
avg
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
atmosphere
GRIB_units :
%
GRIB_uvRelativeToGrid :
0
long_name :
Total Cloud Cover
standard_name :
unknown
units :
%
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
atmosphere
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
avg
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Total Cloud Cover
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Maximum temperature
tmax
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: max
max
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: heightAboveGround float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: tmax (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: heightAboveGround
heightAboveGround
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
heightAboveGround
()
float64
...
long_name :
height above the surface
positive :
up
standard_name :
height
units :
m
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
tmax
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
tmax
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Maximum temperature
GRIB_numberOfPoints :
65160
GRIB_paramId :
3015
GRIB_shortName :
tmax
GRIB_stepType :
max
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
heightAboveGround
GRIB_units :
K
GRIB_uvRelativeToGrid :
0
long_name :
Maximum temperature
standard_name :
unknown
units :
K
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
heightAboveGround
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
max
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Maximum temperature
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Minimum temperature
tmin
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: min
min
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: heightAboveGround float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: tmin (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: heightAboveGround
heightAboveGround
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
heightAboveGround
()
float64
...
long_name :
height above the surface
positive :
up
standard_name :
height
units :
m
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
tmin
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
tmin
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Minimum temperature
GRIB_numberOfPoints :
65160
GRIB_paramId :
3016
GRIB_shortName :
tmin
GRIB_stepType :
min
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
heightAboveGround
GRIB_units :
K
GRIB_uvRelativeToGrid :
0
long_name :
Minimum temperature
standard_name :
unknown
units :
K
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
heightAboveGround
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
min
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Minimum temperature
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Total Precipitation
tp
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: accum
accum
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * latitude (latitude) float64 1kB 90.0 89.0 88.0 87.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:00:00 surface float64 8B ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: tp (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: surface
surface
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
surface
()
float64
...
[1 values with dtype=float64]
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
tp
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
unknown
GRIB_cfVarName :
tp
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Total Precipitation
GRIB_numberOfPoints :
65160
GRIB_paramId :
228228
GRIB_shortName :
tp
GRIB_stepType :
accum
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
surface
GRIB_units :
kg m**-2
GRIB_uvRelativeToGrid :
0
long_name :
Total Precipitation
standard_name :
unknown
units :
kg m**-2
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
surface
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
accum
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Total Precipitation
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: U component of wind
u
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 44MB Dimensions: (isobaricInhPa: 12, latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * isobaricInhPa (isobaricInhPa) float64 96B 10.0 50.0 100.0 ... 925.0 1e+03 * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step, isobaricInhPa) int64 672B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:0... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step, isobaricInhPa) datetime64[ns] 672B ... Data variables: u (time, step, isobaricInhPa, latitude, longitude) float64 44MB ... Attributes: typeOfLevel: isobaricInhPa
isobaricInhPa
Groups: (0)
Dimensions:
isobaricInhPa: 12
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
isobaricInhPa
(isobaricInhPa)
float64
10.0 50.0 100.0 ... 925.0 1e+03
long_name :
pressure
positive :
down
standard_name :
air_pressure
stored_direction :
decreasing
units :
hPa
array([ 10., 50., 100., 200., 250., 300., 400., 500., 700., 850., 925., 1000.])
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step, isobaricInhPa)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[84 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step, isobaricInhPa)
datetime64[ns]
...
long_name :
time
standard_name :
time
[84 values with dtype=datetime64[ns]]
Data variables: (1)
u
(time, step, isobaricInhPa, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
eastward_wind
GRIB_cfVarName :
u
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
U component of wind
GRIB_numberOfPoints :
65160
GRIB_paramId :
131
GRIB_shortName :
u
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
isobaricInhPa
GRIB_units :
m s**-1
GRIB_uvRelativeToGrid :
0
long_name :
U component of wind
standard_name :
eastward_wind
units :
m s**-1
[5473440 values with dtype=float64]
Attributes: (1)
typeOfLevel :
isobaricInhPa
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
U component of wind
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: 10 metre U wind component
u10
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: heightAboveGround float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: u10 (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: heightAboveGround
heightAboveGround
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
heightAboveGround
()
float64
...
long_name :
height above the surface
positive :
up
standard_name :
height
units :
m
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
u10
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
eastward_wind
GRIB_cfVarName :
u10
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
10 metre U wind component
GRIB_numberOfPoints :
65160
GRIB_paramId :
165
GRIB_shortName :
10u
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
heightAboveGround
GRIB_units :
m s**-1
GRIB_uvRelativeToGrid :
0
long_name :
10 metre U wind component
standard_name :
eastward_wind
units :
m s**-1
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
heightAboveGround
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
10 metre U wind component
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: V component of wind
v
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 44MB Dimensions: (isobaricInhPa: 12, latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: * isobaricInhPa (isobaricInhPa) float64 96B 10.0 50.0 100.0 ... 925.0 1e+03 * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step, isobaricInhPa) int64 672B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:0... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step, isobaricInhPa) datetime64[ns] 672B ... Data variables: v (time, step, isobaricInhPa, latitude, longitude) float64 44MB ... Attributes: typeOfLevel: isobaricInhPa
isobaricInhPa
Groups: (0)
Dimensions:
isobaricInhPa: 12
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
isobaricInhPa
(isobaricInhPa)
float64
10.0 50.0 100.0 ... 925.0 1e+03
long_name :
pressure
positive :
down
standard_name :
air_pressure
stored_direction :
decreasing
units :
hPa
array([ 10., 50., 100., 200., 250., 300., 400., 500., 700., 850., 925., 1000.])
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step, isobaricInhPa)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[84 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step, isobaricInhPa)
datetime64[ns]
...
long_name :
time
standard_name :
time
[84 values with dtype=datetime64[ns]]
Data variables: (1)
v
(time, step, isobaricInhPa, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
northward_wind
GRIB_cfVarName :
v
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
V component of wind
GRIB_numberOfPoints :
65160
GRIB_paramId :
132
GRIB_shortName :
v
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
isobaricInhPa
GRIB_units :
m s**-1
GRIB_uvRelativeToGrid :
0
long_name :
V component of wind
standard_name :
northward_wind
units :
m s**-1
[5473440 values with dtype=float64]
Attributes: (1)
typeOfLevel :
isobaricInhPa
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
V component of wind
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: 10 metre V wind component
v10
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: heightAboveGround float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days ... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: v10 (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: heightAboveGround
heightAboveGround
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
heightAboveGround
()
float64
...
long_name :
height above the surface
positive :
up
standard_name :
height
units :
m
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
v10
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
northward_wind
GRIB_cfVarName :
v10
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
10 metre V wind component
GRIB_numberOfPoints :
65160
GRIB_paramId :
166
GRIB_shortName :
10v
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
heightAboveGround
GRIB_units :
m s**-1
GRIB_uvRelativeToGrid :
0
long_name :
10 metre V wind component
standard_name :
northward_wind
units :
m s**-1
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
heightAboveGround
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
10 metre V wind component
<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: name: Vertical velocity
w
Groups: (1)

<xarray.DatasetView> Size: 0B Dimensions: () Data variables: *empty* Attributes: stepType: instant
instant
Groups: (1)

<xarray.DatasetView> Size: 4MB Dimensions: (latitude: 181, longitude: 360, time: 1, step: 7) Coordinates: isobaricInhPa float64 8B ... * latitude (latitude) float64 1kB 90.0 89.0 88.0 ... -88.0 -89.0 -90.0 * longitude (longitude) float64 3kB 0.0 1.0 2.0 3.0 ... 357.0 358.0 359.0 number (time, step) int64 56B ... * step (step) timedelta64[ns] 56B 0 days 06:00:00 ... 1 days 18:0... * time (time) datetime64[ns] 8B 2017-01-01T06:00:00 valid_time (time, step) datetime64[ns] 56B ... Data variables: w (time, step, latitude, longitude) float64 4MB ... Attributes: typeOfLevel: isobaricInhPa
isobaricInhPa
Groups: (0)
Dimensions:
latitude: 181
longitude: 360
time: 1
step: 7
Coordinates: (7)
isobaricInhPa
()
float64
...
long_name :
pressure
positive :
down
standard_name :
air_pressure
stored_direction :
decreasing
units :
hPa
[1 values with dtype=float64]
latitude
(latitude)
float64
90.0 89.0 88.0 ... -89.0 -90.0
long_name :
latitude
standard_name :
latitude
units :
degrees_north
array([ 90., 89., 88., 87., 86., 85., 84., 83., 82., 81., 80., 79., 78., 77., 76., 75., 74., 73., 72., 71., 70., 69., 68., 67., 66., 65., 64., 63., 62., 61., 60., 59., 58., 57., 56., 55., 54., 53., 52., 51., 50., 49., 48., 47., 46., 45., 44., 43., 42., 41., 40., 39., 38., 37., 36., 35., 34., 33., 32., 31., 30., 29., 28., 27., 26., 25., 24., 23., 22., 21., 20., 19., 18., 17., 16., 15., 14., 13., 12., 11., 10., 9., 8., 7., 6., 5., 4., 3., 2., 1., 0., -1., -2., -3., -4., -5., -6., -7., -8., -9., -10., -11., -12., -13., -14., -15., -16., -17., -18., -19., -20., -21., -22., -23., -24., -25., -26., -27., -28., -29., -30., -31., -32., -33., -34., -35., -36., -37., -38., -39., -40., -41., -42., -43., -44., -45., -46., -47., -48., -49., -50., -51., -52., -53., -54., -55., -56., -57., -58., -59., -60., -61., -62., -63., -64., -65., -66., -67., -68., -69., -70., -71., -72., -73., -74., -75., -76., -77., -78., -79., -80., -81., -82., -83., -84., -85., -86., -87., -88., -89., -90.])
longitude
(longitude)
float64
0.0 1.0 2.0 ... 357.0 358.0 359.0
long_name :
longitude
standard_name :
longitude
units :
degrees_east
array([ 0., 1., 2., ..., 357., 358., 359.])
number
(time, step)
int64
...
long_name :
ensemble member numerical id
standard_name :
realization
units :
1
[7 values with dtype=int64]
step
(step)
timedelta64[ns]
0 days 06:00:00 ... 1 days 18:00:00
long_name :
time since forecast_reference_time
standard_name :
forecast_period
array([ 21600000000000, 43200000000000, 64800000000000, 86400000000000, 108000000000000, 129600000000000, 151200000000000], dtype='timedelta64[ns]')
time
(time)
datetime64[ns]
2017-01-01T06:00:00
long_name :
initial time of forecast
standard_name :
forecast_reference_time
array(['2017-01-01T06:00:00.000000000'], dtype='datetime64[ns]')
valid_time
(time, step)
datetime64[ns]
...
long_name :
time
standard_name :
time
[7 values with dtype=datetime64[ns]]
Data variables: (1)
w
(time, step, latitude, longitude)
float64
...
GRIB_NV :
0
GRIB_Nx :
360
GRIB_Ny :
181
GRIB_cfName :
lagrangian_tendency_of_air_pressure
GRIB_cfVarName :
w
GRIB_dataType :
cf
GRIB_gridDefinitionDescription :
Latitude/longitude. Also called equidistant cylindrical, or Plate Carree
GRIB_gridType :
regular_ll
GRIB_iDirectionIncrementInDegrees :
1.0
GRIB_iScansNegatively :
0
GRIB_jDirectionIncrementInDegrees :
1.0
GRIB_jPointsAreConsecutive :
0
GRIB_jScansPositively :
0
GRIB_latitudeOfFirstGridPointInDegrees :
90.0
GRIB_latitudeOfLastGridPointInDegrees :
-90.0
GRIB_longitudeOfFirstGridPointInDegrees :
0.0
GRIB_longitudeOfLastGridPointInDegrees :
359.0
GRIB_missingValue :
3.4028234663852886e+38
GRIB_name :
Vertical velocity
GRIB_numberOfPoints :
65160
GRIB_paramId :
135
GRIB_shortName :
w
GRIB_stepType :
instant
GRIB_stepUnits :
1
GRIB_totalNumber :
20
GRIB_typeOfLevel :
isobaricInhPa
GRIB_units :
Pa s**-1
GRIB_uvRelativeToGrid :
0
long_name :
Vertical velocity
standard_name :
lagrangian_tendency_of_air_pressure
units :
Pa s**-1
[456120 values with dtype=float64]
Attributes: (1)
typeOfLevel :
isobaricInhPa
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
stepType :
instant
Dimensions:
Coordinates: (0)
Data variables: (0)
Attributes: (1)
name :
Vertical velocity
Dimensions:
Coordinates: (0)
Inherited coordinates: (0)
Data variables: (0)
Attributes: (0)

Note: If trying out this notebook, the above way of building the aggregation will take few minutes for this GEFS S3 repository. But in general, it take more time, based on the size of the grib files

Building the aggregation faster with `idx` files¶

This method of aggregating GRIB files requires that each GRIB file be accompanied by its corresponding idx file in text format. This file, also called index files, contain some key metadata of the GRIB messages across the files. These metadata is then used to build an reference index, which helps in aggregation.

The advantage is, building aggregation this way doesn't involve scanning the whole archive of GRIB files but only a single file.

Index Dataframe made from a single Grib file¶

Here is what the contents of an idx file looks like.

1:0:d=2017010100:HGT:10 mb:12 hour fcst:ENS=low-res ctl
2:48163:d=2017010100:TMP:10 mb:12 hour fcst:ENS=low-res ctl
3:68112:d=2017010100:RH:10 mb:12 hour fcst:ENS=low-res ctl
4:79092:d=2017010100:UGRD:10 mb:12 hour fcst:ENS=low-res ctl
5:102125:d=2017010100:VGRD:10 mb:12 hour fcst:ENS=low-res ctl
6:122799:d=2017010100:HGT:50 mb:12 hour fcst:ENS=low-res ctl
7:178898:d=2017010100:TMP:50 mb:12 hour fcst:ENS=low-res ctl
8:201799:d=2017010100:RH:50 mb:12 hour fcst:ENS=low-res ctl
9:224321:d=2017010100:UGRD:50 mb:12 hour fcst:ENS=low-res ctl
10:272234:d=2017010100:VGRD:50 mb:12 hour fcst:ENS=low-res ctl
11:318288:d=2017010100:HGT:100 mb:12 hour fcst:ENS=low-res ctl
12:379010:d=2017010100:TMP:100 mb:12 hour fcst:ENS=low-res ctl
13:405537:d=2017010100:RH:100 mb:12 hour fcst:ENS=low-res ctl
14:441517:d=2017010100:UGRD:100 mb:12 hour fcst:ENS=low-res ctl
15:497421:d=2017010100:VGRD:100 mb:12 hour fcst:ENS=low-res ctl

The general format of idx data is: index:offset:date_with_runtime:variable:forecast_time:.

The metadata are separated by ":" (colon) and we need to convert it into a Dataframe for building the index.

Note: This way of building the reference index only works for a particular horizon file irrespective of the run time of the model, as the messages from a same time horizon have an identical structure

In [6]:

# converting the idx data into a dataframe
idxdf = parse_grib_idx(
    "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af006",
    storage_options=dict(anon=True),
    
)
idxdf.head()

Out[6]:

	offset	date	attrs	length	idx_uri	grib_uri
idx
1	0	d=2017010106	HGT:10 mb:6 hour fcst:ENS=low-res ctl	47493	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...
2	47493	d=2017010106	TMP:10 mb:6 hour fcst:ENS=low-res ctl	19438	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...
3	66931	d=2017010106	RH:10 mb:6 hour fcst:ENS=low-res ctl	10835	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...
4	77766	d=2017010106	UGRD:10 mb:6 hour fcst:ENS=low-res ctl	22625	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...
5	100391	d=2017010106	VGRD:10 mb:6 hour fcst:ENS=low-res ctl	20488	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...

Building a mapping between the index data and grib metadata¶

Creation of the reference index or k_index first involves generating a single mapping from the grib/zarr metadata(the grib_tree output) to the attributes in the idx files. They are unique for each time horizon, so while building the index, we need to build a unique mapping for the 1 hour forecast, the 2 hour forecast and so on.

This mapping can be made from any arbitrary GRIB file, given that the it belongs to the same time horizon of files we're trying to index.

We'll start by examining the GRIB data. The metadata that we'll be extracting will be static in nature. We're going to use a single node by accessing it with datatree.

In [7]:

s3_dt.groups

Out[7]:

('/',
 '/cape',
 '/cfrzr',
 '/cicep',
 '/cin',
 '/crain',
 '/csnow',
 '/gh',
 '/mslhf',
 '/msshf',
 '/prmsl',
 '/pwat',
 '/r',
 '/r2',
 '/sde',
 '/sdlwrf',
 '/sdswrf',
 '/sdwe',
 '/soilw',
 '/sp',
 '/st',
 '/sulwrf',
 '/suswrf',
 '/t',
 '/t2m',
 '/tcc',
 '/tmax',
 '/tmin',
 '/tp',
 '/u',
 '/u10',
 '/v',
 '/v10',
 '/w',
 '/cape/instant',
 '/cfrzr/avg',
 '/cicep/avg',
 '/cin/instant',
 '/crain/avg',
 '/csnow/avg',
 '/gh/instant',
 '/mslhf/avg',
 '/msshf/avg',
 '/prmsl/instant',
 '/pwat/instant',
 '/r/instant',
 '/r2/instant',
 '/sde/instant',
 '/sdlwrf/avg',
 '/sdswrf/avg',
 '/sdwe/instant',
 '/soilw/instant',
 '/sp/instant',
 '/st/instant',
 '/sulwrf/avg',
 '/suswrf/avg',
 '/t/instant',
 '/t2m/instant',
 '/tcc/avg',
 '/tmax/max',
 '/tmin/min',
 '/tp/accum',
 '/u/instant',
 '/u10/instant',
 '/v/instant',
 '/v10/instant',
 '/w/instant',
 '/cape/instant/pressureFromGroundLayer',
 '/cfrzr/avg/surface',
 '/cicep/avg/surface',
 '/cin/instant/pressureFromGroundLayer',
 '/crain/avg/surface',
 '/csnow/avg/surface',
 '/gh/instant/isobaricInhPa',
 '/mslhf/avg/surface',
 '/msshf/avg/surface',
 '/prmsl/instant/meanSea',
 '/pwat/instant/atmosphereSingleLayer',
 '/r/instant/isobaricInhPa',
 '/r2/instant/heightAboveGround',
 '/sde/instant/surface',
 '/sdlwrf/avg/surface',
 '/sdswrf/avg/surface',
 '/sdwe/instant/surface',
 '/soilw/instant/depthBelowLandLayer',
 '/sp/instant/surface',
 '/st/instant/depthBelowLandLayer',
 '/sulwrf/avg/nominalTop',
 '/sulwrf/avg/surface',
 '/suswrf/avg/surface',
 '/t/instant/isobaricInhPa',
 '/t2m/instant/heightAboveGround',
 '/tcc/avg/atmosphere',
 '/tmax/max/heightAboveGround',
 '/tmin/min/heightAboveGround',
 '/tp/accum/surface',
 '/u/instant/isobaricInhPa',
 '/u10/instant/heightAboveGround',
 '/v/instant/isobaricInhPa',
 '/v10/instant/heightAboveGround',
 '/w/instant/isobaricInhPa')

In [8]:

# Parsing the grib metadata from a single datatree node and converting it into a dataframe
grib_df = extract_datatree_chunk_index(s3_dt["sulwrf/avg/nominalTop"], grib_tree_store)
grib_df.head()

Out[8]:

	varname	typeOfLevel	stepType	name	step	time	valid_time	uri	offset	length	inline_value
0	sulwrf	nominalTop	avg	Surface upward long-wave radiation flux	0 days 06:00:00	2017-01-01 06:00:00	2017-01-01 12:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	3924345	43221	None
1	sulwrf	nominalTop	avg	Surface upward long-wave radiation flux	0 days 12:00:00	2017-01-01 06:00:00	2017-01-01 18:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	3951119	42550	None
2	sulwrf	nominalTop	avg	Surface upward long-wave radiation flux	0 days 18:00:00	2017-01-01 06:00:00	2017-01-02 00:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	3948238	43273	None
3	sulwrf	nominalTop	avg	Surface upward long-wave radiation flux	1 days 00:00:00	2017-01-01 06:00:00	2017-01-02 06:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	3876964	42613	None
4	sulwrf	nominalTop	avg	Surface upward long-wave radiation flux	1 days 06:00:00	2017-01-01 06:00:00	2017-01-02 12:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	3865989	42782	None

Note: Above process is part of the mapping creation, the function call to extract_datatree_chunk_index in handled inside build_idx_grib_mapping function

In [9]:

# creating a mapping for a single horizon file which is to be used later
mapping = build_idx_grib_mapping(
    "s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z.pgrb2af006",
    storage_options=dict(anon=True),
    validate=True,
)
mapping.head()

The grib hierarchy in s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z.pgrb2af006 is not unique for 54 variables: ['gh', 't', 'r', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 'u', 'v', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 'gh', 't', 'r', 'u', 'v', 't', 'r', 'u', 'v', 'gh']

Out[9]:

	offset_idx	date	attrs	length_idx	idx_uri	grib_uri	varname	typeOfLevel	stepType	name	level	step	time	valid_time	uri	offset_grib	length_grib	inline_value
idx
1	0	d=2017010100	HGT:10 mb:6 hour fcst:ENS=low-res ctl	47423	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	gh	isobaricInhPa	instant	Geopotential height	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	0	47423	None
2	47423	d=2017010100	TMP:10 mb:6 hour fcst:ENS=low-res ctl	19684	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	t	isobaricInhPa	instant	Temperature	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	47423	19684	None
3	67107	d=2017010100	RH:10 mb:6 hour fcst:ENS=low-res ctl	10334	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	r	isobaricInhPa	instant	Relative humidity	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	67107	10334	None
4	77441	d=2017010100	UGRD:10 mb:6 hour fcst:ENS=low-res ctl	23094	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	u	isobaricInhPa	instant	U component of wind	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	77441	23094	None
5	100535	d=2017010100	VGRD:10 mb:6 hour fcst:ENS=low-res ctl	20427	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	v	isobaricInhPa	instant	V component of wind	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	100535	20427	None

Note: Reference index can be combined across many horizons but each horizon must be indexed separately.

Building the index¶

Now if we parse the runtime from the idx file and other attributes, we can build a fully compatible kerchunk index(k_index) for that particular file. Before creating the index, we need to clean some of the data in the mapping and index dataframe for the some variables as they tend to contain duplicate values, as demonstrated below.

In [10]:

# cleaning the mapping
mapping.loc[~mapping["attrs"].duplicated(keep="first"), :].head()

Out[10]:

	offset_idx	date	attrs	length_idx	idx_uri	grib_uri	varname	typeOfLevel	stepType	name	level	step	time	valid_time	uri	offset_grib	length_grib	inline_value
idx
1	0	d=2017010100	HGT:10 mb:6 hour fcst:ENS=low-res ctl	47423	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	gh	isobaricInhPa	instant	Geopotential height	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	0	47423	None
2	47423	d=2017010100	TMP:10 mb:6 hour fcst:ENS=low-res ctl	19684	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	t	isobaricInhPa	instant	Temperature	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	47423	19684	None
3	67107	d=2017010100	RH:10 mb:6 hour fcst:ENS=low-res ctl	10334	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	r	isobaricInhPa	instant	Relative humidity	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	67107	10334	None
4	77441	d=2017010100	UGRD:10 mb:6 hour fcst:ENS=low-res ctl	23094	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	u	isobaricInhPa	instant	U component of wind	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	77441	23094	None
5	100535	d=2017010100	VGRD:10 mb:6 hour fcst:ENS=low-res ctl	20427	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	v	isobaricInhPa	instant	V component of wind	0.0	0 days 06:00:00	2017-01-01	2017-01-01 06:00:00	s3://noaa-gefs-pds/gefs.20170101/00/gec00.t00z...	100535	20427	None

In [11]:

# this step will be performed for every idx dataframe where we will be using the "mapping" dataframe which we created previously
mapped_index = map_from_index(
    pd.Timestamp("2017-01-01T06"),
    mapping.loc[~mapping["attrs"].duplicated(keep="first"), :],
    idxdf.loc[~idxdf["attrs"].duplicated(keep="first"), :],
)
mapped_index.head()

Out[11]:

	varname	typeOfLevel	stepType	name	step	time	valid_time	uri	offset	length	inline_value
0	gh	isobaricInhPa	instant	Geopotential height	0 days 06:00:00	2017-01-01 06:00:00	2017-01-01 12:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	0	47493	None
1	t	isobaricInhPa	instant	Temperature	0 days 06:00:00	2017-01-01 06:00:00	2017-01-01 12:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	47493	19438	None
2	r	isobaricInhPa	instant	Relative humidity	0 days 06:00:00	2017-01-01 06:00:00	2017-01-01 12:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	66931	10835	None
3	u	isobaricInhPa	instant	U component of wind	0 days 06:00:00	2017-01-01 06:00:00	2017-01-01 12:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	77766	22625	None
4	v	isobaricInhPa	instant	V component of wind	0 days 06:00:00	2017-01-01 06:00:00	2017-01-01 12:00:00	s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z...	100391	20488	None

Final step of building of Aggregation¶

For the final step of the aggregation, we will create an index for each GRIB file to cover a two-month period. We will be using the 6-hour horizon file for building the aggregation, this will be from 2017-01-01 to 2017-02-28. The generated index can then be combined with indexes of other time horizons and stored for later use.

In [12]:

%%time
mapped_index_list = []

deduped_mapping = mapping.loc[~mapping["attrs"].duplicated(keep="first"), :]

# this process is manually done because the runtime and forecast time will vary between models i.e. GEFS, GFS, HRRR etc.
for date in pd.date_range("2017-01-01", "2017-02-28"):
    for runtime in range(0, 24, 6):
        fname = f"s3://noaa-gefs-pds/gefs.{date.strftime('%Y%m%d')}/{runtime:02}/gec00.t{runtime:02}z.pgrb2af006"
    
        idxdf = parse_grib_idx(basename=fname, storage_options=dict(anon=True))
        
        mapped_index = map_from_index(
            pd.Timestamp(date + datetime.timedelta(hours=runtime)),
            deduped_mapping,
            idxdf.loc[~idxdf["attrs"].duplicated(keep="first"), :],
        )
    
        mapped_index_list.append(mapped_index)

s3_kind = pd.concat(mapped_index_list)

CPU times: user 9.21 s, sys: 303 ms, total: 9.51 s
Wall time: 1min 15s

Tip: To confirm the above step, check out this notebook

Using the aggregation¶

The difference between .idx and Kerchunk index that we built is that the former indexes the GRIB messages and the latter indexes the variables in those messages, in a time horizon. Now we'll need a tree model from grib_tree function to reinflate index (variables in the messages). The important point to note here is that the tree model should be made from the GRIB files of the repository that we are indexing.

In [13]:

grib_tree_store = grib_tree(
    scan_grib(
        "s3://noaa-gefs-pds/gefs.20170101/06/gec00.t06z.pgrb2af006",
        storage_options=dict(anon=True),
    ),
    remote_options=dict(anon=True),
)

/home/rsignell/miniforge3/envs/grib-idx/lib/python3.12/site-packages/kerchunk/combine.py:376: UserWarning: Concatenated coordinate 'time' contains less than expectednumber of values across the datasets: [1483250400]
  warnings.warn(
/home/rsignell/miniforge3/envs/grib-idx/lib/python3.12/site-packages/kerchunk/combine.py:376: UserWarning: Concatenated coordinate 'step' contains less than expectednumber of values across the datasets: [6]
  warnings.warn(

Then we need to run that tree model through strip_datavar_chunks function, which will strip the tree of the variables in place. This step is optional

In [14]:

deflated_s3_grib_tree_store = copy.deepcopy(
    grib_tree_store
)  # not affecting the original tree model
strip_datavar_chunks(deflated_s3_grib_tree_store)

After stripping the tree model, we need to introduce two new axes: the runtime used for mapping and date_range for indexing the new reinflated tree.

In [15]:

axes = [
    pd.Index(
        [
            pd.timedelta_range(
                start="0 hours", end="6 hours", freq="6h", closed="right", name="6 hour"
            ),
        ],
        name="step",
    ),
    pd.date_range(
        "2017-01-01T00:00", "2017-02-28T18:00", freq="360min", name="valid_time"
    ),
]
axes

Out[15]:

[Index([[0 days 06:00:00]], dtype='object', name='step'),
 DatetimeIndex(['2017-01-01 00:00:00', '2017-01-01 06:00:00',
                '2017-01-01 12:00:00', '2017-01-01 18:00:00',
                '2017-01-02 00:00:00', '2017-01-02 06:00:00',
                '2017-01-02 12:00:00', '2017-01-02 18:00:00',
                '2017-01-03 00:00:00', '2017-01-03 06:00:00',
                ...
                '2017-02-26 12:00:00', '2017-02-26 18:00:00',
                '2017-02-27 00:00:00', '2017-02-27 06:00:00',
                '2017-02-27 12:00:00', '2017-02-27 18:00:00',
                '2017-02-28 00:00:00', '2017-02-28 06:00:00',
                '2017-02-28 12:00:00', '2017-02-28 18:00:00'],
               dtype='datetime64[ns]', name='valid_time', length=236, freq='360min')]

Now for reinflating, we'll be needing the aggregation types which are: horizon, valid_time, run_time and best_available. We will also be needing the variable(s) that we are reinflating.

In [16]:

s3_store = reinflate_grib_store(
    axes=axes,
    aggregation_type=AggregationType.HORIZON,
    chunk_index=s3_kind.loc[s3_kind.varname.isin(["sulwrf", "prmsl"])],
    zarr_ref_store=deflated_s3_grib_tree_store,
)

/home/rsignell/miniforge3/envs/grib-idx/lib/python3.12/site-packages/kerchunk/_grib_idx.py:347: PerformanceWarning: indexing past lexsort depth may impact performance.
  if lookup not in unique_groups:

Viewing the new subset of the datatree¶

In this step, we can view the new subset as a datatree model.

In [17]:

s3_dt_subset = xr.open_datatree(
    fsspec.filesystem(
        "reference", fo=s3_store, remote_protocol="s3", remote_options={"anon": True}
    ).get_mapper(""),
    engine="zarr",
    consolidated=False,
)

In [18]:

s3_dt_subset.groups

Out[18]:

('/',
 '/prmsl',
 '/sulwrf',
 '/prmsl/instant',
 '/sulwrf/avg',
 '/prmsl/instant/meanSea',
 '/sulwrf/avg/nominalTop',
 '/sulwrf/avg/surface')

In [19]:

da = s3_dt_subset.sulwrf.avg.nominalTop.sulwrf.isel(model_horizons=0)
da

Create an index for time¶

In [20]:

da= da.rename({'valid_times':'time'}).drop_vars(['step'])

/tmp/ipykernel_134388/309788138.py:1: UserWarning: rename 'valid_times' to 'time' does not create an index anymore. Try using swap_dims instead or use set_index after rename to create an indexed coordinate.
  da= da.rename({'valid_times':'time'}).drop_vars(['step'])

In [21]:

da = da.set_index(time='time')

In [22]:

da

In [23]:

da.sel(time='2017-01-02', method='nearest')

Try extracting some data!¶

Time series extraction with GRIB is slow because one needs to read and uncompress the entire dataset: Each data chunk covers the entire spatial domain!

In [25]:

%%time
da[:,90,180].load()

In [ ]: