In [1]:

import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import ACTDR
import netCDF4 as nc
from salishsea_tools import viz_tools
import numpy as np
import datetime
from salishsea_tools import tidetools

import comparisons

%matplotlib inline

In [2]:

sns.set_style('darkgrid')

In [3]:

grid_B = nc.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc')
paths = {'nowcast': '/results/SalishSea/nowcast/',
        'spinup': '/results/SalishSea/spin-up/'}

In [4]:

ACTDR.load_dat('SOG_2000.dat')

('> open ', 'SOG_2000.dat')
> load CTD_DAT
> load STANDARD_KEYS
('> close ', 'SOG_2000.dat')
> complete

In [5]:

data = pd.DataFrame(ACTDR.CTD_DAT)

In [6]:

data_fall = data[(data.Year>=2014) & (data.Month >=10)  ]

In [7]:

fig,axm = plt.subplots(1,figsize=(8,5))
data_fall.plot(x='Longitude',y='Latitude',kind='scatter', marker='o',ax=axm)
viz_tools.plot_coastline(axm,grid_B,coords='map')

/home/nsoontie/anaconda3/envs/py2/lib/python2.7/site-packages/matplotlib/collections.py:650: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors_original != str('face'):

Out[7]:

<matplotlib.contour.QuadContourSet instance at 0x7f5d23108b48>

/home/nsoontie/anaconda3/envs/py2/lib/python2.7/site-packages/matplotlib/collections.py:590: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
  if self._edgecolors == str('face'):

In [8]:

data_fall.hist('Month',bins=np.arange(0.5,13.5))

Out[8]:

array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f5d22ddbbd0>]], dtype=object)

In [9]:

data_fall.hist('Day')

Out[9]:

array([[<matplotlib.axes._subplots.AxesSubplot object at 0x7f5d22ccc590>]], dtype=object)

Southern Strait of Georgia¶

In [20]:

lon_min=-124
lon_max=-123
lat_min=48.8
lat_max=49.35
data_SOG  = comparisons.isolate_region(data_fall,lon_min, lon_max, lat_min, lat_max)

In [21]:

zmax= 50
grouped = data_SOG.groupby('Month')
model_year=2014
for month in grouped.groups.keys():
    fig = comparisons.compare_model_obs(month,model_year,'Salinity',data_SOG,paths['nowcast'],zmax=zmax,vmin=10,
                                        vmax=31.5, xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

No model data for 1/10
No model data for 1/10
No model data for 2/10
No model data for 2/10
No model data for 3/10
No model data for 3/10
No model data for 2/10
No model data for 3/10

In [22]:

month=10
fig=comparisons.compare_cast_hourly(month,2014,'Salinity',data_SOG,paths['nowcast'],zmax=zmax,vmin=10,vmax=31.5,
                                  xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

In late October, most of the surface water in the southern Strait of Georgia is too salty.

In [23]:

month=12
fig=comparisons.compare_cast_hourly(month,2014,'Salinity',data_SOG,paths['nowcast'],zmax=zmax,vmin=10,vmax=31.5,
                                  xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

Strait of Georgia North¶

In [13]:

lon_min=-125.1
lon_max=-123
lat_min=49.35
lat_max=50
data_SOGN  = comparisons.isolate_region(data_fall,lon_min, lon_max, lat_min, lat_max)

In [14]:

zmax= 50
grouped = data_SOGN.groupby('Month')
model_year=2014
for month in grouped.groups.keys():
    fig = comparisons.compare_model_obs(month,model_year,'Salinity',data_SOGN,paths['nowcast'],zmax=zmax,vmin=10,
                                        vmax=31.5, xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

No model data for 1/10
No model data for 4/10
No model data for 4/10
No model data for 5/10
No model data for 5/10
No model data for 5/10
No model data for 6/10
No model data for 7/10
No model data for 7/10
No model data for 8/10
No model data for 8/10

In [15]:

month = 10
fig=comparisons.compare_cast_hourly(month,2014,'Salinity',data_SOGN,paths['nowcast'],zmax=zmax,vmin=20,vmax=31.5,
                                  xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

East of Texada Isalnd is too salty in the surface
Very north is too fresh in the surface. As we go furter south, we start to get too salty in the surface.

Strait of Juan de Fuca¶

In [24]:

lon_min=-125
lon_max=-123
lat_min=48
lat_max=48.48
data_JDF  = comparisons.isolate_region(data_fall,lon_min, lon_max, lat_min, lat_max)

In [25]:

zmax= 200
grouped = data_JDF.groupby('Month')
model_year=2014
for month in grouped.groups.keys():
    fig = comparisons.compare_model_obs(month,model_year,'Salinity',data_JDF,paths['nowcast'],zmax=zmax,vmin=30,
                                        vmax=34, xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

No model data for 16/10
No model data for 16/10
No model data for 16/10

In [26]:

month = 10
fig=comparisons.compare_cast_hourly(month,2014,'Salinity',data_JDF,paths['nowcast'],zmax=zmax,vmin=30,vmax=34,
                                  xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

Surface and intermediate JdF is too salty (above 150m)
Deep is ok (below 150m) but there aren't a lot of cats that go that deep.
It looks like the salinity gradients are too small and too shallow in the model, especially west of -123.5.

Haro¶

In [30]:

lon_min=-123.49
lon_max=-122
lat_min=48.48
lat_max=48.8
data_haro  = comparisons.isolate_region(data_fall,lon_min, lon_max, lat_min, lat_max)

In [31]:

zmax= 300
grouped = data_haro.groupby('Month')
model_year=2014
for month in grouped.groups.keys():
    fig = comparisons.compare_model_obs(month,model_year,'Salinity',data_haro,paths['nowcast'],zmax=zmax,
                                        vmin=28,vmax=32, xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

In [32]:

month = 10
fig=comparisons.compare_cast_hourly(month,2014,'Salinity',data_haro,paths['nowcast'],
                                    zmax=zmax,vmin=28,vmax=32,
                                    xmin=lon_min,xmax=lon_max,ymin=lat_min,ymax=lat_max)

For these two casts, we look ok in Haro.

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