These flags are important to properly use the data. Data not flagged as microwave are sourced from an infrared sensor. The lake and river flags are currently not set, but defined in GDS2.0r4. The aerosol flag indicates high aerosol concentration. The analysis flag indicates high difference from analysis temperatures (differences greater than Analysis Limit). The lowwind flag indicates regions of low wind speed (typically less than the low Wind Limit) per NWP model. The highwind flag indicates regions of high wind speed (typically greater than the high Wind Limit) per NWP model. See wind limits in the comment field for the actual values. The edge flag indicates pixel sizes that are larger than Pixel Spread times the size of the pixel in the center of the field of view in either lat or lon direction. The terminator flag indicates that the sun is near the horizon. The reflector flag indicates that the satellite would receive direct reflected sunlight if the earth was a perfect mirror. The swath flag is used in gridded files to indicate if the pixel could have been seen by the satellite. delta_dn indicates that the day.night sst algorithm was different from the standard algorithm. Other flags may be populated and are for internal use and the definitions may change, so should not be relied on. Flags greater than 64 only apply to non-land pixels
flag_meanings :
microwave land ice lake river reserved aerosol analysis lowwind highwind edge terminator reflector swath delta_dn
These are the overall quality indicators and are used for all GHRSST SSTs. In this case they are a function of distance to cloud, satellite zenith angle, and day/night
Any use of these data requires the following acknowledgment: "HRPT AVHRR SSTfoundation retrievals were produced by the Australian Bureau of Meteorology as a contribution to the Integrated Marine Observing System - an initiative of the Australian Government being conducted as part of the National Collaborative Research Infrastructure Strategy and the Super Science Initiative." The imagery data were acquired from NOAA spacecraft by the Bureau, Australian Institute of Marine Science, Australian Commonwealth Scientific and Industrial Research Organization, Geoscience Australia, and Western Australian Satellite Technology and Applications Consortium.
cdm_data_type :
grid
comment :
HRPT AVHRR experimental L3 retrieval produced by the Australian Bureau of Meteorology as a contribution to the Integrated Marine Observing System. SSTs were calibrated to drifting buoy depths (~20-30cm) under surface mixing wind conditions (>2m/s night, >6m/s day). SSTdepth observations were rejected if wind speeds were <2 m/s (night) or <6 m/s (day) to eliminate effects of potential diurnal warming and produce an estimate of foundation SST. SSTs are a weighted average of the SSTs of contributing pixels (weighted by sses_standard_deviation^-2).
WARNING: some applications are unable to properly handle signed byte values. If byte values >127 are encountered, subtract 256 from this reported value. GRID:CONTINENTAL, SYSCODE:PRODUCTION
compliance_checker_imos_version :
1.1.1
compliance_checker_version :
2.3.1
compliance_checks_passed :
cf ghrsst:1.0
creator_email :
ghrsst@bom.gov.au
creator_name :
Australian Bureau of Meteorology
creator_url :
http://imos.org.au
date_created :
20141010T201443Z
easternmost_longitude :
-170.00999450683594
file_quality_level :
3
gds_version_id :
2.0r4
geospatial_lat_resolution :
0.019999999552965164
geospatial_lat_units :
degrees_north
geospatial_lon_resolution :
0.019999999552965164
geospatial_lon_units :
degrees_east
history :
platform_counts=NOAA-18=2;NOAA-17=2,quality_counts=archive=4,platform=NOAA-18;NOAA-17,quality_source=archive,ice_source=SSMI-NCEP-Analysis-ICE-5min,adi_source=OSDPD-AOD-Analysis-weekly,wind_source=GASP-ABOM-Analysis-WSP,analysis_source=NCDC-L4LRblend-GLOB-AVHRR_OI,source_file=20071028152000-ABOM-L3C_GHRSST-SSTskin-AVHRR18_D-1d_night-v02.0-fv02.0.nc;20071028032000-ABOM-L3C_GHRSST-SSTskin-AVHRR18_D-1d_day-v02.0-fv02.0.nc;20071028152000-ABOM-L3C_GHRSST-SSTskin-AVHRR17_D-1d_night-v02.0-fv02.0.nc;20071028032000-ABOM-L3C_GHRSST-SSTskin-AVHRR17_D-1d_day-v02.0-fv02.0.nc,l3_file=20071028152000-ABOM-L3C_GHRSST-SSTskin-AVHRR18_D-1d_night-v02.0-fv02.0.nc;20071028032000-ABOM-L3C_GHRSST-SSTskin-AVHRR18_D-1d_day-v02.0-fv02.0.nc;20071028152000-ABOM-L3C_GHRSST-SSTskin-AVHRR17_D-1d_night-v02.0-fv02.0.nc;20071028032000-ABOM-L3C_GHRSST-SSTskin-AVHRR17_D-1d_day-v02.0-fv02.0.nc,l3_source=AVHRR18_D-ABOM-L3C-v02.0;AVHRR17_D-ABOM-L3C-v02.0,global_source=wind_source=GASP-ABOM-Analysis-WSP,analysis_source=NCDC-L4LRblend-GLOB-AVHRR_OI,adi_source=OSDPD-AOD-Analysis-weekly,ice_source=SSMI-NCEP-Analysis-ICE-5min,l3_source=AVHRR18_D-ABOM-L3C-v02.0;AVHRR17_D-ABOM-L3C-v02.0,landmask_file=lsmask.dist5.5.nc,landmask_reference=Naval Oceanographic Office (NAVOCEANO),landmask_URL=https://www.ghrsst.org/data/ghrsst-data-tools/navo-ghrsst-pp-land-sea-mask/,landmask_source=NAVOCEANO 1km Version 5.5,ice_reference=US National Weather Service - NCEP,ice_URL=http://polar.ncep.noaa.gov/seaice/Analyses.html,ice_file=20071027.ice_data.5min.nc,ice_jdate=2454401,merge_tool=mergeL3U,mergeL3U_version=3937:3938M,quality=archive,mergeL3U_quality=archive
2017-01-13 23:07:28 UTC: passed compliance checks: cf ghrsst:1.0 (IOOS compliance checker version 2.3.1, IMOS plugin version 1.1.1)
id :
AVHRR_D-ABOM-L3S-v02.0
institution :
ABOM
keywords :
Oceans > Ocean Temperature > Sea Surface Temperature
keywords_vocabulary :
NASA Global Change Master Directory (GCMD) Science Keywords
license :
GHRSST protocol describes data use as free and open
importmatplotlib.pyplotaspltimportpandasaspdimporttracebackdefplot_sst(ds,start_date,lon_slice,lat_slice):""" Plots SST data for 6 consecutive days starting from start_date. Parameters: - ds: xarray.Dataset containing the SST data. - start_date: str, start date in 'YYYY-MM-DD' format. - lon_slice: tuple, longitude slice (start_lon, end_lon). - lat_slice: tuple, latitude slice (start_lat, end_lat). """# Parse the start datestart_date_parsed=pd.to_datetime(start_date)# Ensure the dataset has a time dimension and it's sortedassert'time'inds.dims,"Dataset does not have a 'time' dimension"ds=ds.sortby('time')# Find the nearest date in the datasetnearest_date=ds.sel(time=start_date_parsed,method='nearest').time# Get the index of the nearest datenearest_date_index=ds.time.where(ds.time==nearest_date,drop=True).squeeze().values# Find the position of the nearest date in the time arraynearest_date_position=int((ds.time==nearest_date_index).argmax().values)# Get the next 6 date values including the nearest datedates=ds.time[nearest_date_position:nearest_date_position+6].valuesdates=[pd.Timestamp(date)fordateindates]print(dates)# Create subplotsfig,axes=plt.subplots(nrows=2,ncols=3,figsize=(18,10))axes=axes.flatten()# Plot SST for each dateforax,dateinzip(axes,dates):try:sst_data_kelvin=ds.sea_surface_temperature.sel(time=date.strftime('%Y-%m-%d'),lon=slice(lon_slice[0],lon_slice[1]),lat=slice(lat_slice[0],lat_slice[1]))# Convert Kelvin to Celsius for plottingsst_data_celsius=sst_data_kelvin-273.15sst_data_celsius.plot(ax=ax,cmap='coolwarm',cbar_kwargs={'label':'SST (°C)'})# Using 'coolwarm' colormapax.set_title(date.strftime('%Y-%m-%d'))exceptKeyError:# Print traceback for the KeyError#traceback.print_exc()# Handle the case where data for a specific date is not availableax.set_title(f"No data for {date.strftime('%Y-%m-%d')}")ax.axis('off')# Adjust layoutplt.tight_layout()plt.show()