Comparison reading GOES-R data from AWS S3 in netCDF versus zarr¶
- Funding: Interagency Implementation and Advanced Concepts Team IMPACT for the Earth Science Data Systems (ESDS) program and AWS Public Dataset Program
- Software developed for OceanHackWeek 2020
Credits: Tutorial development¶
- Dr. Chelle Gentemann - Twitter - Farallon Institute
Why data format matters¶
- NetCDF sprinkles metadata throughout files, making them slow to access and read data
- Zarr consolidates the metadata, making them FAST for access and reading
This was developed for oceanhackweek¶
- The zarr files are not permanent. To test this part yourself you will need to create zarr files and write to an s3 bucket that you have read/write access.
In [1]:
#libraries
import datetime as dt
import xarray as xr
import fsspec
import s3fs
import os.path
import matplotlib.pyplot as plt
# make datasets display nicely
xr.set_options(display_style="html")
#magic fncts #put static images of your plot embedded in the notebook
%matplotlib inline
plt.rcParams['figure.figsize'] = 12, 6
%config InlineBackend.figure_format = 'retina'
Define a function to read the netCDF data¶
- The last 30 days are on S3 standard access, after that it is move to infrequent access
- It takes about 3 minutes to connect to a days worth of data for a single product
In [2]:
def get_geo_data(sat,lyr,idyjl):
# arguments
# sat goes-east,goes-west,himawari
# lyr year
# idyjl day of year
d = dt.datetime(lyr,1,1) + dt.timedelta(days=idyjl)
fs = s3fs.S3FileSystem(anon=True) #connect to s3 bucket!
#create strings for the year and julian day
imon,idym=d.month,d.day
syr,sjdy,smon,sdym = str(lyr).zfill(4),str(idyjl).zfill(3),str(imon).zfill(2),str(idym).zfill(2)
#use glob to list all the files in the directory
if sat=='goes-east':
file_location,var = fs.glob('s3://noaa-goes16/ABI-L2-SSTF/'+syr+'/'+sjdy+'/*/*.nc'),'SST'
if sat=='goes-west':
file_location,var = fs.glob('s3://noaa-goes17/ABI-L2-SSTF/'+syr+'/'+sjdy+'/*/*.nc'),'SST'
if sat=='himawari':
file_location,var = fs.glob('s3://noaa-himawari8/AHI-L2-FLDK-SST/'+syr+'/'+smon+'/'+sdym+'/*/*L2P*.nc'),'sea_surface_temperature'
#make a list of links to the file keys
if len(file_location)<1:
return file_ob
file_ob = [fs.open(file) for file in file_location] #open connection to files
#open all the day's data
ds = xr.open_mfdataset(file_ob,combine='nested',concat_dim='time') #note file is super messed up formatting
#clean up coordinates which are a MESS in GOES
#rename one of the coordinates that doesn't match a dim & should
if not sat=='himawari':
ds = ds.rename({'t':'time'})
ds = ds.reset_coords()
else:
ds = ds.rename({'ni':'x','nj':'y'}) #for himawari change dims to match goes
#put in to Celsius
#ds[var] -= 273.15 #nice python shortcut to +- from itself a-=273.15 is the same as a=a-273.15
#ds[var].attrs['units'] = '$^\circ$C'
return ds
Open a day of GOES-16 (East Coast) Data and plot the average SST - netCDF¶
In [3]:
%%time
lyr, idyjl = 2020, 210
ds = get_geo_data('goes-east',lyr,idyjl)
CPU times: user 15.2 s, sys: 2.31 s, total: 17.5 s Wall time: 2min 45s
In [4]:
%%time
subset = ds.sel(x=slice(-0.01,0.06),y=slice(0.12,0.09)) #reduce to GS region
masked = subset.SST.where(subset.DQF==0)
mean_dy = masked.mean('time',skipna=True) #here I want all possible values so skipna=True
mean_dy.plot(vmin=16+273.15,vmax=29+273.15,cmap='inferno')
CPU times: user 1min 46s, sys: 34.1 s, total: 2min 20s Wall time: 19min 19s
/srv/conda/envs/notebook/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
Out[4]:
<matplotlib.collections.QuadMesh at 0x7f5e4d9bbf10>
Exact same process, but with Zarr file stored on S3 us-east-1, just like the netcdf files above¶
In [5]:
%%time
file_location = 's3://ohw-bucket-us-east-1/goes_zarr'
ikey = fsspec.get_mapper(file_location,anon=False)
ds = xr.open_zarr(ikey)
ds
CPU times: user 967 ms, sys: 0 ns, total: 967 ms Wall time: 24.1 s
Out[5]:
<xarray.Dataset>
Dimensions: (SST_day_night_emissive_bands: 4, SST_night_only_emissive_band: 1, number_of_LZA_bounds: 2, number_of_SZA_bounds: 2, number_of_image_bounds: 2, number_of_time_bounds: 2, time: 24, x: 5424, y: 5424)
Coordinates:
* time (time) datetime64[ns] ...
* x (x) float32 -0.15...
* y (y) float32 0.151...
Dimensions without coordinates: SST_day_night_emissive_bands, SST_night_only_emissive_band, number_of_LZA_bounds, number_of_SZA_bounds, number_of_image_bounds, number_of_time_bounds
Data variables:
DQF (time, y, x) float32 dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
SST (time, y, x) float32 dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
SST_day_night_emissive_band_ids (SST_day_night_emissive_bands) int8 dask.array<chunksize=(4,), meta=np.ndarray>
SST_day_night_emissive_wavelengths (SST_day_night_emissive_bands) float32 dask.array<chunksize=(4,), meta=np.ndarray>
SST_night_only_emissive_band_id (SST_night_only_emissive_band) int8 dask.array<chunksize=(1,), meta=np.ndarray>
SST_night_only_emissive_wavelength (SST_night_only_emissive_band) float32 dask.array<chunksize=(1,), meta=np.ndarray>
algorithm_dynamic_input_data_container (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
algorithm_product_version_container (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
day_solar_zenith_angle float32 ...
day_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
geospatial_lat_lon_extent (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
goes_imager_projection (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
max_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
max_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
maximum_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
mean_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
mean_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
mean_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
min_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
min_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
minimum_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
night_solar_zenith_angle float32 ...
night_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
nominal_satellite_height (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
nominal_satellite_subpoint_lat (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
nominal_satellite_subpoint_lon (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
number_of_day_SST_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
number_of_night_SST_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
number_of_twilight_SST_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
percent_uncorrectable_GRB_errors (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
percent_uncorrectable_L0_errors (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
processing_parm_version_container (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
quantitative_local_zenith_angle float32 ...
quantitative_local_zenith_angle_bounds (time, number_of_LZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
retrieval_local_zenith_angle float32 ...
retrieval_local_zenith_angle_bounds (time, number_of_LZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
retrieval_solar_zenith_angle float32 ...
retrieval_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
sea_surface_temp_outlier_pixel_count (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
standard_deviation_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
std_dev_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
std_dev_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
time_bounds (time, number_of_time_bounds) datetime64[ns] dask.array<chunksize=(24, 2), meta=np.ndarray>
total_number_of_degraded_quality_ocean_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
total_number_of_good_quality_ocean_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
total_number_of_severely_degraded_quality_ocean_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
total_number_of_unprocessed_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
twilight_solar_zenith_angle (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
twilight_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
x_image float32 ...
x_image_bounds (time, number_of_image_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
y_image float32 ...
y_image_bounds (time, number_of_image_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
Attributes:
Conventions: CF-1.7
Metadata_Conventions: Unidata Dataset Discovery v1.0
_FillValue: [-999.0]
cdm_data_type: Image
cell_methods: quantitative_local_zenith_angle: sum retrieval...
dataset_name: OR_ABI-L2-SSTF-M6_G16_s20202100000205_e2020210...
date_created: 2020-07-28T01:05:45.6Z
grid_mapping: goes_imager_projection
id: 14a121c9-41b8-4552-9c28-69e6bcd4952f
institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...
instrument_ID: FM1
instrument_type: GOES R Series Advanced Baseline Imager
iso_series_metadata_id: d70be540-c38a-11e0-962b-0800200c9a66
keywords: OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPE...
keywords_vocabulary: NASA Global Change Master Directory (GCMD) Ear...
license: Unclassified data. Access is restricted to ap...
long_name: standard deviation of the difference of the ob...
naming_authority: gov.nesdis.noaa
orbital_slot: GOES-East
platform_ID: G16
processing_level: National Aeronautics and Space Administration ...
production_data_source: Realtime
production_environment: OE
production_site: NSOF
project: GOES
scene_id: Full Disk
spatial_resolution: 2km at nadir
standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)
summary: The ABI Sea Surface Temperature (SST) is calcu...
time_coverage_end: 2020-07-28T00:59:51.3Z
time_coverage_start: 2020-07-28T00:00:20.5Z
timeline_id: ABI Mode 6
title: ABI L2 Sea Surface (Skin) Temperature
units: Kxarray.Dataset
- SST_day_night_emissive_bands: 4
- SST_night_only_emissive_band: 1
- number_of_LZA_bounds: 2
- number_of_SZA_bounds: 2
- number_of_image_bounds: 2
- number_of_time_bounds: 2
- time: 24
- x: 5424
- y: 5424
- time(time)datetime64[ns]2020-07-28T00:30:05.934142976 .....
- axis :
- T
- bounds :
- time_bounds
- long_name :
- J2000 epoch mid-point between the start and end image scan in seconds
- standard_name :
- time
array(['2020-07-28T00:30:05.934142976', '2020-07-28T01:30:05.901723008', '2020-07-28T02:30:05.864743936', '2020-07-28T03:30:05.828807936', '2020-07-28T04:30:05.789944960', '2020-07-28T05:30:05.866763904', '2020-07-28T06:30:05.943120000', '2020-07-28T07:30:05.902876032', '2020-07-28T08:30:05.866008960', '2020-07-28T09:30:05.823889024', '2020-07-28T10:30:05.785832960', '2020-07-28T11:30:05.747997056', '2020-07-28T12:30:05.725508992', '2020-07-28T13:30:05.716819072', '2020-07-28T14:30:05.711737088', '2020-07-28T15:30:05.688460928', '2020-07-28T16:30:05.651743104', '2020-07-28T17:30:05.499197056', '2020-07-28T18:30:05.346963968', '2020-07-28T19:30:05.309723008', '2020-07-28T20:30:05.273282944', '2020-07-28T21:30:05.235561984', '2020-07-28T22:30:05.200251008', '2020-07-28T23:30:05.159278080'], dtype='datetime64[ns]') - x(x)float32-0.151844 -0.151788 ... 0.151844
- axis :
- X
- long_name :
- GOES fixed grid projection x-coordinate
- standard_name :
- projection_x_coordinate
- units :
- rad
array([-0.151844, -0.151788, -0.151732, ..., 0.151732, 0.151788, 0.151844], dtype=float32) - y(y)float320.151844 0.151788 ... -0.151844
- axis :
- Y
- long_name :
- GOES fixed grid projection y-coordinate
- standard_name :
- projection_y_coordinate
- units :
- rad
array([ 0.151844, 0.151788, 0.151732, ..., -0.151732, -0.151788, -0.151844], dtype=float32)
- DQF(time, y, x)float32dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: point quantitative_local_zenith_angle: point retrieval_solar_zenith_angle: point t: point area: point
- coordinates :
- retrieval_local_zenith_angle quantitative_local_zenith_angle retrieval_solar_zenith_angle t y x
- flag_meanings :
- good_quality_qf degraded_quality_qf severely_degraded_quality_qf invalid_due_to_unprocessed_qf
- flag_values :
- [0, 1, 2, 3]
- grid_mapping :
- goes_imager_projection
- long_name :
- ABI L2+ Sea Surface (Skin) Temperature data quality flags
- number_of_qf_values :
- [4]
- percent_degraded_quality_qf :
- [0.02484860084950924]
- percent_good_quality_qf :
- [0.1703146994113922]
- percent_invalid_due_to_unprocessed_qf :
- [0.5447992086410522]
- percent_severely_degraded_quality_qf :
- [0.5365844964981079]
- standard_name :
- status_flag
- units :
- 1
- valid_range :
- [0, 3]
Array Chunk Bytes 2.82 GB 117.68 MB Shape (24, 5424, 5424) (1, 5424, 5424) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - SST(time, y, x)float32dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
- algorithm_type :
- regression
- ancillary_variables :
- DQF
- cell_methods :
- retrieval_local_zenith_angle: point (good or degraded quality pixel produced) quantitative_local_zenith_angle: point (good quality pixel produced) retrieval_solar_zenith_angle: point (good quality pixel produced) t: point area: point
- coordinates :
- retrieval_local_zenith_angle quantitative_local_zenith_angle retrieval_solar_zenith_angle t y x
- grid_mapping :
- goes_imager_projection
- long_name :
- ABI L2+ Sea Surface (Skin) Temperature
- resolution :
- y: 0.000056 rad x: 0.000056 rad
- standard_name :
- sea_surface_skin_temperature
- units :
- K
- valid_range :
- [0, -6]
Array Chunk Bytes 2.82 GB 117.68 MB Shape (24, 5424, 5424) (1, 5424, 5424) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - SST_day_night_emissive_band_ids(SST_day_night_emissive_bands)int8dask.array<chunksize=(4,), meta=np.ndarray>
- long_name :
- ABI band identifiers used to generate Sea Surface (Skin) Temperature product (day and night pixels)
- standard_name :
- sensor_band_identifier
- units :
- 1
Array Chunk Bytes 4 B 4 B Shape (4,) (4,) Count 2 Tasks 1 Chunks Type int8 numpy.ndarray - SST_day_night_emissive_wavelengths(SST_day_night_emissive_bands)float32dask.array<chunksize=(4,), meta=np.ndarray>
- long_name :
- ABI band central emissive wavelengths used to generate Sea Surface (Skin) Temperature product (day and night pixels)
- standard_name :
- sensor_band_central_radiation_wavelength
- units :
- um
Array Chunk Bytes 16 B 16 B Shape (4,) (4,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - SST_night_only_emissive_band_id(SST_night_only_emissive_band)int8dask.array<chunksize=(1,), meta=np.ndarray>
- long_name :
- ABI band identifier used to generate Sea Surface (Skin) Temperature product (night pixels only)
- standard_name :
- sensor_band_identifier
- units :
- 1
Array Chunk Bytes 1 B 1 B Shape (1,) (1,) Count 2 Tasks 1 Chunks Type int8 numpy.ndarray - SST_night_only_emissive_wavelength(SST_night_only_emissive_band)float32dask.array<chunksize=(1,), meta=np.ndarray>
- long_name :
- ABI band central emissive wavelength used to generate Sea Surface (Skin) Temperature product (night pixels only)
- standard_name :
- sensor_band_central_radiation_wavelength
- units :
- um
Array Chunk Bytes 4 B 4 B Shape (1,) (1,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - algorithm_dynamic_input_data_container(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- input_ABI_L2_auxiliary_solar_zenith_angle_data :
- null
- input_ABI_L2_auxiliary_sunglint_angle_data :
- null
- input_ABI_L2_brightness_temperature_band_14_2km_data :
- OR_ABI-L2-CMIF-M6C14_G16_s20202100000205_e20202100059513_c*.nc
- input_ABI_L2_brightness_temperature_band_15_2km_data :
- OR_ABI-L2-CMIF-M6C15_G16_s20202100000205_e20202100059513_c*.nc
- input_ABI_L2_brightness_temperature_band_7_2km_data :
- OR_ABI-L2-CMIF-M6C07_G16_s20202100000205_e20202100059513_c*.nc
- input_ABI_L2_intermediate_product_CRTM_clear_sky_brightness_temperature_band_14_data :
- null
- input_ABI_L2_intermediate_product_CRTM_clear_sky_brightness_temperature_band_15_data :
- null
- input_ABI_L2_intermediate_product_CRTM_clear_sky_brightness_temperature_band_7_data :
- null
- input_ABI_L2_intermediate_product_CRTM_skin_temperature_derivative_band_14_data :
- null
- input_ABI_L2_intermediate_product_CRTM_skin_temperature_derivative_band_15_data :
- null
- input_ABI_L2_intermediate_product_CRTM_skin_temperature_derivative_band_7_data :
- null
- input_ABI_L2_intermediate_product_CRTM_water_vapor_derivative_band_14_data :
- null
- input_ABI_L2_intermediate_product_CRTM_water_vapor_derivative_band_15_data :
- null
- input_ABI_L2_intermediate_product_CRTM_water_vapor_derivative_band_7_data :
- null
- input_ABI_L2_intermediate_product_SST_historical_bias_estimate_data :
- null
- input_ABI_L2_intermediate_product_cloud_mask_info_flag_data :
- null
- input_ABI_L2_intermediate_product_instantaneous_sea_surface_temperature_data :
- null
- input_dynamic_ancillary_Reynolds_SST_data :
- null
- input_dynamic_ancillary_Reynolds_SST_uncertainty_data :
- null
- long_name :
- container for filenames of dynamic algorithm input data
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - algorithm_product_version_container(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- algorithm_version :
- OR_ABI-L2-ALG-SST_v01r00.zip
- long_name :
- container for algorithm package filename and product version
- product_version :
- v01r00
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - day_solar_zenith_angle()float32...
- bounds :
- day_solar_zenith_angle_bounds
- long_name :
- threshold angle of the day region for the angle between the line of sight to the sun and the local zenith at the observation target
- standard_name :
- solar_zenith_angle
- units :
- degree
array(85., dtype=float32)
- day_solar_zenith_angle_bounds(time, number_of_SZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- solar zenith angle degree range for the day region
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - geospatial_lat_lon_extent(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- geospatial_eastbound_longitude :
- [6.299499988555908]
- geospatial_lat_center :
- [0.0]
- geospatial_lat_nadir :
- [0.0]
- geospatial_lat_units :
- degrees_north
- geospatial_lon_center :
- [-75.0]
- geospatial_lon_nadir :
- [-75.0]
- geospatial_lon_units :
- degrees_east
- geospatial_northbound_latitude :
- [81.32820129394531]
- geospatial_southbound_latitude :
- [-81.32820129394531]
- geospatial_westbound_longitude :
- [-156.29949951171875]
- long_name :
- geospatial latitude and longitude references
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - goes_imager_projection(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- grid_mapping_name :
- geostationary
- inverse_flattening :
- [298.2572221]
- latitude_of_projection_origin :
- [0.0]
- long_name :
- GOES-R ABI fixed grid projection
- longitude_of_projection_origin :
- [-75.0]
- perspective_point_height :
- [35786023.0]
- semi_major_axis :
- [6378137.0]
- semi_minor_axis :
- [6356752.31414]
- sweep_angle_axis :
- x
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - max_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
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- coordinates :
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- grid_mapping :
- goes_imager_projection
- long_name :
- maximum difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - max_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
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- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
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- long_name :
- maximum difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product
- units :
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Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - maximum_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
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- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- maximum sea surface temperature
- standard_name :
- sea_surface_temperature
- units :
- K
- valid_range :
- [180.0, 340.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - mean_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
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- coordinates :
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- grid_mapping :
- goes_imager_projection
- long_name :
- mean difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - mean_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
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- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- mean difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - mean_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: mean (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- mean sea surface temperature
- standard_name :
- sea_surface_temperature
- units :
- K
- valid_range :
- [180.0, 340.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - min_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
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- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle SST_night_only_emissive_band_id SST_night_only_emissive_wavelength t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- minimum difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - min_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- minimum difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - minimum_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- minimum sea surface temperature
- standard_name :
- sea_surface_temperature
- units :
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- valid_range :
- [180.0, 340.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - night_solar_zenith_angle()float32...
- bounds :
- night_solar_zenith_angle_bounds
- long_name :
- threshold angle of the night region for the angle between the line of sight to the sun and the local zenith at the observation target
- standard_name :
- solar_zenith_angle
- units :
- degree
array(95., dtype=float32)
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- long_name :
- solar zenith angle degree range for the night region
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - nominal_satellite_height(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- long_name :
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- standard_name :
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- units :
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Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - nominal_satellite_subpoint_lat(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- long_name :
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- standard_name :
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- units :
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Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - nominal_satellite_subpoint_lon(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- long_name :
- nominal satellite subpoint longitude (platform longitude)
- standard_name :
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- units :
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Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - number_of_day_SST_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
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- coordinates :
- quantitative_local_zenith_angle day_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of day sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - number_of_night_SST_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of night sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - number_of_twilight_SST_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum twilight_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_twilight_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of twilight sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - percent_uncorrectable_GRB_errors(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- t: sum area: sum (uncorrectable GRB errors only)
- coordinates :
- t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- percent data lost due to uncorrectable GRB errors
- units :
- percent
- valid_range :
- [0.0, 1.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - percent_uncorrectable_L0_errors(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- t: sum area: sum (uncorrectable L0 errors only)
- coordinates :
- t y_image x_image
- grid_mapping :
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- long_name :
- percent data lost due to uncorrectable L0 errors
- units :
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- valid_range :
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Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - processing_parm_version_container(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- L2_processing_parm_version :
- OR-PARM-SST_v01r00.zip, OR-PARM-SEMISTATIC_v01r00.zip, OR-PARM-ANCILLARY_v01r00.zip, OR-PARM-AUXILIARY_v01r00.zip, OR-PARM-TARP_v01r00.zip
- long_name :
- container for processing parameter filenames
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - quantitative_local_zenith_angle()float32...
- bounds :
- quantitative_local_zenith_angle_bounds
- long_name :
- threshold angle between the line of sight to the satellite and the local zenith at the observation target for good quality sea surface (skin) temperature data production
- standard_name :
- platform_zenith_angle
- units :
- degree
array(67., dtype=float32)
- quantitative_local_zenith_angle_bounds(time, number_of_LZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- local zenith angle degree range where good quality sea surface (skin) temperature data is produced
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - retrieval_local_zenith_angle()float32...
- bounds :
- retrieval_local_zenith_angle_bounds
- long_name :
- threshold angle between the line of sight to the satellite and the local zenith at the observation target for good or degraded quality sea surface (skin) temperature data production
- standard_name :
- platform_zenith_angle
- units :
- degree
array(90., dtype=float32)
- retrieval_local_zenith_angle_bounds(time, number_of_LZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- local zenith angle degree range where good or degraded quality sea surface (skin) temperature data is produced
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - retrieval_solar_zenith_angle()float32...
- bounds :
- retrieval_solar_zenith_angle_bounds
- long_name :
- threshold angle between the line of sight to the sun and the local zenith at the observation target for good quality sea surface (skin) temperature data production
- standard_name :
- solar_zenith_angle
- units :
- degree
array(180., dtype=float32)
- retrieval_solar_zenith_angle_bounds(time, number_of_SZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- solar zenith angle degree range where good quality sea surface (skin) temperature data is produced
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - sea_surface_temp_outlier_pixel_count(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels whose values are outside valid measurement range only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of sea surface temperature pixels whose value is outside valid measurement range
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - standard_deviation_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- standard deviation of sea surface temperature values
- standard_name :
- sea_surface_temperature
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - std_dev_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle SST_night_only_emissive_band_id SST_night_only_emissive_wavelength t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- standard deviation of the difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) values for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - std_dev_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- standard_deviation of the difference of the retrieved SST and Reynolds real-time global SST analysis values used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - time_bounds(time, number_of_time_bounds)datetime64[ns]dask.array<chunksize=(24, 2), meta=np.ndarray>
- long_name :
- Scan start and end times in seconds since epoch (2000-01-01 12:00:00)
Array Chunk Bytes 384 B 384 B Shape (24, 2) (24, 2) Count 2 Tasks 1 Chunks Type datetime64[ns] numpy.ndarray - total_number_of_degraded_quality_ocean_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: degraded quality pixels only) where sea
- coordinates :
- retrieval_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of degraded quality sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - total_number_of_good_quality_ocean_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of good quality sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - total_number_of_severely_degraded_quality_ocean_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: severely degraded quality pixels only) where sea
- coordinates :
- retrieval_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of severely degraded quality sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - total_number_of_unprocessed_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: invalid due to unprocessed pixels only)
- coordinates :
- retrieval_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of unprocessed pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - twilight_solar_zenith_angle(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- bounds :
- twilight_solar_zenith_angle_bounds
- long_name :
- midpoint of the twilight region for the angle between the line of sight to the sun and the local zenith at the observation target
- standard_name :
- solar_zenith_angle
- units :
- degree
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - twilight_solar_zenith_angle_bounds(time, number_of_SZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- solar zenith angle degree range for the twilight region
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - x_image()float32...
- axis :
- X
- long_name :
- GOES-R fixed grid projection x-coordinate center of image
- standard_name :
- projection_x_coordinate
- units :
- rad
array(0., dtype=float32)
- x_image_bounds(time, number_of_image_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- GOES-R fixed grid projection x-coordinate west/east extent of image
- units :
- rad
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - y_image()float32...
- axis :
- Y
- long_name :
- GOES-R fixed grid projection y-coordinate center of image
- standard_name :
- projection_y_coordinate
- units :
- rad
array(0., dtype=float32)
- y_image_bounds(time, number_of_image_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- GOES-R fixed grid projection y-coordinate north/south extent of image
- units :
- rad
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray
- Conventions :
- CF-1.7
- Metadata_Conventions :
- Unidata Dataset Discovery v1.0
- _FillValue :
- [-999.0]
- cdm_data_type :
- Image
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- dataset_name :
- OR_ABI-L2-SSTF-M6_G16_s20202100000205_e20202100059513_c20202100105456.nc
- date_created :
- 2020-07-28T01:05:45.6Z
- grid_mapping :
- goes_imager_projection
- id :
- 14a121c9-41b8-4552-9c28-69e6bcd4952f
- institution :
- DOC/NOAA/NESDIS > U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Services
- instrument_ID :
- FM1
- instrument_type :
- GOES R Series Advanced Baseline Imager
- iso_series_metadata_id :
- d70be540-c38a-11e0-962b-0800200c9a66
- keywords :
- OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPERATURE
- keywords_vocabulary :
- NASA Global Change Master Directory (GCMD) Earth Science Keywords, Version 7.0.0.0.0
- license :
- Unclassified data. Access is restricted to approved users only.
- long_name :
- standard deviation of the difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) values for the day and night emissive band central wavelengths used in the generation of the sea surface temperature product
- naming_authority :
- gov.nesdis.noaa
- orbital_slot :
- GOES-East
- platform_ID :
- G16
- processing_level :
- National Aeronautics and Space Administration (NASA) L2
- production_data_source :
- Realtime
- production_environment :
- OE
- production_site :
- NSOF
- project :
- GOES
- scene_id :
- Full Disk
- spatial_resolution :
- 2km at nadir
- standard_name_vocabulary :
- CF Standard Name Table (v35, 20 July 2016)
- summary :
- The ABI Sea Surface Temperature (SST) is calculated using a 4-band (8.44, 10.33, 11.19, and 12.27 um) non-linear SST (NLSST) regression equation with coefficients calculated using match-ups with in situ SSTs from drifting and tropical moored buoys. Hence on average, ABI SST is close to in situ (bulk) SST, but its spatial and temporal variations are representative of skin SST (to which ABI BTs are sensitive). One regression equation, and one set of regression coefficients are used across day and night, resulting in consistent and continuous SST diurnal cycle. Note that SST is reported over all water pixels, and only data with quality flag DQF=0 should be used to select clear-sky pixels.
- time_coverage_end :
- 2020-07-28T00:59:51.3Z
- time_coverage_start :
- 2020-07-28T00:00:20.5Z
- timeline_id :
- ABI Mode 6
- title :
- ABI L2 Sea Surface (Skin) Temperature
- units :
- K
In [6]:
%%time
subset = ds.sel(x=slice(-0.01,0.06),y=slice(0.12,0.09)) #reduce to GS region
masked = subset.SST.where(subset.DQF==0)
mean_dy = masked.mean('time',skipna=True) #here I want all possible values so skipna=True
mean_dy.plot(vmin=16+273.15,vmax=29+273.15,cmap='inferno')
CPU times: user 3.03 s, sys: 1.8 s, total: 4.83 s Wall time: 9.13 s
/srv/conda/envs/notebook/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
Out[6]:
<matplotlib.collections.QuadMesh at 0x7f5e4ce46eb0>
Again, but with Zarr file stored on S3 in same region as this jupyter hub¶
In [7]:
%%time
file_location = 's3://ohw-bucket/goes_zarr'
ikey = fsspec.get_mapper(file_location,anon=False)
ds = xr.open_zarr(ikey) #,consolidated=True)
ds
CPU times: user 791 ms, sys: 0 ns, total: 791 ms Wall time: 5.05 s
Out[7]:
<xarray.Dataset>
Dimensions: (SST_day_night_emissive_bands: 4, SST_night_only_emissive_band: 1, number_of_LZA_bounds: 2, number_of_SZA_bounds: 2, number_of_image_bounds: 2, number_of_time_bounds: 2, time: 24, x: 5424, y: 5424)
Coordinates:
* time (time) datetime64[ns] ...
* x (x) float32 -0.15...
* y (y) float32 0.151...
Dimensions without coordinates: SST_day_night_emissive_bands, SST_night_only_emissive_band, number_of_LZA_bounds, number_of_SZA_bounds, number_of_image_bounds, number_of_time_bounds
Data variables:
DQF (time, y, x) float32 dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
SST (time, y, x) float32 dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
SST_day_night_emissive_band_ids (SST_day_night_emissive_bands) int8 dask.array<chunksize=(4,), meta=np.ndarray>
SST_day_night_emissive_wavelengths (SST_day_night_emissive_bands) float32 dask.array<chunksize=(4,), meta=np.ndarray>
SST_night_only_emissive_band_id (SST_night_only_emissive_band) int8 dask.array<chunksize=(1,), meta=np.ndarray>
SST_night_only_emissive_wavelength (SST_night_only_emissive_band) float32 dask.array<chunksize=(1,), meta=np.ndarray>
algorithm_dynamic_input_data_container (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
algorithm_product_version_container (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
day_solar_zenith_angle float32 ...
day_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
geospatial_lat_lon_extent (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
goes_imager_projection (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
max_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
max_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
maximum_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
mean_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
mean_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
mean_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
min_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
min_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
minimum_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
night_solar_zenith_angle float32 ...
night_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
nominal_satellite_height (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
nominal_satellite_subpoint_lat (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
nominal_satellite_subpoint_lon (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
number_of_day_SST_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
number_of_night_SST_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
number_of_twilight_SST_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
percent_uncorrectable_GRB_errors (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
percent_uncorrectable_L0_errors (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
processing_parm_version_container (time) int32 dask.array<chunksize=(24,), meta=np.ndarray>
quantitative_local_zenith_angle float32 ...
quantitative_local_zenith_angle_bounds (time, number_of_LZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
retrieval_local_zenith_angle float32 ...
retrieval_local_zenith_angle_bounds (time, number_of_LZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
retrieval_solar_zenith_angle float32 ...
retrieval_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
sea_surface_temp_outlier_pixel_count (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
standard_deviation_sea_surface_temp (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
std_dev_obs_modeled_diff_SST_night_only_emissive_band (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
std_dev_retrieved_Reynolds_SST_diff (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
time_bounds (time, number_of_time_bounds) datetime64[ns] dask.array<chunksize=(24, 2), meta=np.ndarray>
total_number_of_degraded_quality_ocean_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
total_number_of_good_quality_ocean_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
total_number_of_severely_degraded_quality_ocean_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
total_number_of_unprocessed_pixels (time) float64 dask.array<chunksize=(24,), meta=np.ndarray>
twilight_solar_zenith_angle (time) float32 dask.array<chunksize=(24,), meta=np.ndarray>
twilight_solar_zenith_angle_bounds (time, number_of_SZA_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
x_image float32 ...
x_image_bounds (time, number_of_image_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
y_image float32 ...
y_image_bounds (time, number_of_image_bounds) float32 dask.array<chunksize=(1, 2), meta=np.ndarray>
Attributes:
Conventions: CF-1.7
Metadata_Conventions: Unidata Dataset Discovery v1.0
_FillValue: [-999.0]
cdm_data_type: Image
cell_methods: quantitative_local_zenith_angle: sum retrieval...
dataset_name: OR_ABI-L2-SSTF-M6_G16_s20202100000205_e2020210...
date_created: 2020-07-28T01:05:45.6Z
grid_mapping: goes_imager_projection
id: 14a121c9-41b8-4552-9c28-69e6bcd4952f
institution: DOC/NOAA/NESDIS > U.S. Department of Commerce,...
instrument_ID: FM1
instrument_type: GOES R Series Advanced Baseline Imager
iso_series_metadata_id: d70be540-c38a-11e0-962b-0800200c9a66
keywords: OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPE...
keywords_vocabulary: NASA Global Change Master Directory (GCMD) Ear...
license: Unclassified data. Access is restricted to ap...
long_name: standard deviation of the difference of the ob...
naming_authority: gov.nesdis.noaa
orbital_slot: GOES-East
platform_ID: G16
processing_level: National Aeronautics and Space Administration ...
production_data_source: Realtime
production_environment: OE
production_site: NSOF
project: GOES
scene_id: Full Disk
spatial_resolution: 2km at nadir
standard_name_vocabulary: CF Standard Name Table (v35, 20 July 2016)
summary: The ABI Sea Surface Temperature (SST) is calcu...
time_coverage_end: 2020-07-28T00:59:51.3Z
time_coverage_start: 2020-07-28T00:00:20.5Z
timeline_id: ABI Mode 6
title: ABI L2 Sea Surface (Skin) Temperature
units: Kxarray.Dataset
- SST_day_night_emissive_bands: 4
- SST_night_only_emissive_band: 1
- number_of_LZA_bounds: 2
- number_of_SZA_bounds: 2
- number_of_image_bounds: 2
- number_of_time_bounds: 2
- time: 24
- x: 5424
- y: 5424
- time(time)datetime64[ns]2020-07-28T00:30:05.934142976 .....
- axis :
- T
- bounds :
- time_bounds
- long_name :
- J2000 epoch mid-point between the start and end image scan in seconds
- standard_name :
- time
array(['2020-07-28T00:30:05.934142976', '2020-07-28T01:30:05.901723008', '2020-07-28T02:30:05.864743936', '2020-07-28T03:30:05.828807936', '2020-07-28T04:30:05.789944960', '2020-07-28T05:30:05.866763904', '2020-07-28T06:30:05.943120000', '2020-07-28T07:30:05.902876032', '2020-07-28T08:30:05.866008960', '2020-07-28T09:30:05.823889024', '2020-07-28T10:30:05.785832960', '2020-07-28T11:30:05.747997056', '2020-07-28T12:30:05.725508992', '2020-07-28T13:30:05.716819072', '2020-07-28T14:30:05.711737088', '2020-07-28T15:30:05.688460928', '2020-07-28T16:30:05.651743104', '2020-07-28T17:30:05.499197056', '2020-07-28T18:30:05.346963968', '2020-07-28T19:30:05.309723008', '2020-07-28T20:30:05.273282944', '2020-07-28T21:30:05.235561984', '2020-07-28T22:30:05.200251008', '2020-07-28T23:30:05.159278080'], dtype='datetime64[ns]') - x(x)float32-0.151844 -0.151788 ... 0.151844
- axis :
- X
- long_name :
- GOES fixed grid projection x-coordinate
- standard_name :
- projection_x_coordinate
- units :
- rad
array([-0.151844, -0.151788, -0.151732, ..., 0.151732, 0.151788, 0.151844], dtype=float32) - y(y)float320.151844 0.151788 ... -0.151844
- axis :
- Y
- long_name :
- GOES fixed grid projection y-coordinate
- standard_name :
- projection_y_coordinate
- units :
- rad
array([ 0.151844, 0.151788, 0.151732, ..., -0.151732, -0.151788, -0.151844], dtype=float32)
- DQF(time, y, x)float32dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: point quantitative_local_zenith_angle: point retrieval_solar_zenith_angle: point t: point area: point
- coordinates :
- retrieval_local_zenith_angle quantitative_local_zenith_angle retrieval_solar_zenith_angle t y x
- flag_meanings :
- good_quality_qf degraded_quality_qf severely_degraded_quality_qf invalid_due_to_unprocessed_qf
- flag_values :
- [0, 1, 2, 3]
- grid_mapping :
- goes_imager_projection
- long_name :
- ABI L2+ Sea Surface (Skin) Temperature data quality flags
- number_of_qf_values :
- [4]
- percent_degraded_quality_qf :
- [0.02484860084950924]
- percent_good_quality_qf :
- [0.1703146994113922]
- percent_invalid_due_to_unprocessed_qf :
- [0.5447992086410522]
- percent_severely_degraded_quality_qf :
- [0.5365844964981079]
- standard_name :
- status_flag
- units :
- 1
- valid_range :
- [0, 3]
Array Chunk Bytes 2.82 GB 117.68 MB Shape (24, 5424, 5424) (1, 5424, 5424) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - SST(time, y, x)float32dask.array<chunksize=(1, 5424, 5424), meta=np.ndarray>
- algorithm_type :
- regression
- ancillary_variables :
- DQF
- cell_methods :
- retrieval_local_zenith_angle: point (good or degraded quality pixel produced) quantitative_local_zenith_angle: point (good quality pixel produced) retrieval_solar_zenith_angle: point (good quality pixel produced) t: point area: point
- coordinates :
- retrieval_local_zenith_angle quantitative_local_zenith_angle retrieval_solar_zenith_angle t y x
- grid_mapping :
- goes_imager_projection
- long_name :
- ABI L2+ Sea Surface (Skin) Temperature
- resolution :
- y: 0.000056 rad x: 0.000056 rad
- standard_name :
- sea_surface_skin_temperature
- units :
- K
- valid_range :
- [0, -6]
Array Chunk Bytes 2.82 GB 117.68 MB Shape (24, 5424, 5424) (1, 5424, 5424) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - SST_day_night_emissive_band_ids(SST_day_night_emissive_bands)int8dask.array<chunksize=(4,), meta=np.ndarray>
- long_name :
- ABI band identifiers used to generate Sea Surface (Skin) Temperature product (day and night pixels)
- standard_name :
- sensor_band_identifier
- units :
- 1
Array Chunk Bytes 4 B 4 B Shape (4,) (4,) Count 2 Tasks 1 Chunks Type int8 numpy.ndarray - SST_day_night_emissive_wavelengths(SST_day_night_emissive_bands)float32dask.array<chunksize=(4,), meta=np.ndarray>
- long_name :
- ABI band central emissive wavelengths used to generate Sea Surface (Skin) Temperature product (day and night pixels)
- standard_name :
- sensor_band_central_radiation_wavelength
- units :
- um
Array Chunk Bytes 16 B 16 B Shape (4,) (4,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - SST_night_only_emissive_band_id(SST_night_only_emissive_band)int8dask.array<chunksize=(1,), meta=np.ndarray>
- long_name :
- ABI band identifier used to generate Sea Surface (Skin) Temperature product (night pixels only)
- standard_name :
- sensor_band_identifier
- units :
- 1
Array Chunk Bytes 1 B 1 B Shape (1,) (1,) Count 2 Tasks 1 Chunks Type int8 numpy.ndarray - SST_night_only_emissive_wavelength(SST_night_only_emissive_band)float32dask.array<chunksize=(1,), meta=np.ndarray>
- long_name :
- ABI band central emissive wavelength used to generate Sea Surface (Skin) Temperature product (night pixels only)
- standard_name :
- sensor_band_central_radiation_wavelength
- units :
- um
Array Chunk Bytes 4 B 4 B Shape (1,) (1,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - algorithm_dynamic_input_data_container(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- input_ABI_L2_auxiliary_solar_zenith_angle_data :
- null
- input_ABI_L2_auxiliary_sunglint_angle_data :
- null
- input_ABI_L2_brightness_temperature_band_14_2km_data :
- OR_ABI-L2-CMIF-M6C14_G16_s20202100000205_e20202100059513_c*.nc
- input_ABI_L2_brightness_temperature_band_15_2km_data :
- OR_ABI-L2-CMIF-M6C15_G16_s20202100000205_e20202100059513_c*.nc
- input_ABI_L2_brightness_temperature_band_7_2km_data :
- OR_ABI-L2-CMIF-M6C07_G16_s20202100000205_e20202100059513_c*.nc
- input_ABI_L2_intermediate_product_CRTM_clear_sky_brightness_temperature_band_14_data :
- null
- input_ABI_L2_intermediate_product_CRTM_clear_sky_brightness_temperature_band_15_data :
- null
- input_ABI_L2_intermediate_product_CRTM_clear_sky_brightness_temperature_band_7_data :
- null
- input_ABI_L2_intermediate_product_CRTM_skin_temperature_derivative_band_14_data :
- null
- input_ABI_L2_intermediate_product_CRTM_skin_temperature_derivative_band_15_data :
- null
- input_ABI_L2_intermediate_product_CRTM_skin_temperature_derivative_band_7_data :
- null
- input_ABI_L2_intermediate_product_CRTM_water_vapor_derivative_band_14_data :
- null
- input_ABI_L2_intermediate_product_CRTM_water_vapor_derivative_band_15_data :
- null
- input_ABI_L2_intermediate_product_CRTM_water_vapor_derivative_band_7_data :
- null
- input_ABI_L2_intermediate_product_SST_historical_bias_estimate_data :
- null
- input_ABI_L2_intermediate_product_cloud_mask_info_flag_data :
- null
- input_ABI_L2_intermediate_product_instantaneous_sea_surface_temperature_data :
- null
- input_dynamic_ancillary_Reynolds_SST_data :
- null
- input_dynamic_ancillary_Reynolds_SST_uncertainty_data :
- null
- long_name :
- container for filenames of dynamic algorithm input data
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - algorithm_product_version_container(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- algorithm_version :
- OR_ABI-L2-ALG-SST_v01r00.zip
- long_name :
- container for algorithm package filename and product version
- product_version :
- v01r00
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - day_solar_zenith_angle()float32...
- bounds :
- day_solar_zenith_angle_bounds
- long_name :
- threshold angle of the day region for the angle between the line of sight to the sun and the local zenith at the observation target
- standard_name :
- solar_zenith_angle
- units :
- degree
array(85., dtype=float32)
- day_solar_zenith_angle_bounds(time, number_of_SZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- solar zenith angle degree range for the day region
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - geospatial_lat_lon_extent(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- geospatial_eastbound_longitude :
- [6.299499988555908]
- geospatial_lat_center :
- [0.0]
- geospatial_lat_nadir :
- [0.0]
- geospatial_lat_units :
- degrees_north
- geospatial_lon_center :
- [-75.0]
- geospatial_lon_nadir :
- [-75.0]
- geospatial_lon_units :
- degrees_east
- geospatial_northbound_latitude :
- [81.32820129394531]
- geospatial_southbound_latitude :
- [-81.32820129394531]
- geospatial_westbound_longitude :
- [-156.29949951171875]
- long_name :
- geospatial latitude and longitude references
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - goes_imager_projection(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- grid_mapping_name :
- geostationary
- inverse_flattening :
- [298.2572221]
- latitude_of_projection_origin :
- [0.0]
- long_name :
- GOES-R ABI fixed grid projection
- longitude_of_projection_origin :
- [-75.0]
- perspective_point_height :
- [35786023.0]
- semi_major_axis :
- [6378137.0]
- semi_minor_axis :
- [6356752.31414]
- sweep_angle_axis :
- x
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - max_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: maximum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle SST_night_only_emissive_band_id SST_night_only_emissive_wavelength t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- maximum difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - max_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: maximum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- maximum difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - maximum_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: maximum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- maximum sea surface temperature
- standard_name :
- sea_surface_temperature
- units :
- K
- valid_range :
- [180.0, 340.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - mean_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: mean (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle SST_night_only_emissive_band_id SST_night_only_emissive_wavelength t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- mean difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - mean_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: mean (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- mean difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - mean_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: mean (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- mean sea surface temperature
- standard_name :
- sea_surface_temperature
- units :
- K
- valid_range :
- [180.0, 340.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - min_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle SST_night_only_emissive_band_id SST_night_only_emissive_wavelength t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- minimum difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - min_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- minimum difference of the retrieved SST and Reynolds real-time global SST analysis used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - minimum_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: minimum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- minimum sea surface temperature
- standard_name :
- sea_surface_temperature
- units :
- K
- valid_range :
- [180.0, 340.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - night_solar_zenith_angle()float32...
- bounds :
- night_solar_zenith_angle_bounds
- long_name :
- threshold angle of the night region for the angle between the line of sight to the sun and the local zenith at the observation target
- standard_name :
- solar_zenith_angle
- units :
- degree
array(95., dtype=float32)
- night_solar_zenith_angle_bounds(time, number_of_SZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- solar zenith angle degree range for the night region
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - nominal_satellite_height(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- long_name :
- nominal satellite height above GRS 80 ellipsoid (platform altitude)
- standard_name :
- height_above_reference_ellipsoid
- units :
- km
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - nominal_satellite_subpoint_lat(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- long_name :
- nominal satellite subpoint latitude (platform latitude)
- standard_name :
- latitude
- units :
- degrees_north
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - nominal_satellite_subpoint_lon(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- long_name :
- nominal satellite subpoint longitude (platform longitude)
- standard_name :
- longitude
- units :
- degrees_east
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - number_of_day_SST_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum day_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle day_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of day sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - number_of_night_SST_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of night sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - number_of_twilight_SST_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum twilight_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_twilight_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of twilight sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - percent_uncorrectable_GRB_errors(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- t: sum area: sum (uncorrectable GRB errors only)
- coordinates :
- t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- percent data lost due to uncorrectable GRB errors
- units :
- percent
- valid_range :
- [0.0, 1.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - percent_uncorrectable_L0_errors(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- t: sum area: sum (uncorrectable L0 errors only)
- coordinates :
- t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- percent data lost due to uncorrectable L0 errors
- units :
- percent
- valid_range :
- [0.0, 1.0]
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - processing_parm_version_container(time)int32dask.array<chunksize=(24,), meta=np.ndarray>
- L2_processing_parm_version :
- OR-PARM-SST_v01r00.zip, OR-PARM-SEMISTATIC_v01r00.zip, OR-PARM-ANCILLARY_v01r00.zip, OR-PARM-AUXILIARY_v01r00.zip, OR-PARM-TARP_v01r00.zip
- long_name :
- container for processing parameter filenames
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type int32 numpy.ndarray - quantitative_local_zenith_angle()float32...
- bounds :
- quantitative_local_zenith_angle_bounds
- long_name :
- threshold angle between the line of sight to the satellite and the local zenith at the observation target for good quality sea surface (skin) temperature data production
- standard_name :
- platform_zenith_angle
- units :
- degree
array(67., dtype=float32)
- quantitative_local_zenith_angle_bounds(time, number_of_LZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- local zenith angle degree range where good quality sea surface (skin) temperature data is produced
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - retrieval_local_zenith_angle()float32...
- bounds :
- retrieval_local_zenith_angle_bounds
- long_name :
- threshold angle between the line of sight to the satellite and the local zenith at the observation target for good or degraded quality sea surface (skin) temperature data production
- standard_name :
- platform_zenith_angle
- units :
- degree
array(90., dtype=float32)
- retrieval_local_zenith_angle_bounds(time, number_of_LZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- local zenith angle degree range where good or degraded quality sea surface (skin) temperature data is produced
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - retrieval_solar_zenith_angle()float32...
- bounds :
- retrieval_solar_zenith_angle_bounds
- long_name :
- threshold angle between the line of sight to the sun and the local zenith at the observation target for good quality sea surface (skin) temperature data production
- standard_name :
- solar_zenith_angle
- units :
- degree
array(180., dtype=float32)
- retrieval_solar_zenith_angle_bounds(time, number_of_SZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- solar zenith angle degree range where good quality sea surface (skin) temperature data is produced
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - sea_surface_temp_outlier_pixel_count(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels whose values are outside valid measurement range only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of sea surface temperature pixels whose value is outside valid measurement range
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - standard_deviation_sea_surface_temp(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- standard deviation of sea surface temperature values
- standard_name :
- sea_surface_temperature
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - std_dev_obs_modeled_diff_SST_night_only_emissive_band(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum night_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle night_solar_zenith_angle SST_night_only_emissive_band_id SST_night_only_emissive_wavelength t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- standard deviation of the difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) values for the night only emissive band central wavelength used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - std_dev_retrieved_Reynolds_SST_diff(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- standard_deviation of the difference of the retrieved SST and Reynolds real-time global SST analysis values used in the generation of the sea surface temperature product
- units :
- K
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - time_bounds(time, number_of_time_bounds)datetime64[ns]dask.array<chunksize=(24, 2), meta=np.ndarray>
- long_name :
- Scan start and end times in seconds since epoch (2000-01-01 12:00:00)
Array Chunk Bytes 384 B 384 B Shape (24, 2) (24, 2) Count 2 Tasks 1 Chunks Type datetime64[ns] numpy.ndarray - total_number_of_degraded_quality_ocean_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: degraded quality pixels only) where sea
- coordinates :
- retrieval_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of degraded quality sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - total_number_of_good_quality_ocean_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: good quality pixels only) where sea
- coordinates :
- quantitative_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of good quality sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - total_number_of_severely_degraded_quality_ocean_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: severely degraded quality pixels only) where sea
- coordinates :
- retrieval_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of severely degraded quality sea surface temperature pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - total_number_of_unprocessed_pixels(time)float64dask.array<chunksize=(24,), meta=np.ndarray>
- cell_methods :
- retrieval_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: sum (interval: 0.000056 rad comment: invalid due to unprocessed pixels only)
- coordinates :
- retrieval_local_zenith_angle retrieval_solar_zenith_angle t y_image x_image
- grid_mapping :
- goes_imager_projection
- long_name :
- number of unprocessed pixels
- units :
- count
Array Chunk Bytes 192 B 192 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float64 numpy.ndarray - twilight_solar_zenith_angle(time)float32dask.array<chunksize=(24,), meta=np.ndarray>
- bounds :
- twilight_solar_zenith_angle_bounds
- long_name :
- midpoint of the twilight region for the angle between the line of sight to the sun and the local zenith at the observation target
- standard_name :
- solar_zenith_angle
- units :
- degree
Array Chunk Bytes 96 B 96 B Shape (24,) (24,) Count 2 Tasks 1 Chunks Type float32 numpy.ndarray - twilight_solar_zenith_angle_bounds(time, number_of_SZA_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- solar zenith angle degree range for the twilight region
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - x_image()float32...
- axis :
- X
- long_name :
- GOES-R fixed grid projection x-coordinate center of image
- standard_name :
- projection_x_coordinate
- units :
- rad
array(0., dtype=float32)
- x_image_bounds(time, number_of_image_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- GOES-R fixed grid projection x-coordinate west/east extent of image
- units :
- rad
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray - y_image()float32...
- axis :
- Y
- long_name :
- GOES-R fixed grid projection y-coordinate center of image
- standard_name :
- projection_y_coordinate
- units :
- rad
array(0., dtype=float32)
- y_image_bounds(time, number_of_image_bounds)float32dask.array<chunksize=(1, 2), meta=np.ndarray>
- long_name :
- GOES-R fixed grid projection y-coordinate north/south extent of image
- units :
- rad
Array Chunk Bytes 192 B 8 B Shape (24, 2) (1, 2) Count 25 Tasks 24 Chunks Type float32 numpy.ndarray
- Conventions :
- CF-1.7
- Metadata_Conventions :
- Unidata Dataset Discovery v1.0
- _FillValue :
- [-999.0]
- cdm_data_type :
- Image
- cell_methods :
- quantitative_local_zenith_angle: sum retrieval_solar_zenith_angle: sum t: sum area: standard_deviation (interval: 0.000056 rad comment: good quality pixels only) where sea
- dataset_name :
- OR_ABI-L2-SSTF-M6_G16_s20202100000205_e20202100059513_c20202100105456.nc
- date_created :
- 2020-07-28T01:05:45.6Z
- grid_mapping :
- goes_imager_projection
- id :
- 14a121c9-41b8-4552-9c28-69e6bcd4952f
- institution :
- DOC/NOAA/NESDIS > U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Services
- instrument_ID :
- FM1
- instrument_type :
- GOES R Series Advanced Baseline Imager
- iso_series_metadata_id :
- d70be540-c38a-11e0-962b-0800200c9a66
- keywords :
- OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPERATURE
- keywords_vocabulary :
- NASA Global Change Master Directory (GCMD) Earth Science Keywords, Version 7.0.0.0.0
- license :
- Unclassified data. Access is restricted to approved users only.
- long_name :
- standard deviation of the difference of the observed and modeled brightness temperature (Joint Center for Satellite Data Assimilation Community Radiative Transfer Model using temporally interpolated NWP data as input) values for the day and night emissive band central wavelengths used in the generation of the sea surface temperature product
- naming_authority :
- gov.nesdis.noaa
- orbital_slot :
- GOES-East
- platform_ID :
- G16
- processing_level :
- National Aeronautics and Space Administration (NASA) L2
- production_data_source :
- Realtime
- production_environment :
- OE
- production_site :
- NSOF
- project :
- GOES
- scene_id :
- Full Disk
- spatial_resolution :
- 2km at nadir
- standard_name_vocabulary :
- CF Standard Name Table (v35, 20 July 2016)
- summary :
- The ABI Sea Surface Temperature (SST) is calculated using a 4-band (8.44, 10.33, 11.19, and 12.27 um) non-linear SST (NLSST) regression equation with coefficients calculated using match-ups with in situ SSTs from drifting and tropical moored buoys. Hence on average, ABI SST is close to in situ (bulk) SST, but its spatial and temporal variations are representative of skin SST (to which ABI BTs are sensitive). One regression equation, and one set of regression coefficients are used across day and night, resulting in consistent and continuous SST diurnal cycle. Note that SST is reported over all water pixels, and only data with quality flag DQF=0 should be used to select clear-sky pixels.
- time_coverage_end :
- 2020-07-28T00:59:51.3Z
- time_coverage_start :
- 2020-07-28T00:00:20.5Z
- timeline_id :
- ABI Mode 6
- title :
- ABI L2 Sea Surface (Skin) Temperature
- units :
- K
In [8]:
%%time
subset = ds.sel(x=slice(-0.01,0.06),y=slice(0.12,0.09)) #reduce to GS region
masked = subset.SST.where(subset.DQF==0)
mean_dy = masked.mean('time',skipna=True) #here I want all possible values so skipna=True
mean_dy.plot(vmin=16+273.15,vmax=29+273.15,cmap='inferno')
CPU times: user 3.17 s, sys: 2.19 s, total: 5.36 s Wall time: 6.59 s
/srv/conda/envs/notebook/lib/python3.8/site-packages/dask/array/numpy_compat.py:40: RuntimeWarning: invalid value encountered in true_divide x = np.divide(x1, x2, out)
Out[8]:
<matplotlib.collections.QuadMesh at 0x7f5e44570d90>
Summarize Results reading GOES data on the cloud¶
- Code run from Jupyter Hub on us-west-2
- Compare results reading netcdf and zarr files both stored on us-east-1
- Compare results reading zarr stored next to hub, both on us-west-2
| Format | Region | Access-time (sec) | Analysis-time (sec) | Total effort (%) |
|---|---|---|---|---|
| NetCDF | different | 165 | 1159 | 100 |
| Zarr | different | 24 | 9 | 2.5 |
| Zarr | same | 5 | 7 | 0.1 |
In [ ]: