Feedstock: noaa-coastwatch-geopolar-sst

lat
(lat)
float32
-89.97 -89.93 ... 89.93 89.97
axis :
Y
comment :
equirectangular projection
long_name :
latitude
standard_name :
latitude
units :
degrees_north
valid_max :
90.0
valid_min :
-90.0
```
array([-89.975, -89.925, -89.875, ...,  89.875,  89.925,  89.975],
      dtype=float32)
```
lon
(lon)
float32
-180.0 -179.9 ... 179.9 180.0
axis :
X
comment :
equirectangular projection
long_name :
longitude
standard_name :
longitude
units :
degrees_east
valid_max :
180.0
valid_min :
-180.0
```
array([-179.975, -179.925, -179.875, ...,  179.875,  179.925,  179.975],
      dtype=float32)
```

time

(time)

datetime64[ns]

2002-09-01T12:00:00 ... 2022-03-...

axis :: T
comment :: Nominal time of Level 4 analysis
long_name :: reference time of sst field
standard_name :: time

array(['2002-09-01T12:00:00.000000000', '2002-09-02T12:00:00.000000000',
       '2002-09-03T12:00:00.000000000', ..., '2022-03-18T12:00:00.000000000',
       '2022-03-19T12:00:00.000000000', '2022-03-20T12:00:00.000000000'],
      dtype='datetime64[ns]')

analysed_sst

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: Analysed SST for each ocean grid point
long_name :: analysed sea surface temperature
reference :: Fieguth,P.W. et al. "Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm", J. Atmos. Ocean Tech, 15 (2): 535-546, 1998. Fieguth, P. Multiply-Rooted Multiscale Models for Large-Scale Estimation, IEEE Image Processing, 10(11), 1676-1686, 2001. Khellah, F., P.W. Fieguth, M.J. Murray and M.R. Allen, "Statistical Processing of Large Image Sequences", IEEE Transactions on Geoscience and Remote Sensing, 12 (1), 80-93, 2005. Maturi, E., A. Harris, J. Mittaz, J. Sapper, G. Wick, X. Zhu, P. Dash, P. Koner, "A New High-Resolution Sea Surface Temperature Blended Analysis", Bulleting of the American Meteorological Society, 98 (5), 1015-1026, 2017.
source :: STAR-ACSPO_GAC, STAR-ACSPO_H-8, STAR-Geo_SST, UKMO-OSTIA
standard_name :: sea_surface_foundation_temperature
units :: kelvin
valid_max :: 4000
valid_min :: -200

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

analysis_error

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: Estimate of internal analysis accuracy
long_name :: estimated error standard deviation of analysed_sst
units :: kelvin
valid_max :: 500
valid_min :: 0

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

mask

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: b0: 1=grid cell is water, b1: 1=grid cell is land, b2: 1=grid cell is ice
flag_meanings :: water land ice
flag_values :: [1, 2, 4]
long_name :: sea/land/ice bit mask
source :: OSTIA reanalysis land mask
standard_name :: sea_land_ice_bit_mask
valid_max :: 4
valid_min :: 1

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

sea_ice_fraction

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: Percentage of ice
long_name :: sea ice fraction
source :: OSTIA reanalysis ice mask
standard_name :: sea_ice_area_fraction
units :: 1
valid_max :: 100
valid_min :: 0

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

lat

PandasIndex

PandasIndex(Index([ -89.9749984741211, -89.92500305175781,            -89.875,
       -89.82499694824219,  -89.7750015258789,  -89.7249984741211,
       -89.67500305175781,            -89.625, -89.57499694824219,
        -89.5250015258789,
       ...
         89.5250015258789,  89.57499694824219,             89.625,
        89.67500305175781,   89.7249984741211,   89.7750015258789,
        89.82499694824219,             89.875,  89.92500305175781,
         89.9749984741211],
      dtype='float32', name='lat', length=3600))

lon

PandasIndex

PandasIndex(Index([-179.97500610351562,  -179.9250030517578,            -179.875,
        -179.8249969482422, -179.77499389648438, -179.72500610351562,
        -179.6750030517578,            -179.625,  -179.5749969482422,
       -179.52499389648438,
       ...
        179.52499389648438,   179.5749969482422,             179.625,
         179.6750030517578,  179.72500610351562,  179.77499389648438,
         179.8249969482422,             179.875,   179.9250030517578,
        179.97500610351562],
      dtype='float32', name='lon', length=7200))

time

PandasIndex

PandasIndex(DatetimeIndex(['2002-09-01 12:00:00', '2002-09-02 12:00:00',
               '2002-09-03 12:00:00', '2002-09-04 12:00:00',
               '2002-09-05 12:00:00', '2002-09-06 12:00:00',
               '2002-09-07 12:00:00', '2002-09-08 12:00:00',
               '2002-09-09 12:00:00', '2002-09-10 12:00:00',
               ...
               '2022-03-11 12:00:00', '2022-03-12 12:00:00',
               '2022-03-13 12:00:00', '2022-03-14 12:00:00',
               '2022-03-15 12:00:00', '2022-03-16 12:00:00',
               '2022-03-17 12:00:00', '2022-03-18 12:00:00',
               '2022-03-19 12:00:00', '2022-03-20 12:00:00'],
              dtype='datetime64[ns]', name='time', length=7134, freq=None))

Conventions :: CF-1.4, Unidata Observation Dataset v1.0
Metadata_Conventions :: Unidata Observation Dataset v1.0
acknowledgment :: NOAA/NESDIS
cdm_data_type :: grid
comment :: The Geo-Polar Blended Sea Surface Temperature (SST) Analysis combines multi-satellite retrievals of sea surface temperature into a single analysis of SST
creator_email :: andy.harris@noaa.gov
creator_name :: Satellite Applications and Research
creator_url :: www.star.nesdis.noaa.gov
date_created :: 20170622T163825Z
easternmost_longitude :: 180.0
file_quality_level :: 0.0
gds_version_id :: 2.0
geospatial_lat_resolution :: 0.05
geospatial_lat_units :: degrees north
geospatial_lon_resolution :: 0.05
geospatial_lon_units :: degrees east
history :: Fri Oct 19 11:12:34 2018: ncatted -a add_offset,analysis_error,o,f,0. 20020901000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.nc Fri Oct 19 11:09:25 2018: ncatted -a add_offset,analysed_sst,o,f,273.15 20020901000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.nc NESDIS geo-SST L1 to L2 processor, NESDIS Advanced Clear-Sky Processor for Oceans (ACSPO), NESDIS Geo-Polar 1/20th degree Blended SST Analysis
id :: Geo_Polar_Blended_Night-STAR-L4-GLOB-v1.0
institution :: Office of Satellite Products and Operations
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
metadata_link :: http://podaac.jpl.nasa.gov:8890/ws/metadata/dataset?format=iso&shortName=Geo_Polar_Blended_Night-STAR-L4-GLOB-v1.0
naming_authority :: org.ghrsst
netcdf_version_id :: 4.1.3
northernmost_latitude :: 90.0
platform :: NOAA-16, NOAA-17, NOAA-18, NOAA-19, MetOpA, Himawari-8, GOES10, GOES11, GOES12, GOES13, GOES15, MTSAT1R, MTSAT2
processing_level :: L4
product_version :: 1.0
project :: Group for High Resolution Sea Surface Temperature
publisher_email :: ghrsst-po@nceo.ac.uk
publisher_name :: The GHRSST Project Office
publisher_url :: http://www.ghrsst.org
references :: Fieguth,P.W. et al. "Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm", J. Atmos. Ocean Tech, 15 (2): 535-546, 1998. Fieguth, P. Multiply-Rooted Multiscale Models for Large-Scale Estimation, IEEE Image Processing, 10(11), 1676-1686, 2001. Khellah, F., P.W. Fieguth, M.J. Murray and M.R. Allen, "Statistical Processing of Large Image Sequences", IEEE Transactions on Geoscience and Remote Sensing, 12 (1), 80-93, 2005. Maturi, E., A. Harris, J. Mittaz, J. Sapper, G. Wick, X. Zhu, P. Dash, P. Koner, "A New High-Resolution Sea Surface Temperature Blended Analysis", Bulleting of the American Meteorological Society, 98 (5), 1015-1026, 2017.
sensor :: AVHRR_GAC, AHI, GOES_Imager, JAMI
source :: STAR-ACSPO_GAC, STAR-ACSPO_H-8, STAR-Geo_SST, UKMO-OSTIA
southernmost_latitude :: -90.0
spatial_resolution :: 0.05 degree
standard_name_vocabulary :: NetCDF Climate and Forecast (CF) Metadata Convetion
start_time :: 20020901T000000Z
stop_time :: 20020902T000000Z
summary :: An SST estimation scheme which combines multi-satellite retrievals of sea surface temperature datasets available from polar orbiters, geostationary IR and microwave sensors into a single global analysis. This global SST ananlysis provide a daily gap free map of the foundation sea surface temperature at 0.05o spatial resolution.
time_coverage_end :: 20020902T000000Z
time_coverage_start :: 20020901T000000Z
title :: Analysed blended sea surface temperature over the global ocean
uuid :: 7c4fc02a-1034-4021-be6f-c3ce858fd33a
westernmost_longitude :: -180.0

lat
(lat)
float32
-89.97 -89.93 ... 89.93 89.97
axis :
Y
comment :
equirectangular projection
long_name :
latitude
standard_name :
latitude
units :
degrees_north
valid_max :
90.0
valid_min :
-90.0
```
array([-89.975, -89.925, -89.875, ...,  89.875,  89.925,  89.975],
      dtype=float32)
```
lon
(lon)
float32
-180.0 -179.9 ... 179.9 180.0
axis :
X
comment :
equirectangular projection
long_name :
longitude
standard_name :
longitude
units :
degrees_east
valid_max :
180.0
valid_min :
-180.0
```
array([-179.975, -179.925, -179.875, ...,  179.875,  179.925,  179.975],
      dtype=float32)
```

time

(time)

datetime64[ns]

2002-09-01T12:00:00 ... 2022-03-...

axis :: T
comment :: Nominal time of Level 4 analysis
long_name :: reference time of sst field
standard_name :: time

array(['2002-09-01T12:00:00.000000000', '2002-09-02T12:00:00.000000000',
       '2002-09-03T12:00:00.000000000', ..., '2022-03-18T12:00:00.000000000',
       '2022-03-19T12:00:00.000000000', '2022-03-20T12:00:00.000000000'],
      dtype='datetime64[ns]')

analysed_sst

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: Analysed SST for each ocean grid point
long_name :: analysed sea surface temperature
reference :: Fieguth,P.W. et al. "Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm", J. Atmos. Ocean Tech, 15 (2): 535-546, 1998. Fieguth, P. Multiply-Rooted Multiscale Models for Large-Scale Estimation, IEEE Image Processing, 10(11), 1676-1686, 2001. Khellah, F., P.W. Fieguth, M.J. Murray and M.R. Allen, "Statistical Processing of Large Image Sequences", IEEE Transactions on Geoscience and Remote Sensing, 12 (1), 80-93, 2005. Maturi, E., A. Harris, J. Mittaz, J. Sapper, G. Wick, X. Zhu, P. Dash, P. Koner, "A New High-Resolution Sea Surface Temperature Blended Analysis", Bulleting of the American Meteorological Society, 98 (5), 1015-1026, 2017.
source :: STAR-ACSPO_GAC, STAR-ACSPO_H-8, STAR-Geo_SST, UKMO-OSTIA
standard_name :: sea_surface_foundation_temperature
units :: kelvin
valid_max :: 4000
valid_min :: -200

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

analysis_error

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: Estimate of internal analysis accuracy
long_name :: estimated error standard deviation of analysed_sst
units :: kelvin
valid_max :: 500
valid_min :: 0

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

mask

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: b0: 1=grid cell is water, b1: 1=grid cell is land, b2: 1=grid cell is ice
flag_meanings :: water land ice
flag_values :: [1, 2, 4]
long_name :: sea/land/ice bit mask
source :: OSTIA reanalysis land mask
standard_name :: sea_land_ice_bit_mask
valid_max :: 4
valid_min :: 1

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

sea_ice_fraction

(time, lat, lon)

float32

dask.array<chunksize=(2, 1800, 7200), meta=np.ndarray>

comment :: Percentage of ice
long_name :: sea ice fraction
source :: OSTIA reanalysis ice mask
standard_name :: sea_ice_area_fraction
units :: 1
valid_max :: 100
valid_min :: 0

	Array	Chunk
Bytes	688.86 GiB	98.88 MiB
Shape	(7134, 3600, 7200)	(2, 1800, 7200)
Dask graph	7134 chunks in 2 graph layers
Data type	float32 numpy.ndarray

lat

PandasIndex

PandasIndex(Index([ -89.9749984741211, -89.92500305175781,            -89.875,
       -89.82499694824219,  -89.7750015258789,  -89.7249984741211,
       -89.67500305175781,            -89.625, -89.57499694824219,
        -89.5250015258789,
       ...
         89.5250015258789,  89.57499694824219,             89.625,
        89.67500305175781,   89.7249984741211,   89.7750015258789,
        89.82499694824219,             89.875,  89.92500305175781,
         89.9749984741211],
      dtype='float32', name='lat', length=3600))

lon

PandasIndex

PandasIndex(Index([-179.97500610351562,  -179.9250030517578,            -179.875,
        -179.8249969482422, -179.77499389648438, -179.72500610351562,
        -179.6750030517578,            -179.625,  -179.5749969482422,
       -179.52499389648438,
       ...
        179.52499389648438,   179.5749969482422,             179.625,
         179.6750030517578,  179.72500610351562,  179.77499389648438,
         179.8249969482422,             179.875,   179.9250030517578,
        179.97500610351562],
      dtype='float32', name='lon', length=7200))

time

PandasIndex

PandasIndex(DatetimeIndex(['2002-09-01 12:00:00', '2002-09-02 12:00:00',
               '2002-09-03 12:00:00', '2002-09-04 12:00:00',
               '2002-09-05 12:00:00', '2002-09-06 12:00:00',
               '2002-09-07 12:00:00', '2002-09-08 12:00:00',
               '2002-09-09 12:00:00', '2002-09-10 12:00:00',
               ...
               '2022-03-11 12:00:00', '2022-03-12 12:00:00',
               '2022-03-13 12:00:00', '2022-03-14 12:00:00',
               '2022-03-15 12:00:00', '2022-03-16 12:00:00',
               '2022-03-17 12:00:00', '2022-03-18 12:00:00',
               '2022-03-19 12:00:00', '2022-03-20 12:00:00'],
              dtype='datetime64[ns]', name='time', length=7134, freq=None))

Conventions :: CF-1.4, Unidata Observation Dataset v1.0
Metadata_Conventions :: Unidata Observation Dataset v1.0
acknowledgment :: NOAA/NESDIS
cdm_data_type :: grid
comment :: The Geo-Polar Blended Sea Surface Temperature (SST) Analysis combines multi-satellite retrievals of sea surface temperature into a single analysis of SST
creator_email :: andy.harris@noaa.gov
creator_name :: Satellite Applications and Research
creator_url :: www.star.nesdis.noaa.gov
date_created :: 20170622T163825Z
easternmost_longitude :: 180.0
file_quality_level :: 0.0
gds_version_id :: 2.0
geospatial_lat_resolution :: 0.05
geospatial_lat_units :: degrees north
geospatial_lon_resolution :: 0.05
geospatial_lon_units :: degrees east
history :: Fri Oct 19 11:12:34 2018: ncatted -a add_offset,analysis_error,o,f,0. 20020901000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.nc Fri Oct 19 11:09:25 2018: ncatted -a add_offset,analysed_sst,o,f,273.15 20020901000000-STAR-L4_GHRSST-SSTfnd-Geo_Polar_Blended_Night-GLOB-v02.0-fv01.0.nc NESDIS geo-SST L1 to L2 processor, NESDIS Advanced Clear-Sky Processor for Oceans (ACSPO), NESDIS Geo-Polar 1/20th degree Blended SST Analysis
id :: Geo_Polar_Blended_Night-STAR-L4-GLOB-v1.0
institution :: Office of Satellite Products and Operations
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
metadata_link :: http://podaac.jpl.nasa.gov:8890/ws/metadata/dataset?format=iso&shortName=Geo_Polar_Blended_Night-STAR-L4-GLOB-v1.0
naming_authority :: org.ghrsst
netcdf_version_id :: 4.1.3
northernmost_latitude :: 90.0
platform :: NOAA-16, NOAA-17, NOAA-18, NOAA-19, MetOpA, Himawari-8, GOES10, GOES11, GOES12, GOES13, GOES15, MTSAT1R, MTSAT2
processing_level :: L4
product_version :: 1.0
project :: Group for High Resolution Sea Surface Temperature
publisher_email :: ghrsst-po@nceo.ac.uk
publisher_name :: The GHRSST Project Office
publisher_url :: http://www.ghrsst.org
references :: Fieguth,P.W. et al. "Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm", J. Atmos. Ocean Tech, 15 (2): 535-546, 1998. Fieguth, P. Multiply-Rooted Multiscale Models for Large-Scale Estimation, IEEE Image Processing, 10(11), 1676-1686, 2001. Khellah, F., P.W. Fieguth, M.J. Murray and M.R. Allen, "Statistical Processing of Large Image Sequences", IEEE Transactions on Geoscience and Remote Sensing, 12 (1), 80-93, 2005. Maturi, E., A. Harris, J. Mittaz, J. Sapper, G. Wick, X. Zhu, P. Dash, P. Koner, "A New High-Resolution Sea Surface Temperature Blended Analysis", Bulleting of the American Meteorological Society, 98 (5), 1015-1026, 2017.
sensor :: AVHRR_GAC, AHI, GOES_Imager, JAMI
source :: STAR-ACSPO_GAC, STAR-ACSPO_H-8, STAR-Geo_SST, UKMO-OSTIA
southernmost_latitude :: -90.0
spatial_resolution :: 0.05 degree
standard_name_vocabulary :: NetCDF Climate and Forecast (CF) Metadata Convetion
start_time :: 20020901T000000Z
stop_time :: 20020902T000000Z
summary :: An SST estimation scheme which combines multi-satellite retrievals of sea surface temperature datasets available from polar orbiters, geostationary IR and microwave sensors into a single global analysis. This global SST ananlysis provide a daily gap free map of the foundation sea surface temperature at 0.05o spatial resolution.
time_coverage_end :: 20020902T000000Z
time_coverage_start :: 20020901T000000Z
title :: Analysed blended sea surface temperature over the global ocean
uuid :: 7c4fc02a-1034-4021-be6f-c3ce858fd33a
westernmost_longitude :: -180.0