Chlorophyll (Gap-filled DINEOF), NOAA S-NPP NOAA-20 VIIRS and Copernicus S-3A OLCI, Science Quality, Global 9km, 2018-
recent, Daily

Visible and Infrared Imager/Radiometer Suite/Suomi-NPP and NOAA-20 (VIIRS) and Sentinel-3A OLCI DINEOF gap filled L4 data. NOAA National Environmental Satellite, Data, and Information Service (NESDIS) STAR data. Sentinel-3A courtesy of Copernicus Program

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlor_a (Chlorophyll Concentration, DINEOF Gap-Filled, mg m^-3)


Chlorophyll (Gap-filled DINEOF), NOAA S-NPP NOAA-20, VIIRS, Near Real-Time, Global 9km, 2020-present,  Daily

Visible and Infrared Imager/Radiometer Suite/Suomi-NPP NOAA-20 (VIIRS) Level-3 (WW00), Chlorophyll, DINEOF, Gap filled, MSL12,  Global, Daily, processed by NOAA.  EXPERIMENTAL.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlor_a (Chlorophyll Concentration, DINEOF Gap-Filled, mg m^-3)


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite)

This dataset has Level 3, Standard Mapped Image, 4km, chlorophyll-a concentration data from NASA's Aqua Spacecraft.  Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft.  This is Science Quality data.  This is the August 2015 version of this dataset.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlorophyll (Mean Chlorophyll a Concentration, mg m-3)


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite)


Chlorophyll-a, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite)


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite)

This dataset has monthly composites of Level 3, Standard Mapped Image, 4km, Diffuse Attenuation Coefficient at 490 nm Wavelength data from NASA's Aqua Spacecraft.  Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft. This is Science Quality data.  This is the August 2015 version of this dataset.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
k490 (Diffuse Attenuation Coefficient K490, m-1)


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite)


Diffuse Attenuation K490, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite)


ESA CCI Ocean Colour Product (CCI ALL-v5.0-8DAY), 0.04166666°, 1997-present

Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are 8 day composites of merged sensor (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Sea-Wide Field-of-View Sensor (SeaWiFS) Local Area Coverage (LAC) & Global Area Coverage (GAC), Visible and Infrared Imager/Radiometer Suite (VIIRS), OLCI) products.  MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007.  VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2013; and at the third stage OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30.  VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.12 (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with polymer.  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's SNAP.  Derived products were generally computed with the standard algorithmsthrough SeaDAS.  QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting.  The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships.  Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated accorsing to Jackson et al. (in prep).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_412 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_443 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_490 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm., sr-1)
Rrs_510 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 510 nm., sr-1)
Rrs_560 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 560 nm., sr-1)
Rrs_665 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 665 nm., sr-1)
water_class1 (Mean of normalised water class 1 membership over the compositing period)
water_class2 (Mean of normalised water class 2 membership over the compositing period)
water_class3 (Mean of normalised water class 3 membership over the compositing period)
... (83 more variables)


ESA CCI Ocean Colour Product (CCI ALL-v5.0-MONTHLY), 0.04166666°, 1997-present

Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are monthly composites of merged sensor (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Sea-Wide Field-of-View Sensor (SeaWiFS) Local Area Coverage (LAC) & Global Area Coverage (GAC), Visible and Infrared Imager/Radiometer Suite (VIIRS), OLCI) products.  MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007.  VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2013; and at the third stage OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30.  VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.12 (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with polymer.  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's SNAP.  Derived products were generally computed with the standard algorithmsthrough SeaDAS.  QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting.  The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships.  Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated accorsing to Jackson et al. (in prep).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_412 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_443 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_490 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm., sr-1)
Rrs_510 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 510 nm., sr-1)
Rrs_560 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 560 nm., sr-1)
Rrs_665 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 665 nm., sr-1)
water_class1 (Mean of normalised water class 1 membership over the compositing period)
water_class2 (Mean of normalised water class 2 membership over the compositing period)
water_class3 (Mean of normalised water class 3 membership over the compositing period)
... (83 more variables)


ESA CCI Ocean Colour Product (CCI ALL-v6.0-5DAY), 0.041666668°, 1997-present

Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are 5 day composites of merged sensor (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Sea-Wide Field-of-View Sensor (SeaWiFS) Local Area Coverage (LAC) & Global Area Coverage (GAC), Visible and Infrared Imager/Radiometer Suite (VIIRS), OLCI) products.  MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007.  VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2014; at the third stage Sentinel-3A OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30;  at the fourth stage Sentinel-3B OLCI was bias corrected against already corrected Sentinel-3A OLCI, for overlap period 2018-07-01 to 2021-06-30.  VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS POLYMER (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with POLYMER.  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's SNAP.  Derived products were generally computed with the standard algorithms through SeaDAS.  QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting.  The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships.  Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated according to Jackson et al. (in prep).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_412 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_bias (Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_rmsd (Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_443 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_443_bias (Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_443_rmsd (Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_490 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm., sr-1)
... (86 more variables)


ESA CCI Ocean Colour Product (CCI ALL-v6.0-8DAY), 0.041666668°, 1997-present

Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are 8 day composites of merged sensor (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Sea-Wide Field-of-View Sensor (SeaWiFS) Local Area Coverage (LAC) & Global Area Coverage (GAC), Visible and Infrared Imager/Radiometer Suite (VIIRS), OLCI) products.  MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007.  VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2014; at the third stage Sentinel-3A OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30;  at the fourth stage Sentinel-3B OLCI was bias corrected against already corrected Sentinel-3A OLCI, for overlap period 2018-07-01 to 2021-06-30.  VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS POLYMER (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with POLYMER.  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's SNAP.  Derived products were generally computed with the standard algorithms through SeaDAS.  QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting.  The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships.  Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated according to Jackson et al. (in prep).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_412 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_bias (Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_rmsd (Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_443 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_443_bias (Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_443_rmsd (Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_490 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm., sr-1)
... (86 more variables)


ESA CCI Ocean Colour Product (CCI ALL-v6.0-DAILY), 0.041666668°, 1997-present

Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are daily composites of merged sensor (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Sea-Wide Field-of-View Sensor (SeaWiFS) Local Area Coverage (LAC) & Global Area Coverage (GAC), Visible and Infrared Imager/Radiometer Suite (VIIRS), OLCI) products.  MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007.  VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2014; at the third stage Sentinel-3A OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30;  at the fourth stage Sentinel-3B OLCI was bias corrected against already corrected Sentinel-3A OLCI, for overlap period 2018-07-01 to 2021-06-30.  VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS POLYMER (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with POLYMER.  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's SNAP.  Derived products were generally computed with the standard algorithms through SeaDAS.  QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting.  The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships.  Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated according to Jackson et al. (in prep).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
MERIS_nobs (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
OLCI_A_nobs (Count of the number of observations from the OLCI (Sentinel-3a) sensor contributing to this bin cell)
OLCI_B_nobs (Count of the number of observations from the OLCI (Sentinel-3b) sensor contributing to this bin cell)
Rrs_412 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_bias (Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_rmsd (Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
... (86 more variables)


ESA CCI Ocean Colour Product (CCI ALL-v6.0-MONTHLY), 0.041666668°, 1997-2022

Data products generated by the Ocean Colour component of the European Space Agency Climate Change Initiative project. These files are monthly composites of merged sensor (MERIS, Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua, Sea-Wide Field-of-View Sensor (SeaWiFS) Local Area Coverage (LAC) & Global Area Coverage (GAC), Visible and Infrared Imager/Radiometer Suite (VIIRS), OLCI) products.  MODIS Aqua and SeaWiFS were band-shifted and bias-corrected to MERIS bands and values using a temporally and spatially varying scheme based on the overlap years of 2003-2007.  VIIRS was band-shifted and bias-corrected in a second stage against the MODIS Rrs that had already been corrected to MERIS levels, for the overlap period 2012-2014; at the third stage Sentinel-3A OLCI was bias corrected against already corrected MODIS, for overlap period 2016-07-01 to 2019-06-30;  at the fourth stage Sentinel-3B OLCI was bias corrected against already corrected Sentinel-3A OLCI, for overlap period 2018-07-01 to 2021-06-30.  VIIRS, MODIS, SeaWiFS and MERIS Rrs were derived from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS POLYMER (for atmospheric correction). OLCI Rrs were sourced at L1b (already geometrically corrected) and processed with POLYMER.  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's SNAP.  Derived products were generally computed with the standard algorithms through SeaDAS.  QAA IOPs were derived using the standard SeaDAS algorithm but with a modified backscattering table to match that used in the bandshifting.  The final chlorophyll is a combination of OCI, OCI2, OC2 and OCx, depending on the water class memberships.  Uncertainty estimates were added using the fuzzy water classifier and uncertainty estimation algorithm of Tim Moore as documented in Jackson et al (2017). and updated according to Jackson et al. (in prep).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_412 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_bias (Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_412_rmsd (Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm., sr-1)
Rrs_443 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_443_bias (Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_443_rmsd (Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm., sr-1)
Rrs_490 (Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm., sr-1)
... (86 more variables)


Fluorescence Line Height, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite)

This dataset has monthly composites of Level 3, Standard Mapped Image, 4km, chlorophyll fluorescence data from NASA's Aqua Spacecraft, which gives insight into the physiology of phytoplankton in the ocean. When phytoplankton are under stress, the rate at which they fluoresce can be decoupled from the rate of photosynthetic productivity. Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft. This is Science Quality data.  This is the August 2015 version of this dataset.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
cflh (Normalized Fluorescence Line Height, W m-2 um-1 sr-1)


Fluorescence Line Height, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite)


Fluorescence Line Height, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite)


Kd490 (Gap-filled DINEOF), NOAA S-NPP NOAA-20 VIIRS and Copernicus S-3A OLCI, Science Quality, Global 9km, 2018-recent, Daily

Visible and Infrared Imager/Radiometer Suite/Suomi-NPP and NOAA-20 (VIIRS) and Sentinel-3A OLCI DINEOF gap filled L4 data. NOAA National Environmental Satellite, Data, and Information Service (NESDIS) STAR data. Sentinel-3A courtesy of Copernicus Program

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
kd_490 (Diffuse attenuation coefficient at 490 nm, kd2 algorithm, m^-1)


Multi-scale Ultra-high Resolution (MUR) SST Analysis Anomaly fv04.1, Global, 0.01°, 2002-present, Daily

A daily Sea Surface Temperature (SST) Anomaly product created by ERD based on JPL MUR's climatology (2003-2014) of the Jet Propulsion Laboratory's (JPL) Multi-scale Ultra-high Resolution (MUR), merged, multi-sensor L4 v4.1 Foundation SST analysis product (part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project).

The data for the most recent 4 days is usually revised everyday.  The data for other days is sometimes revised.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sstAnom (sea surface temperature anomaly, degree_C)
mask (sea/land field composite mask)

NOAA NMFS SWFSC ERD and NOAA NESDIS CoastWatch WCRN


Multi-scale Ultra-high Resolution (MUR) SST Analysis Anomaly fv04.1, Global, 0.01°, 2002-present, Monthly

This monthly Sea Surface Temperature (SST) Anomaly product is a simple mean of the daily anomaly product created by ERD for a given month.  The daily anomalies were created by ERD based on JPL MUR's climatology (2003-2014) of the Jet Propulsion Laboratory's (JPL) Multi-scale Ultra-high Resolution (MUR), merged, multi-sensor L4 v4.1 Foundation SST analysis product (part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sstAnom (Sea Surface Temperature Anomaly Monthly Mean, degree_C)
mask (sea/land field composite mask)


Multi-scale Ultra-high Resolution (MUR) SST Analysis fv04.1, Global, 0.01°, 2002-present, Daily

This is a merged, multi-sensor L4 Foundation Sea Surface Temperature (SST) analysis product from Jet Propulsion Laboratory (JPL). This daily, global, Multi-scale, Ultra-high Resolution (MUR) Sea Surface Temperature (SST) 1-km data set, Version 4.1, is produced at JPL under the NASA MEaSUREs program. For details, see https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1 . This dataset is part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project. The data for the most recent 7 days is usually revised everyday.  The data for other days is sometimes revised.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (Analysed Sea Surface Temperature, degree_C)
analysis_error (Estimated Error Standard Deviation of analysed_sst, degree_C)
mask (Sea/Land Field Composite Mask)
sea_ice_fraction (Sea Ice Area Fraction, 1)


Multi-scale Ultra-high Resolution (MUR) SST Analysis fv04.1, Global, 0.01°, 2002-present, Monthly

A monthly mean Sea Surface Temperature (SST) product created by NOAA NMFS SWFSC ERD based on the daily, global, Multi-scale, Ultra-high Resolution (MUR) Sea Surface Temperature (SST) 1-km data set, Version 4.1, which is produced at the NASA Jet Propulsion Laboratory (JPL) under the NASA MEaSUREs program. For details of the source dataset, see https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1 . The source dataset is part of the Group for High-Resolution Sea Surface Temperature (GHRSST) project.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sst (Sea Surface Temperature Monthly Mean, degree_C)
nobs (Number of Observations)
mask (Sea/Land Field Composite Mask)

NOAA ERD and CoastWatch West Coast Regional Node


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 10 m Wind, Lon+/-180

Navy Global Environmental Model (NAVGEM) is a global numerical weather prediction computer model. It replaced NOGAPS as the prime model in the middle of February 2013 at the Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC) Weather model synoptic site. [Wikipedia]

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
wnd_ucmp_height_above_ground (Eastward Wind, m s-1)
wnd_vcmp_height_above_ground (Northward Wind, m s-1)


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 20 m Wind, Lon+/-180


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, 500 hPa Height, Lon+/-180

Navy Global Environmental Model (NAVGEM) is a global numerical weather prediction computer model. It replaced NOGAPS as the prime model in the middle of February 2013 at the Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC) Weather model synoptic site. [Wikipedia]

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][isobaric][latitude][longitude]):
geop_ht_isobaric (Geopotential Height (500 hPa), gpm)


Navy Global Environmental Model (NAVGEM), 0.5 degree, 2013-present, Pressure MSL, Lon+/-180

Navy Global Environmental Model (NAVGEM) is a global numerical weather prediction computer model. It replaced NOGAPS as the prime model in the middle of February 2013 at the Navy Fleet Numerical Meteorology and Oceanography Center (FNMOC) Weather model synoptic site. [Wikipedia]

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
pres_reduced_msl (Pressure (adjusted to Mean Sea Level), hPa)


NOAA CoastWatch, Sea Surface Height Anomalies and Geostrophic Currents from Altimetry, Global, 2017-present, EXPERIMENTAL

The altimetry data are from RADS (http://rads.tudelft.nl/rads/rads.shtml), the Radar Altimetry Database System, first developed at Delft University of Technology, now also at the NOAA and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). The RADS data for each mission is updated with state of the art corrections for tides, atmospheric path delay, etc. Because they are all computed consistently between the various missions, this avoids the possibility of introducing biases and drifts because of the different implementation of the various corrections by different agencies. The goals of RADS are to provide a homogenous dataset of sea level anomalies, wave heights, and wind speeds, along with database selection and analysis tools.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sla (Sea Level Anomalies, m)
ugos (Absolute Geostrophic Velocity: Zonal Component, m s-1)
vgos (Absolute Geostrophic Velocity: Meridian Component, m s-1)

NOAA/NESDIS Center for Satellite Applications and Research


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (1 Day Composite)

This dataset has Level 3, Standard Mapped Image, 4km, photosynthetically available radiation (PAR) data from NASA's Aqua Spacecraft.  Measurements are gathered by the Moderate Resolution Imaging Spectroradiometer (MODIS) carried aboard the spacecraft.  This is Science Quality data.  This is the August 2015 version of this dataset.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
par (Photosynthetically Available Radiation, R. Frouin, einstein m-2 day-1)


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (8 Day Composite)


Photosynthetically Available Radiation, Aqua MODIS, NPP, L3SMI, Global, 4km, Science Quality, 2003-present (Monthly Composite)


Sea Surface Height, Absolute, Aviso, 0.25 degrees, Global, 1992-2010, Science Quality (Monthly Composite)

Aviso Absolute Sea Surface Height is the Sea Surface Height Deviation plus the long term mean dynamic height. This is Science Quality data.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
ssh (Absolute Sea Surface Height, m)
sshd (Sea Surface Height Deviation, m)


Sea Surface Height, Absolute, Aviso, 0.25 degrees, Global, 1992-2010, Science Quality (Monthly Composite), Lon+/-180


Sea Surface Height, Absolute, Aviso, 0.25 degrees, Global, 1992-2012, Science Quality (1 Day Composite), Lon+/-180


Sea Surface Height, Aviso, Global, Science Quality (1 Day Composite)

Aviso Absolute Sea Surface Height is the Sea Surface Height Deviation plus the long term mean dynamic height. This is Science Quality data.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
ssh (Sea Surface Height, m)
sshd (Sea Surface Height Deviation, m)


Sea Surface Salinity, Miras SMOS, Near Real-Time, Global 0.25°, 2010-present, 3 Day Composite, Lon0360

Sea Surface Salinity - Near Real Time - Miras SMOS 3-Day Mean. CoastWatch/OceanWatch Level-3 SSS products are generated directly from the ESA MIRAS SMOS Level-2 swath Network Common Data Format (NetCDF) files (currently V6.62; see release "https://earth.esa.int/documents/10174/1854503/SMOS-Level-2-Ocean-Salinity-v662-release-note" ). There are two SSS variables in V6.62 L2 NetCDF files, SSS_corr (corrected for land-sea contamination) and SSS_uncorr. The CoastWatch L3 product ingests the SSS_corr  with values between 25 - 40 Practical Salinity Scale (PSS). These products improve the application of satellite SSS products in NOAA by minimizing the data latency to within 24 hours of Level-2 data availability.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
sss (Sea Surface Salinity, PSU)
sss_dif (SMOS Sea Surface Salinity minus World Ocean Atlas Value, PSU)


Sea Surface Salinity, Miras SMOS, Near Real-Time, Global 0.25°, 2010-present, Daily, Lon0360

Sea Surface Salinity - Near Real Time - Miras SMOS Daily Composite. CoastWatch/OceanWatch Level-3 SSS products are generated directly from the ESA MIRAS SMOS Level-2 swath Network Common Data Format (NetCDF) files (currently V6.62; see release "https://earth.esa.int/documents/10174/1854503/SMOS-Level-2-Ocean-Salinity-v662-release-note" ). There are two SSS variables in V6.62 L2 NetCDF files, SSS_corr (corrected for land-sea contamination) and SSS_uncorr. The CoastWatch L3 product ingests the SSS_corr  with values between 25 - 40 Practical Salinity Scale (PSS). These products improve the application of satellite SSS products in NOAA by minimizing the data latency to within 24 hours of Level-2 data availability.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
sss (Sea Surface Salinity, PSU)
sss_dif (SMOS Sea Surface Salinity minus World Ocean Atlas Value, PSU)
l2_time (Time from L2 files, seconds since 1970-01-01T00:00:00Z)
l2_lat (Latitude from L2 files, degrees_north)
l2_lon (Longitude from L2 files, degrees_north)


Sea-Surface Temperature, NOAA ACSPO NOAA-20 VIIRS CoastWatch Co-gridded 4km Daily (degrees C)

Sea surface temperature retrievals produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from Visible and Infrared Imager/Radiometer Suite (VIIRS) sensor

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
sea_surface_temperature (sea surface sub-skin temperature, degree_C)


Sea-Surface Temperature, NOAA ACSPO S-NPP VIIRS CoastWatch Co-gridded 4km Daily (degrees C)

Sea surface temperature retrievals produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from Visi                                      ble and Infrared Imager/Radiometer Suite (VIIRS) sensor

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
sea_surface_temperature (sea surface sub-skin temperature, degree_C)


Sea-Surface Temperature, NOAA Geo-polar Blended Analysis Night Only, GHRSST, Near Real-Time, Global 5km, 2002-Present, Daily (degree C)

Analyzed blended sea surface temperature over the global ocean using night only input data. An SST estimation scheme which combines multi-satellite retrieva
ls of sea surface temperature datasets available from polar orbiters, geostationary InfraRed (IR) and microwave sensors into a single global analysis. This global SST analysis provides
 a daily gap-free map of the foundation sea surface temperature at 0.05Âº spatial resolution. Note 2002-2016 is a reanalysis.  2017-present is near real-time processing.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_C)
analysis_error (estimated error standard deviation of analysed_sst, kelvin)
mask (sea/land/ice bit mask)
sea_ice_fraction (1)


SST, Pathfinder Ver 5.2 (L3C), Day and Night, Global, 0.0417°, 1981-2006, Science Quality (8 Day Composite)

This dataset contains sea surface temperature (SST) data produced as part of the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST Project, created using Version 5.2 of the Pathfinder algorithm and the dataset. Multi-day composites and composites of day and night datasets were generated by the Environmental Research Division (NOAA/NMFS/SWFSC/ERD).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m Wind Speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.2 (L3C), Day and Night, Global, 0.0417°, 1981-2012, Science Quality (1 Day Composite)


SST, Pathfinder Ver 5.2 (L3C), Day and Night, Global, 0.0417°, 1981-2012, Science Quality (Monthly Composite)


SST, Pathfinder Ver 5.3 (L3C), Day, Global, 0.0417°, 1981-present, Science Quality (8 Day Composite)

This dataset contains 8-day-composites of daytime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.3 (L3C), Day, Global, 0.0417°, 1981-present, Science Quality (Monthly Composite)

This dataset contains monthly composites of daytime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.3 (L3C), Night, Global, 0.0417°, 1981-present, Science Quality (8 Day Composite)

This dataset contains 8-day-composites of nighttime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, Pathfinder Ver 5.3 (L3C), Night, Global, 0.0417°, 1981-present, Science Quality (Monthly Composite)

This dataset contains monthly composites of nighttime sea surface temperature (SST) data produced as part of the AVHRR Pathfinder SST Project. The source data were created using Version 5.3 of the Pathfinder algorithm and the file is nearly but not completely compliant with the GHRSST Data Specifications V2.0 (GDS2). Source data were created by the NOAA National Centers for Environmental Information (NCEI). Multi-day composites were created by NOAA CoastWatch-West Coast and NOAA/SWFSC/ERD.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (NOAA Climate Data Record of Sea Surface Skin Temperature, degree_C)
sea_ice_fraction (1)
wind_speed (10m wind speed, m s-1)
l2p_flags


SST, VIIRS NOAA-20, Alaska, 750m, 2020-present, Science Quality Daily

Daily global sea surface temperature produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from the Visible and Infrared Imager/Radiometer Suite (VIIRS) NOAA-20 sensor. The data were processed by the Advanced Clear-Sky Processor for Oceans (ACSPO).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (degree_C)


SST, VIIRS NOAA-20, Alaska, 750m, 2020-present, Science Quality Monthly

Monthly global sea surface temperature produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from the Visible and Infrared Imager/Radiometer Suite (VIIRS) NOAA-20 sensor. The data were processed by the Advanced Clear-Sky Processor for Oceans (ACSPO).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (degree_C)


SST, VIIRS NOAA-20, Alaska, 750m, 2020-present, Science Quality Weekly

Weekly global sea surface temperature produced by NOAA/NESDIS/Office of Satellite and Product Operations (OSPO) office from the Visible and Infrared Imager/Radiometer Suite (VIIRS) NOAA-20 sensor. The data were processed by the Advanced Clear-Sky Processor for Oceans (ACSPO).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
sea_surface_temperature (degree_C)


Suspended Particulate Matter (Gap-filled DINEOF), NOAA S-NPP NOAA-20 VIIRS and Copernicus S-3A OLCI, Science Quality, Global 9km, 2018-recent, Daily

Visible and Infrared Imager/Radiometer Suite/Suomi-NPP and NOAA-20 (VIIRS) and Sentinel-3A OLCI DINEOF gap filled L4 data. NOAA National Environmental Satellite, Data, and Information Service (NESDIS) STAR data. Sentinel-3A courtesy of Copernicus Program

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
spm (Suspended Particulate Matter, mg l-1)


Topography, ETOPO1, 0.0166667 degrees, Global (longitude -180 to 180), (Ice Sheet Surface)

ETOPO1 is a 1 arc-minute global relief model of Earth's surface that integrates land topography and ocean bathymetry. It was built from numerous global and regional data sets. This is the 'Ice Surface' version, with the top of the Antarctic and Greenland ice sheets. The horizontal datum is WGS-84, the vertical datum is Mean Sea Level. Keywords: Bathymetry, Digital Elevation. This is the grid/node-registered version: the dataset's latitude and longitude values mark the centers of the cells.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
altitude (m)


Topography, ETOPO1, 0.0166667 degrees, Global (longitude 0 to 360), (Ice Sheet Surface)


Wind, All Metop ASCAT, 0.25°, Global, Near Real Time, 2013-present (Monthly), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instruments onboard all EUMETSAT's MetOp satellites.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a monthly composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (1 Day), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a 1 day composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (3 Day), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a 3 day composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (8 Day), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is an 8 day composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


Wind, Metop-B ASCAT, 0.25°, Global, Near Real Time, 2013-present (Monthly), Lon+/-180

NOAA CoastWatch distributes near real time wind data originating with wind velocity measurements from the ASCAT instrument onboard EUMETSAT's Metop-B satellite.  ASCAT is a microwave scatterometer designed to measure surface winds over the global ocean.  Wind velocity is processed to wind divergence by NOAA CoastWatch. (This is a monthly composite.)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
x_wind (Zonal Wind, m s-1)
y_wind (Meridional Wind, m s-1)


X-experimental - Particulate Organic Carbon in Ocean Surface Water, MODIS, 9km, NASA SMI, Stramski 2022

Particulate Organic Carbon in Ocean Surface Water, MODIS Aqua, 9km, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
poc_stdev (Standard Deviation for Particulate Organic Carbon, mg m^-3)
poc_var (Variance for Particulate Organic Carbon, mg m^-3)
poc_nobs (Number Particulate Organic Carbon of Observations, count)


X-experimental - Particulate Organic Carbon in Ocean Surface Water, SeaWiFS, 9km, NASA SMI, Stramski 2022

Particulate Organic Carbon in Ocean Surface Water, Sea-Wide Field-of-View Sensor (SeaWiFS), 9km, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
poc_stdev (Standard Deviation for Particulate Organic Carbon, mg m^-3)
poc_var (Variance for Particulate Organic Carbon, mg m^-3)
poc_nobs (Number Particulate Organic Carbon of Observations, count)


X-experimental - Particulate Organic Carbon in Ocean Surface Water, VIIRS SNPP, 9km, NASA SMI, Stramski 2022

Particulate Organic Carbon in Ocean Surface Water, VIIRS SNPP, Level-3, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
poc_stdev (Standard Deviation for Particulate Organic Carbon, mg m^-3)
poc_var (Variance for Particulate Organic Carbon, mg m^-3)
poc_nobs (Number Particulate Organic Carbon of Observations, count)


X-Experimental Chlorophyll, S-NPP VIIR, Alaska, Daily

Ocean color standard products include normalized water-leaving radiances, chlorophyll-a concentration, diffusive attenuation coefficient at 490 nm and diffusive attenuation coefficient of the photosynthetically available radiation (PAR).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll Concentration, OC3 Algorithm, mg m^-3)


X-Experimental Far Red Remote Sensing Reflectance (745nm 862nm), S-NPP VIIR, Alaska, Daily

Ocean color products include remote sensing reflectance at 745nm and 862nm, chlorophyll-a concentration, diffusive attenuation coefficient at 490 nm and diffusive attenuation coefficient of the photosynthetically available radiation (PAR).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_745 (Remove Sensing Reflectance 745nm, sr^-1)
Rrs_862 (Remove Sensing Reflectance 862nm, sr^-1)
par (Photosynthetically Available Radiation, sr^-1)
kd_490 (Diffuse Attenuation Coefficient at 490nm, m-1)
kd_par (Diffuse Attenuation Coefficient for PAR, m-1)


X-Experimental POC from NOAA S-NPP VIIRS Source Data

Particulate Organic Carbon in Ocean Surface Water, Sea-Wide Field-of-View Sensor (SeaWiFS), 9km, NASA Standard Mapped Image (SMI), Stramski 2022

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
poc (Particulate Organic Carbon, D. Stramski, 2022, mg m^-3)
Rrs_443 (Remote Sensing Reflectance at 443 nm, sr^-1)
Rrs_486 (Remote Sensing Reflectance at 486 nm, sr^-1)
Rrs_551 (Remote Sensing Reflectance at 551 nm, W m^-2 um^-1 sr^-1)
Rrs_510v (Virtual Remote Sensing Reflectance at 510 nm, W m^-2 um^-1 sr^-1)


X-Experimental Remote Sensing Reflectance, S-NPP VIIR, Alaska, Daily

Ocean color standard products include normalized water-leaving radiances, chlorophyll-a concentration, diffusive attenuation coefficient at 490 nm and diffusive attenuation coefficient of the photosynthetically available radiation (PAR).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Rrs_410 (SNPP Remote Sensing Reflectance at 410 nm, sr^-1)
Rrs_443 (Remove Sensing Reflectance 443nm, sr^-1)
Rrs_486 (Remove Sensing Reflectance 486nm, sr^-1)
Rrs_551 (Remove Sensing Reflectance 551nm, sr^-1)
Rrs_638 (Remove Sensing Reflectance 638nm)
Rrs_671 (Remove Sensing Reflectance 671nm, sr^-1)