* The List of All Active Datasets in this ERDDAP *

Summary:
This dataset is a table which has a row of information for each dataset currently active in this ERDDAP.

cdm_data_type = Other
VARIABLES:
datasetID (Dataset ID)
accessible
institution
dataStructure (Data Structure)
cdm_data_type (Common Data Model Type)
class (ERDDAP Class)
title
minLongitude (Minimum Longitude, degrees_east)
maxLongitude (Maximum Longitude, degrees_east)
longitudeSpacing (Average Grid Longitude Spacing, degrees_east)
minLatitude (Minimum Latitude, degrees_north)
maxLatitude (Maximum Latitude, degrees_north)
latitudeSpacing (Average Grid Latitude Spacing, degrees_north)
minAltitude (Minimum Altitude (or negative Depth), m)
maxAltitude (Maximum Altitude (or negative Depth), m)
minTime (Minimum Time, seconds since 1970-01-01T00:00:00Z)
maxTime (Maximum Time, seconds since 1970-01-01T00:00:00Z)
timeSpacing (Average Grid Time Spacing, seconds)
griddap (Base URL of OPeNDAP Grid Service)
subset (URL of Subset Web Page)
tabledap (Base URL of OPeNDAP Table/Sequence Service)
MakeAGraph (URL of Make-A-Graph Web Page)
sos (Base URL of SOS Service)
wcs (Base URL of WCS Service)
wms (Base URL of WMS Service)
files (Base URL of "files" Service)
... (10 more variables)


Bathymetry and Topography, NCEI ETOPO 2022, 15 Arc-Second, Global (Ice Surface)

Summary:
ETOPO 2022, a global relief model with 15 arc-second resolution seamlessly integrating topographic and bathymetric data. The ETOPO 2022 model uses a combination of numerous airborne lidar, satellite-derived topography, and shipborne bathymetry datasets from U.S. national and global sources. ETOPO 2022 uses bare-earth topographic data from NASAs ICESat-2 and other vetted data sources to independently validate both the input datasets and the final ETOPO 2022 model. ETOPO 2022 is available in "Ice Surface" (top of Antarctic and Greenland ice sheets) and "Bedrock" (base of the ice sheets) versions. ETOPO Global Topography and Bathymetry. NOAA National Centers for Environmental Information (NCEI) data from a local source.

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


Bathymetry and Topography, NCEI ETOPO 2022, 30 Arc-Second, Global (Ice Surface)

Summary:
ETOPO 2022, a global relief model with 15 arc-second resolution seamlessly integrating topographic and bathymetric data. The ETOPO 2022 model uses a combination of numerous airborne lidar, satellite-derived topography, and shipborne bathymetry datasets from U.S. national and global sources. ETOPO 2022 uses bare-earth topographic data from NASAs ICESat-2 and other vetted data sources to independently validate both the input datasets and the final ETOPO 2022 model. ETOPO 2022 is available in "Ice Surface" (top of Antarctic and Greenland ice sheets) and "Bedrock" (base of the ice sheets) versions. ETOPO Global Topography and Bathymetry. NOAA National Centers for Environmental Information (NCEI) data from a local source.

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


Bathymetry and Topography, NCEI ETOPO 2022, 60 Arc-Second, Global (Ice Surface)


Chlorophyll a Concentration, Aqua MODIS - 8-day, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - 8-day Ocean Color. Chlorophyll-a Concentration. 2002 - present. spatial resolution = 4.64km

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


Chlorophyll a Concentration, Aqua MODIS - Cumulative Mean, January 2003 -February 2019. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - Ocean Color. Chlorophyll-a Concentration. Cumulative mean from January 2003 - February 2019. spatial resolution = 4.64km

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


Chlorophyll a Concentration, Aqua MODIS - Daily, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - Daily Ocean Color. Chlorophyll-a Concentration. 2002 - present. spatial resolution = 4.64km

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


Chlorophyll a Concentration, Aqua MODIS - Monthly, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - Monthly Ocean Color. Chlorophyll-a Concentration. 2002 - present. spatial resolution = 4.64km

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


Chlorophyll a concentration, ESA OC CCI - 8-Day, 1997-present. v6.0

Summary:
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]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
OLCI_A_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3a) sensor contributing to this bin cell)
OLCI_B_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3b) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 1998-2009. v6.0

Summary:
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]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships, mg m-3)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)


Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 1998-2021. v6.0


Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 2023. v6.0


Chlorophyll a concentration, ESA OC CCI - Monthly, 1997-present. v6.0

Summary:
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]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
OLCI_A_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3a) sensor contributing to this bin cell)
OLCI_B_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3b) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


Chlorophyll a Concentration, NPP VIIRS - CoastWatch - Daily, 2012-present

Summary:
Visible and Infrared Imager/Radiometer Suite/Suomi-NPP (VIIRSN) produced by NOAA/STAR Ocean Color Team through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) using the Ocean Color improved satellite data record. This is daily data, 4-km resolution. More info: https://coastwatch.noaa.gov/cw_html/OceanColor_Science_Quality_VIIRS_SNPP.html

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][altitude][latitude][longitude]):
chlor_a (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, mg m^-3)


Chlorophyll a Concentration, NPP VIIRS - CoastWatch - Monthly, 2012-present

Summary:
Visible and Infrared Imager/Radiometer Suite/Suomi-NPP (VIIRSN) produced by NOAA/STAR Ocean Color Team through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) using the Ocean Color improved satellite data record. This is monthly data, 4-km resolution. More info: https://coastwatch.noaa.gov/cw_html/OceanColor_Science_Quality_VIIRS_SNPP.html

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


Chlorophyll a Concentration, NPP VIIRS - CoastWatch - Weekly, 2012-present

Summary:
Visible and Infrared Imager/Radiometer Suite/Suomi-NPP (VIIRSN) produced by NOAA/STAR Ocean Color Team through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) using the Ocean Color improved satellite data record. This is weekly data, 4-km resolution. More info: https://coastwatch.noaa.gov/cw_html/OceanColor_Science_Quality_VIIRS_SNPP.html

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


Chlorophyll a Concentration, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - Monthly, 2012-present

Summary:
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][altitude][latitude][longitude]):
chlor_a (Chlorophyll Concentration, OC3 Algorithm, mg m-3)


Chlorophyll a Concentration, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - Weekly, 2012-present


Chlorophyll a Concentration, SeaWIFS - 8-day, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - 8-day Ocean Color. Chlorophyll-a Concentration. 1997 - 2010. spatial resolution = 9.28km

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


Chlorophyll a Concentration, SeaWIFS - Daily, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - Daily Ocean Color. Chlorophyll-a Concentration. 1997 - 2010. spatial resolution = 9.28km

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


Chlorophyll a Concentration, SeaWIFS - Monthly, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - Monthly Ocean Color. Chlorophyll-a Concentration. 1997 - 2010. spatial resolution = 9.28km

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


Coral Bleaching Alert Area 7-day Maximum Composite, Coral Reef Watch - Daily, 1985-
present

Summary:
This is a product of NOAA Coral Reef Watch Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0. Bleaching Alert Levels: 0 - No stress, 1 - Watch, 2 - Warning, 3 - Alert Level 1, 4 - Alert LEvel 2. For more information: https://coralreefwatch.noaa.gov/product/5km/index_5km_baa_max_r07d.php

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
bleaching_alert_area (bleaching alert area 7-day maximum composite, stress_level)

NOAA/NESDIS/STAR Coral Reef Watch Program


Coral Bleaching HotSpot, Coral Reef Watch - Daily, 1985-present

Summary:
This is a product of NOAA Coral Reef Watch Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
hotspot (coral bleaching hotspot, degree_C)


Degree Heating Week, Coral Reef Watch - Daily, 1985-present

Summary:
This is a product of NOAA Coral Reef Watch Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0.

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


EXPERIMENTAL - Median Phytoplankton Size, North Pacific, Cumulative Mean, 1998-2009

Summary:
Experimental product derived from NOAA CoralReefWatch CoralTemp SST and ESA OC-CCI chlorophyll a concentration using algorithm from Carolyn Barnes, Xabier Irigoien, JosÃ© A. A. De Oliveira, David Maxwell, Simon Jennings, Predicting marine phytoplankton community size structure from empirical relationships with remotely sensed variables, Journal of Plankton Research, Volume 33, Issue 1, January 2011, Pages 13-24, https://doi.org/10.1093/plankt/fbq088

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
MD50 (2.138*(MB50^0.355))


EXPERIMENTAL - Median Phytoplankton Size, North Pacific, Cumulative Mean, 1998-2021


EXPERIMENTAL - Median Phytoplankton Size, North Pacific, Cumulative Mean, 2023


EXPERIMENTAL - Median Phytoplankton Size, North Pacific. Monthly, 1998-present

Summary:
Experimental product derived from NOAA CoralReefWatch CoralTemp SST and ESA OC-CCI chlorophyll a concentration using algorithm from Carolyn Barnes, Xabier Irigoien, JosÃ© A. A. De Oliveira, David Maxwell, Simon Jennings, Predicting marine phytoplankton community size structure from empirical relationships with remotely sensed variables, Journal of Plankton Research, Volume 33, Issue 1, January 2011, Pages 13-24, https://doi.org/10.1093/plankt/fbq088

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
MD50 (2.138*(MB50^0.355))


Kd490, Aqua MODIS - 8-Day, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - 8-Day Ocean Color. Diffuse attenuation coefficient at 490 nm, KD2 algorithm. 2002 - present. spatial resolution = 4.64km

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Kd_490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m-1)


Kd490, Aqua MODIS - Daily, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - Daily Ocean Color. Diffuse attenuation coefficient at 490 nm, KD2 algorithm. 2002 - present. spatial resolution = 4.64km

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Kd_490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m-1)


Kd490, Aqua MODIS - Monthly, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - Monthly Ocean Color. Diffuse attenuation coefficient at 490 nm, KD2 algorithm. 2002 - present. spatial resolution = 4.64km

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Kd_490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m-1)


Kd490, ESA OC CCI - 8-Day, 1997-present. v6.0

Summary:
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]):
kd_490 (Downwelling attenuation coefficient at 490nm, derived using Lee 2005 equation and bbw from Zhang 2009 (following the SeaDAS Kd_lee algorithm), m-1)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
OLCI_A_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3a) sensor contributing to this bin cell)
OLCI_B_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3b) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
kd_490_bias (Bias of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
kd_490_rmsd (Root-mean-square-difference of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


Kd490, ESA OC CCI - Monthly, 1997-present. v6.0

Summary:
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]):
kd_490 (Downwelling attenuation coefficient at 490nm, derived using Lee 2005 equation and bbw from Zhang 2009 (following the SeaDAS Kd_lee algorithm), m-1)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
OLCI_A_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3a) sensor contributing to this bin cell)
OLCI_B_nobs_sum (Count of the number of observations from the OLCI (Sentinel-3b) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
kd_490_bias (Bias of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
kd_490_rmsd (Root-mean-square-difference of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


Kd490, NPP VIIRS - CoastWatch - Daily, 2012-present

Summary:
Visible and Infrared Imager/Radiometer Suite/Suomi-NPP (VIIRSN) produced by NOAA/STAR Ocean Color Team through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) using the Ocean Color improved satellite data record. This is daily Diffuse attenuation coefficient at 490 nm data, 4-km resolution. More info: https://coastwatch.noaa.gov/cw_html/OceanColor_Science_Quality_VIIRS_SNPP.html

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)


Kd490, NPP VIIRS - CoastWatch - Monthly, 2012-present

Summary:
Visible and Infrared Imager/Radiometer Suite/Suomi-NPP (VIIRSN) produced by NOAA/STAR Ocean Color Team through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) using the Ocean Color improved satellite data record. This is monthly Diffuse attenuation coefficient at 490 nm data, 4-km resolution. More info: https://coastwatch.noaa.gov/cw_html/OceanColor_Science_Quality_VIIRS_SNPP.html

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


Kd490, NPP VIIRS - CoastWatch - Weekly, 2012-present

Summary:
Visible and Infrared Imager/Radiometer Suite/Suomi-NPP (VIIRSN) produced by NOAA/STAR Ocean Color Team through NOAA Multi-Sensor Level 1 to Level 2 processing system (MSL12) using the Ocean Color improved satellite data record. This is weekly Diffuse attenuation coefficient at 490 nm data, 4-km resolution. More info: https://coastwatch.noaa.gov/cw_html/OceanColor_Science_Quality_VIIRS_SNPP.html

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)


Kd490, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - Monthly, 2012-present

Summary:
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][altitude][latitude][longitude]):
kd_490 (Diffuse Attenuation Coefficient at 490 nm, m-1)


Kd490, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - Weekly, 2012-present


Kd490, SeaWIFS - 8-Day, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - 8-Day Ocean Color. Diffuse attenuation coefficient at 490 nm, KD2 algorithm. 1997 - 2010. spatial resolution = 9.28km

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Kd_490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m-1)


Kd490, SeaWIFS - Daily, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - Daily Ocean Color. Diffuse attenuation coefficient at 490 nm, KD2 algorithm. 1997 - 2010. spatial resolution = 9.28km

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Kd_490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m-1)


Kd490, SeaWIFS - Monthly, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - Monthly Ocean Color. Diffuse attenuation coefficient at 490 nm, KD2 algorithm. 1997 - 2010. spatial resolution = 9.28km

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
Kd_490 (Diffuse attenuation coefficient at 490 nm, KD2 algorithm, m-1)


KdPAR, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - monthly, 2012-present

Summary:
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][altitude][latitude][longitude]):
kd_par (Diffuse Attenuation Coefficient for PAR, m-1)


KdPAR, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - weekly, 2012-present


Ocean Surface Currents, Ocean Surface Current Analyses Real-time (OSCAR) - 5-day, 1992-2018

Summary:
Maximum Mask velocity is the geostrophic component at all points + any concurrent Ekman and buoyancy components. Longitude extends from 20 E to 420 E to avoid a break in major ocean basins. Data repeats in overlap region. 5-day, spatial resolution = 0.33Âº

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][latitude][longitude]):
u (Ocean Surface Zonal Currents, m s-1)
v (Ocean Surface Meridional Currents, m s-1)
um (Ocean Surface Zonal Currents Maximum Mask, m s-1)
vm (Ocean Surface Meridional Currents Maximum Mask, m s-1)


Ocean Surface Winds - CCMP - 6-hour (Near Real Time), 2016-present. v2.1

Summary:
CCMP_RT V2.1 has been created using the same VAM as CCMP V2.0 Input data have changed and now include all V7 radiometer data from RSS, V8.1 GMI data from RSS, scatterometer data from RSS (V4 QuikSCAT and V1.2 Advanced SCATterometer (ASCAT)), NO buoy data, and National Centers for Environmental Prediction (NCEP) GFS 0.25 degree data for the background field.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind vector component at 10 meters, m s-1)
vwnd (v-wind vector component at 10 meters, m s-1)
nobs (number of observations used to derive wind vector components)


Ocean Surface Winds - CCMP - 6-hour, 1987-2019. v2.0

Summary:
CCMP V2.0 has been created using the same VAM as CCMP V1.1 only it is now running at Remote Sensing Systems. Input data have changed and now include all V7 radiometer data from RSS, V8.1 GMI data from RSS, scatterometer data from RSS (V4 QuikSCAT and V1.2 Advanced SCATterometer (ASCAT)), quality checked moored buoy data from National Data Buoy Center (NDBC), Pacific Marine Environmental Laboratory (PMEL), and ISDM, and ERA-Interim data from European Centre for Medium-Range Weather Forecasts (ECMWF).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind vector component at 10 meters, m s-1)
vwnd (v-wind vector component at 10 meters, m s-1)
nobs (number of observations used to derive wind vector components, count)


Ocean Surface Winds - CCMP - Monthly, 1987-2019. v2.0

Summary:
This is data from the Cross-Calibrated Multi-Platform (CCMP) Wind Vector
Analysis, generated by Remote Sensing Systems. CCMP V2.0 has been created using the same VAM as CCMP V1.1 only it is now running at Remote Sensing Systems. Input data have changed and now include all V7 radiometer data from RSS, V8.1 GMI data from RSS, scatterometer data from RSS (V4 QuikSCAT and V1.2 Advanced SCATterometer (ASCAT)), quality checked moored buoy data from National Data Buoy Center (NDBC), Pacific Marine Environmental Laboratory (PMEL), and ISDM, and ERA-Interim data from European Centre for Medium-Range Weather Forecasts (ECMWF).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
uwnd (u-wind vector component at 10 meters, m s-1)
vwnd (v-wind vector component at 10 meters, m s-1)
wspd (wind speed at 10 meters, m s-1)


Ocean Surface Winds, ASCAT - Daily, 2007-present

Summary:
Daily Advanced SCATterometer (ASCAT) global wind field. HAWAII School of Ocean and Earth Science and Technology (SOEST) data from http://apdrc.soest.hawaii.edu/dods/public_data/satellite_product/ASCAT/daily.das . 0.25Âº resolution. More info: http://apdrc.soest.hawaii.edu/datadoc/ascat.php

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
wsp (wind speed, m s-1)
uwnd (eastward wind speed, m s-1)
vwnd (northward wind speed, m s-1)
wind_stress (wind stress (pa))
uwnd_stress (eastward wind stress (pa))
vwnd_stress (northward wind stress (pa))
wsp_err (wind speed root mean square, m s-1)
uwnd_err (eastward wind speed root mean square, m s-1)
vwnd_err (northward wind speed root mean square, m s-1)
sampling_length


Ocean Surface Winds, QuikSCAT - 3-Day, 1999-2009

Summary:
QuikSCAT Winds - 3Day. Satellite-Derived Ocean Surface Wind Data. 1999 - 2009. spatial resolution = 0.5&deg

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
spd (Ocean Wind Speed, Meters per second)
taux (Zonal Wind Stress, Pascals)
tauy (Meridional Wind Stress, Pascals)
ux (Zonal Wind Speed, meter second-1)
vy (Meridional Wind Speed, meter second-1)

NOAA/NESDIS/OceanWatch - Central Pacific


Ocean Surface Winds, QuikSCAT - Monthly, 1999-2009

Summary:
QuikSCAT Winds - Monthly. Satellite-Derived Ocean Surface Wind Data. 1999 - 2009. spatial resolution = 0.5&deg

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
curl (Wind Stress Curl, Pascals per meter)
divw (Wind Speed Divergence, Seconds^-1)
mag (Wind Speed, Meters per second)
taumag (Wind Stress, Pascals)
taux (Zonal Wind Stress, Pascals)
tauy (Meridional Wind Stress, Pascals)
ux (Zonal Wind Speed, meter second-1)
vy (Meridional Wind Speed, meter second-1)


Ocean Surface Winds, QuikSCAT - Weekly, 1999-2009

Summary:
QuikSCAT Winds - Weekly. Satellite-Derived Ocean Surface Wind Data. 1999 - 2009. spatial resolution = 0.5&deg

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
curl (Wind Stress Curl, Pascals per meter)
divw (Wind Speed Divergence, Seconds^-1)
mag (Wind Speed, Meters per second)
taumag (Wind Stress, Pascals)
taux (Zonal Wind Stress, Pascals)
tauy (Meridional Wind Stress, Pascals)
ux (Zonal Wind Speed, meter second-1)
vy (Meridional Wind Speed, meter second-1)


Photosynthetically Available Radiation (PAR), Aqua MODIS - 8-Day, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - 8-Day Ocean Color. Photosynthetically Available Radiation. 2002 - present. spatial resolution = 4.64km

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 (PAR), Aqua MODIS - Daily, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - Daily Ocean Color. Photosynthetically Available Radiation. 2002 - present. spatial resolution = 4.64km

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 (PAR), Aqua MODIS - Monthly, 2002-present. v.2018.0

Summary:
Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua - Monthly Ocean Color. Photosynthetically Available Radiation. 2002 - present. spatial resolution = 4.64km

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 (PAR), SeaWIFS - 8-Day, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - 8-Day Ocean Color. Photosynthetically Available Radiation. 1997 - 2010. spatial resolution = 9.28km

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 (PAR), SeaWIFS - Daily, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - Daily Ocean Color. Photosynthetically Available Radiation. 1997 - 2010. spatial resolution = 9.28km

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 (PAR), SeaWIFS - Monthly, 1997-2010. v.2018.0

Summary:
Sea-Wide Field-of-View Sensor (SeaWiFS) - Monthly Ocean Color. Photosynthetically Available Radiation. 1997 - 2010. spatial resolution = 9.28km

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)


PIFSC CTD Data

Summary:
This is CTD data from various PIFSC cruises.

cdm_data_type = Point
VARIABLES:
CRUISE_NAME (The name of the given cruise designated by NOAA (e.g. SE-15-01))
CRUISE_START_DATE (The start date of the given research cruise, seconds since 1970-01-01T00:00:00Z)
CRUISE_END_DATE (The end date of the given research cruise, seconds since 1970-01-01T00:00:00Z)
CRUISE_YEAR (The calendar year for the start date of the given research cruise)
VESSEL_NAME (Name of the given research vessel)
LEG_NAME (The name of the given research cruise leg)
latitude (CTD Cast Latitude in decimal degrees, degrees_north)
longitude (CTD Cast Longitude in decimal degrees, degrees_east)
DEPTH_SW_M (Depth [salt water, m])
Temperature (Temperature [ITS-90, deg C])
Salinity (Practical Salinity [PSU])
Density (Sea Water Density [sigma-t, Kg/m^3 ])
Dissolved_Oxygen (Oxygen, SBE 43 [ml/l])
Fluorescence (Fluorescence, WET Labs ECO-AFL/FL [mg/m^3])
pH (Sea Water Ph Reported On Total Scale (ph: pH))
CAST_ID (Primary key for the CTD_CASTS table)
CAST_NUMBER (CTD Cast Number)
time (System UpLoad Time in MM/DD/YYYY HH24:MI:SS format, seconds since 1970-01-01T00:00:00Z)
FORMAT_UTC_DTM (Cast UTC Date/Time in MM/DD/YYYY HH24:MI:SS format, seconds since 1970-01-01T00:00:00Z)
STATION_ID (Primary key for CTD_PERM_STATIONS table)
STATION_LAT_DD (latitude of permanent station in decimal degrees)
STATION_LON_DD (longitude of permanent station in decimal degrees)
FORMAT_LEG_START_DATE (The start date for the given research cruise leg in MM/DD/YYYY format, seconds since 1970-01-01T00:00:00Z)
FORMAT_LEG_END_DATE (The end date for the given research cruise leg in MM/DD/YYYY format, seconds since 1970-01-01T00:00:00Z)
LEG_YEAR (The calendar year for the start date of the given research cruise leg)
LEG_ALIASES_DELIM (Comma delimited list of cruise leg name aliases in alphabetical order for the given research cruise leg)
NUM_REGIONS (The number of distinct regions associated with the given research cruise leg)
... (47 more variables)


satellite product TRMM TRMM PR 3B43 monthly v7

Summary:
satellite product Tropical Rainfall Measuring Mission (TRMM) TRMM PR 3B43 monthly v7

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
rr (3b43 hourly rainfall [mm/hour])
er (3b43 error of precip [mm/hr])
weight (3b43 weight [%])


Sea Surface Height Anomalies and Geostrophic Currents, Delayed-Time, NOAA/NESDIS/STAR - Daily, 2012-2019

Summary:
The NOAA Laboratory for Satellite Altimetry's (LSA) sea surface height team produces 0.25-degree longitude/latitude Level-3 sea level anomaly (SLA) daily datasets by applying optimal interpolation to along-track satellite observations over the global ocean from a constellation of radar altimeter missions. More information: https://coastwatch.noaa.gov/cw/satellite-data-products/sea-surface-height/optimal-interpolation-level-3-sea-level-anomalies-from-multiple-altimeter-missions.html

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

NOAA/NESDIS Center for Satellite Applications and Research


Sea Surface Salinity, Aquarius - Monthly, 2011-2015

Summary:
Aquarius Sea-Surface Salinity - Weekly. 2011 - 2015. spatial resolution = 1&deg

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


Sea Surface Salinity, Aquarius - Weekly, 2011-2015


Sea Surface Salinity, Miras SMOS - 3-Day, 2010-present

Summary:
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 Temperature Anomaly, Coral Reef Watch, CoralTemp - Daily, 1985-present

Summary:
NOAA Coral Reef Watch Daily Global 5km Satellite Sea Surface Temperature Anomaly. This is a product of NOAA Coral Reef Watch Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0.

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


Sea Surface Temperature, Coral Reef Watch, CoralTemp - Daily, 1985-present

Summary:
CoralTemp 5km gap-free analysed blended sea surface temperature over the global ocean. CoralTemp is derived from three different but related 5km daily gap-free SST data sets and provides an internally consistent SST product that stretches from 1985 to present: Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature Reanalysis (1985-2002), Geo-Polar Blended Night-only Sea Surface Temperature Reanalysis (2002-2016), Geo-Polar Blended Night-only Sea Surface Temperature Near Real-Time (2017 to present).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_C)
sea_ice_fraction (1)

NOAA/NESDIS/STAR Coral Reef Watch program


Sea Surface Temperature, Coral Reef Watch, CoralTemp, v3.1 - Cumulative Mean, 1985-2009

Summary:
NOAA Coral Reef Watch Global 5km Satellite Sea Surface Temperature (CoralTemp Version 1.0) Monthly Mean Composite for January 1985. This is a product of NOAA Coral Reef Watch Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0.

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


Sea Surface Temperature, Coral Reef Watch, CoralTemp, v3.1 - Cumulative Mean, 1985-2021


Sea Surface Temperature, Coral Reef Watch, CoralTemp, v3.1 - Cumulative Mean, 2023

Summary:
NOAA Coral Reef Watch Global 5km Satellite Sea Surface Temperature (CoralTemp) Monthly Mean Composite for January 2022. This is a product of NOAA Coral Reef Watch Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite

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


Sea Surface Temperature, Coral Reef Watch, CoralTemp, v3.1 - Daily, 1985-present

Summary:
NOAA Coral Reef Watch Daily Global 5km Satellite Sea Surface Temperature (CoralTemp). CoralTemp is derived from three different but related 5km daily gap-free SST data sets and provides an internally consistent SST product that stretches from 1985 to present: Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) Sea Surface Temperature Reanalysis (1985-2002), Geo-Polar Blended Night-only Sea Surface Temperature Reanalysis (2002-2016), Geo-Polar Blended Night-only Sea Surface Temperature Near Real-Time (2017 to present).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_C)
sea_ice_fraction (1)


Sea Surface Temperature, Coral Reef Watch, CoralTemp, v3.1 - Monthly, 1985-present

Summary:
NOAA Coral Reef Watch Global 5km Satellite Sea Surface Temperature (CoralTemp Version 1.0) Monthly Mean Composite for February 2021. This is a product of NOAA Coral Reef Watch Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite, derived from CoralTemp v1.0.

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


Sea Surface Temperature, NOAA geopolar blended - 8-day, 2002-Present (2017 Reanalysis)

Summary:
8-day composite of analysed blended sea surface temperature over the global ocean using night only input data. An SST estimation scheme which combines multi-satellite retrievals 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 0.05° spatial resolution. The 8-day composites were generated from daily files by OceanWatch Central Pacific. The time coverage of each file is: date to date + 7

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_K)
sea_ice_fraction (1)

Office of Satellite Products and Operations


Sea Surface Temperature, NOAA geopolar blended - Cumulative mean 2003-2017 (2017 Reanalysis)

Summary:
Analysed blended sea surface temperature over the global ocean. An SST estimation scheme which combines multi-satellite retrievals of sea surface temperature datasets available from polar orbiters, geostationary InfraRed (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.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_K)


Sea Surface Temperature, NOAA geopolar blended - Cumulative mean 2018 (2017 Reanalysis)

Summary:
Analysed blended sea surface temperature over the global ocean using night only input data. An SST estimation scheme which combines multi-satellite retrievals of sea surface temperature datasets available from polar orbiters, geostationary InfraRed (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.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_K)


Sea Surface Temperature, NOAA geopolar blended - Daily, 2002-Present (2017 Reanalysis)

Summary:
Analyzed blended sea surface temperature over the global ocean using night only input data. An SST estimation scheme which combines multi-satellite retrievals of sea surface temperature datasets available from polar orbiters, geostationary InfraRed (IR) and microwave sensors into a single global analysis. This global SST analysis providez a daily gap-free map of the foundation sea surface temperature at 0.05Âº spatial resolution.

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


Sea Surface Temperature, NOAA geopolar blended - Monthly, 2002-Present (2017 Reanalysis)

Summary:
Monthly composite of analysed blended sea surface temperature over the global ocean using night only input data. An SST estimation scheme which combines multi-satellite retrievals 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 0.05º spatial resolution. The monthly composites were generated from daily files by OceanWatch Central Pacific

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
analysed_sst (analysed sea surface temperature, degree_K)
sea_ice_fraction (1)


Sea Surface Temperature, Pathfinder Ver 5.3, Night - 8-Day, 1981-2018

Summary:
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. spatial resolution = 0.0416667 degree

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)
wind_speed (10m wind speed, m s-1)
sea_ice_fraction (1)
l2p_flags


Sea Surface Temperature, Pathfinder Ver 5.3, Night - Monthly, 1981-2018

Summary:
This dataset contains monthly composites of night-time 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. Spatial resolution = 0.0416667 degree

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)
wind_speed (10m wind speed, m s-1)
sea_ice_fraction (1)
l2p_flags


Sea Surface Temperature, Pathfinder Ver 5.3, Night, Cumulative Mean, 1982-2017

Summary:
This netCDF file contains sea surface temperature (SST) data produced as part of the Advanced Very High Resolution Radiometer (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 Global High-Resolution Sea Surface Temperature (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. This is a cumulative mean of monthly composites from 1982 to 2017

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 Surface Temperature, Pathfinder Ver 5.3, Night, Cumulative Mean, 2018

Summary:
This netCDF file contains sea surface temperature (SST) data produced as part of the Advanced Very High Resolution Radiometer (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 Global High-Resolution Sea Surface Temperature (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. This is a cumulative mean of monthly composites for 2018

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)


TEST - CMIP6 - 0 - Grid Specification, ACCESS-ESM1-5

Summary:
ACCESS-ESM1-5 output prepared for Climate Model Intercomparison Project 6 (CMIP6)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [j][i]):
latitude (degrees_north)
longitude (degrees_east)
areacello (Grid-Cell Area for Ocean Variables, m2)

Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia


TEST - CMIP6 - 0 - Grid Specification, CESM2

Summary:
National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA data from a local source.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [nlat][nlon]):
lat (latitude, degrees_north)
lon (longitude, degrees_east)
areacello (Grid-Cell Area for Ocean Variables, m2)


TEST - CMIP6 - 1 - 3D variables (Sea surface temperature, Chlorophyll concentration, Phytoplankton biomass at surface, Integrated primary productivity, Mixed layer depth),  monthly, SSP245, ACCESS-ESM1-5

Summary:
ACCESS-ESM1-5 output prepared for Climate Model Intercomparison Project 6 (CMIP6)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][j][i]):
tos (Sea Surface Temperature, degree_C)
phycos (Sea Surface Phytoplankton Carbon Concentration, mol m-3)
chlos (Surface Mass Concentration of Total Phytoplankton Expressed as Chlorophyll in Sea Water, kg m-3)
intpp (Primary Organic Carbon Production by All Types of Phytoplankton, mol m-2 s-1)
mlotst (Ocean Mixed Layer Thickness Defined by Sigma T, m)


TEST - CMIP6 - 1 - 3D variables (Sea surface temperature, Chlorophyll concentration, Phytoplankton biomass at surface, Integrated primary productivity, Mixed layer depth), monthly, SSP370, ACCESS-ESM1-5


TEST - CMIP6 - 1 - 3D variables (Sea surface temperature, Chlorophyll concentration, Phytoplankton biomass at surface, Integrated primary productivity, Mixed layer depth), monthly, SSP585, ACCESS-ESM1-5


TEST - CMIP6 - 1 - 3D variables (Sea surface temperature, Chlorophyll concentration, Phytoplankton biomass, Zooplankton biomass at surface, Integrated primary productivity, Mixed layer depth), monthly, historical, ACCESS-ESM1-5

Summary:
ACCESS-ESM1-5 output prepared for Climate Model Intercomparison Project 6 (CMIP6)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][j][i]):
tos (Sea Surface Temperature, degree_C)
phycos (Sea Surface Phytoplankton Carbon Concentration, mol m-3)
chlos (Surface Mass Concentration of Total Phytoplankton Expressed as Chlorophyll in Sea Water, kg m-3)
zoocos (Surface Zooplankton Carbon Concentration, mol m-3)
intpp (Primary Organic Carbon Production by All Types of Phytoplankton, mol m-2 s-1)
mlotst (Ocean Mixed Layer Thickness Defined by Sigma T, m)


TEST - CMIP6 - 1 - 3D variables (Sea surface temperature, Chlorophyll concentration, Phytoplankton biomass, Zooplankton biomass at surface, Integrated primary productivity, Mixed layer depth), monthly, historical, CESM2

Summary:
National Center for Atmospheric Research, Climate and Global Dynamics Laboratory, 1850 Table Mesa Drive, Boulder, CO 80305, USA data from a local source.

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][nlat][nlon]):
tos (Sea Surface Temperature, degree_C)
chlos (Surface Mass Concentration of Total Phytoplankton expressed as Chlorophyll in Sea Water, kg m-3)
phycos (Sea Surface Phytoplankton Carbon Concentration, mol m-3)
zoocos (Surface Zooplankton Carbon Concentration, mol m-3)
intpp (Primary Organic Carbon Production by All Types of Phytoplankton, mol m-2 s-1)
mlotst (Ocean Mixed Layer Thickness Defined by Sigma T, m)


TEST - CMIP6 - 2 - 4D variables (Temperature at depth, O2, Chlorophyll concentration, Zooplankton biomass, Horizontal velocities), monthly, historical, ACCESS-ESM1-5

Summary:
ACCESS-ESM1-5 output prepared for Climate Model Intercomparison Project 6 (CMIP6)

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][depth][j][i]):
thetao (Sea Water Potential Temperature, degree_C)
o2 (Dissolved Oxygen Concentration, mol m-3)
chl (Mass Concentration of Total Phytoplankton Expressed as Chlorophyll in Sea Water, kg m-3)
zooc (Zooplankton Carbon Concentration, mol m-3)
uo (Sea Water X Velocity, m s-1)
vo (Sea Water Y Velocity, m s-1)


TEST - CMIP6 - 2 - 4D variables (Temperature at depth, O2, Chlorophyll concentration, Zooplankton biomass, Horizontal velocities), monthly, SSP245, ACCESS-ESM1-5


TEST - CMIP6 - 2 - 4D variables (Temperature at depth, O2, Chlorophyll concentration, Zooplankton biomass, Horizontal velocities), monthly, SSP370, ACCESS-ESM1-5


TEST - CMIP6 - 2 - 4D variables (Temperature at depth, O2, Chlorophyll concentration, Zooplankton biomass, Horizontal velocities), monthly, SSP585, ACCESS-ESM1-5


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - 8-day, 1997-2018. v3.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS and MODIS from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v3.5 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - 8-Day, 1997-2018. v4.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS, MODIS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS - from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.8 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - 8-Day, 1997-2019. v4.2


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - 8-Day, 1997-2021. v5.0

Summary:
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]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
OLCI_nobs_sum (Count of the number of observations from the OLCI sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 1998-2008. v4.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS, MODIS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS - from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.8 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships, mg m-3)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 1998-2008. v4.2


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 1998-2018. v4.2


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 1998-2019. v5.0

Summary:
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]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships, mg m-3)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 1998-2020. v5.0


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 2009-2018. v4.1


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 2009-2018. v4.2


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 2019. v4.2


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 2020. v5.0


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, 2021. v5.0


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, July 1998 - June 2017. v3.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS and MODIS from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v3.5 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships, mg m-3)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, July 2008 - June 2017. v3.1


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean, July 2017 - June 2018. v3.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS and MODIS from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v3.5 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships, mg m-3)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Cumulative Mean,2022. v6.0

Summary:
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]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships, mg m-3)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Monthly, 1997-2018. v3.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS and MODIS from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v3.5 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Monthly, 1997-2018. v4.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS, MODIS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS - from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.8 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using a blended combination of OCI (OC4v6 + Hu's CI), OC3 and OC5, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Monthly, 1997-2019. v4.2


ZZZ - DEPRECATED - Chlorophyll a concentration, ESA OC CCI - Monthly, 1997-2021. v5.0

Summary:
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]):
chlor_a (Chlorophyll-a concentration in seawater (not log-transformed), generated by as a blended combination of OCI, OCI2, OC2 and OCx algorithms, depending on water class memberships, mg m-3)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
OLCI_nobs_sum (Count of the number of observations from the OLCI sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
chlor_a_log10_bias (Bias of log10-transformed chlorophyll-a concentration in seawater.)
chlor_a_log10_rmsd (Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater.)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Chlorophyll a Concentration, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - Monthly, 2012-present

Summary:
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][altitude][latitude][longitude]):
chlor_a (Chlorophyll Concentration, OC3 Algorithm, mg m-3)


ZZZ - DEPRECATED - Chlorophyll a Concentration, NPP VIIRS, 750m, Pacific Islands Region - CoastWatch - Weekly, 2012-present


ZZZ - DEPRECATED - EXPERIMENTAL - Median Phytoplankton Size, North Pacific, Cumulative Mean, 2022

Summary:
Experimental product derived from NOAA CoralReefWatch CoralTemp SST and ESA OC-CCI chlorophyll a concentration using algorithm from Carolyn Barnes, Xabier Irigoien, JosÃ© A. A. De Oliveira, David Maxwell, Simon Jennings, Predicting marine phytoplankton community size structure from empirical relationships with remotely sensed variables, Journal of Plankton Research, Volume 33, Issue 1, January 2011, Pages 13-24, https://doi.org/10.1093/plankt/fbq088

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [latitude][longitude]):
MD50 (2.138*(MB50^0.355))


ZZZ - DEPRECATED - Kd490, ESA OC CCI - 8-Day, 1997-2018. v3.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS and MODIS from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v3.5 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
kd_490 (Downwelling attenuation coefficient at 490nm, derived using Lee 2005 equation and bbw from Zhang 2009 (following the SeaDAS Kd_lee algorithm), m-1)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
kd_490_bias (Bias of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
kd_490_rmsd (Root-mean-square-difference of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Kd490, ESA OC CCI - 8-Day, 1997-2018. v4.1

Summary:
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)) products.  MODIS Aqua and MERIS were band-shifted and bias-corrected to SeaWiFS 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 SeaWiFS levels, for the overlap period 2012-2013.  VIIRS, MODIS and SeaWiFS Rrs were derived from standard NASA L2 products; MERIS - from a combination of NASA's l2gen (for basic sensor geometry corrections, etc) and HYGEOS Polymer v4.8 (for atmospheric correction).  The Rrs were binned to a sinusoidal 4km level-3 grid, and later to 4km geographic projection, by Brockmann Consult's BEAM.  Derived products were generally computed with the standard SeaDAS algorithms.  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 OC4, Hu's CI and OC5, 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).

cdm_data_type = Grid
VARIABLES (all of which use the dimensions [time][latitude][longitude]):
kd_490 (Downwelling attenuation coefficient at 490nm, derived using Lee 2005 equation and bbw from Zhang 2009 (following the SeaDAS Kd_lee algorithm), m-1)
MERIS_nobs_sum (Count of the number of observations from the MERIS sensor contributing to this bin cell)
MODISA_nobs_sum (Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell)
SeaWiFS_nobs_sum (Count of the number of observations from the SeaWiFS (GAC and LAC) sensor contributing to this bin cell)
VIIRS_nobs_sum (Count of the number of observations from the VIIRS sensor contributing to this bin cell)
kd_490_bias (Bias of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
kd_490_rmsd (Root-mean-square-difference of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009, m-1)
total_nobs_sum (Count of the total number of observations contributing to this bin cell)


ZZZ - DEPRECATED - Kd490, ESA OC CCI - 8-Day, 1997-2019. v4.2