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  • kd 490 (62)
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  • number of observations (3)
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  • optical thickness of atmosphere layer due to ambient aerosol (6)
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  • surface albedo 1560nm (3)
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  • surface albedo 1630nm (1)
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  • surface altitude (5)
  • surface altitude stdev (5)
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  • surface pressure (1)
  • surface reflectance1600 interquartile mean (5)
  • surface reflectance1600 lowerquartile (5)
  • surface reflectance1600 mean (9)
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  • surface reflectance1600 sdev (9)
  • surface reflectance1600 uncertainty interquartile mean (5)
  • surface reflectance1600 uncertainty lowerquartile (5)
  • surface reflectance1600 uncertainty mean (5)
  • surface reflectance1600 uncertainty median (5)
  • surface reflectance1600 uncertainty sdev (5)
  • surface reflectance1600 uncertainty upperquartile (5)
  • surface reflectance1600 upperquartile (5)
  • surface reflectance550 interquartile mean (5)
  • surface reflectance550 lowerquartile (5)
  • surface reflectance550 mean (9)
  • surface reflectance550 median (5)
  • surface reflectance550 sdev (9)
  • surface reflectance550 uncertainty interquartile mean (5)
  • surface reflectance550 uncertainty lowerquartile (5)
  • surface reflectance550 uncertainty mean (5)
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  • surface reflectance550 uncertainty sdev (5)
  • surface reflectance550 uncertainty upperquartile (5)
  • surface reflectance550 upperquartile (5)
  • surface reflectance670 interquartile mean (5)
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  • surface reflectance670 mean (9)
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  • surface reflectance670 uncertainty mean (5)
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  • surface reflectance870 interquartile mean (5)
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  • surface temperature (2)
  • surface type number mean (9)
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  • synoptically correlated uncertainty (30)
  • t0 (9)
  • time asc (8)
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  • total aod (3)
  • total nobs (70)
  • total nobs sum (38)
  • total standard error (8)
  • uncorrelated uncertainty (30)
  • vegetation class (1)
  • vegetation class name (1)
  • view (5)
  • water class1 (62)
  • water class10 (48)
  • water class11 (48)
  • water class12 (48)
  • water class13 (48)
  • water class14 (48)
  • water class2 (62)
  • water class3 (62)
  • water class4 (62)
  • water class5 (62)
  • water class6 (62)
  • water class7 (62)
  • water class8 (62)
  • water class9 (62)
  • wb class (1)
  • wind speed (30)
  • x wind (6)
  • xc (8)
  • xch4 (12)
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  • xco2 (10)
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  • xco2 nonscat (1)
  • xco2 prior (1)
  • xco2 quality flag (10)
  • xco2 retrieved (1)
  • xco2 statistical uncertainty (2)
  • xco2 uncertainty (10)
  • y wind (6)
  • yc (8)
  •  
  • (6)
  • 1-sigma uncertainty of the retrieved column-average dry-air mole fraction of atmospheric carbon dioxide (6)
  • 1-sigma uncertainty of the retrieved column-average dry-air mole fraction of atmospheric methane (7)
  • 1-sigma uncertainty of the retrieved column-averaged dry air mole fraction of atmospheric carbon dioxide (2)
  • 1-sigma uncertainty of the retrieved column-averaged dry air mole fraction of atmospheric methane (2)
  • 10m wind speed (30)
  • Absorbing aerosol index averaged for each grid cell (3)
  • Absorption coefficient for dissolved and detrital material at 412 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Absorption coefficient for dissolved and detrital material at 443 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Absorption coefficient for dissolved and detrital material at 490 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Absorption coefficient for dissolved and detrital material at 510 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Absorption coefficient for dissolved and detrital material at 555 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Absorption coefficient for dissolved and detrital material at 670 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Aerosol optical thickness per retrieval window (6)
  • Air temperature at each level (6)
  • Altitude (6)
  • Angstrom exponent (AOD) of stratospheric aerosols for lambda=[450nm - 756nm] (1)
  • Angstrom exponent (AOD) of stratospheric aerosols for lambda=[450nm - 756nm] associated error (1)
  • Angstrom exponent (EXT) of stratospheric aerosols for lambda=[450nm - 756nm] (1)
  • Angstrom exponent (EXT) of stratospheric aerosols for lambda=[450nm - 756nm] associated error (1)
  • Apriori XCO2 model total column (1)
  • Apriori XCO2 total column (1)
  • Bias of absorption coefficient for dissolved and detrital material at 412 nm. (64)
  • Bias of absorption coefficient for dissolved and detrital material at 443 nm. (64)
  • Bias of absorption coefficient for dissolved and detrital material at 490 nm. (64)
  • Bias of absorption coefficient for dissolved and detrital material at 510 nm. (64)
  • Bias of absorption coefficient for dissolved and detrital material at 555 nm. (64)
  • Bias of absorption coefficient for dissolved and detrital material at 670 nm. (64)
  • Bias of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009 (48)
  • Bias of log10-transformed chlorophyll-a concentration in seawater. (52)
  • Bias of phytoplankton absorption coefficient at 412 nm. (64)
  • Bias of phytoplankton absorption coefficient at 443 nm. (64)
  • Bias of phytoplankton absorption coefficient at 490 nm. (64)
  • Bias of phytoplankton absorption coefficient at 510 nm. (64)
  • Bias of phytoplankton absorption coefficient at 555 nm. (64)
  • Bias of phytoplankton absorption coefficient at 670 nm. (64)
  • Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm. (52)
  • Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm. (52)
  • Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm. (52)
  • Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 510 nm. (52)
  • Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 555 nm. (52)
  • Bias of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 670 nm. (52)
  • Bias uncertainty in absorption coefficient for dissolved and detrital material at 412 nm. (14)
  • Bias uncertainty in absorption coefficient for dissolved and detrital material at 443 nm. (14)
  • Bias uncertainty in absorption coefficient for dissolved and detrital material at 490 nm. (14)
  • Bias uncertainty in absorption coefficient for dissolved and detrital material at 510 nm. (14)
  • Bias uncertainty in absorption coefficient for dissolved and detrital material at 555 nm. (14)
  • Bias uncertainty in absorption coefficient for dissolved and detrital material at 670 nm. (14)
  • Bias uncertainty in downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009 (12)
  • Bias uncertainty in downwelling attenuation coefficient at 490nm (2)
  • Bias uncertainty in phytoplankton absorption coefficient at 412 nm. (14)
  • Bias uncertainty in phytoplankton absorption coefficient at 443 nm. (14)
  • Bias uncertainty in phytoplankton absorption coefficient at 490 nm. (14)
  • Bias uncertainty in phytoplankton absorption coefficient at 510 nm. (14)
  • Bias uncertainty in phytoplankton absorption coefficient at 555 nm. (14)
  • Bias uncertainty in phytoplankton absorption coefficient at 670 nm. (14)
  • Bias uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm. (14)
  • Bias uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm. (14)
  • Bias uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm. (14)
  • Bias uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 510 nm. (14)
  • Bias uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 555 nm. (14)
  • Bias uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 670 nm. (14)
  • Chi-squared (8)
  • Chlorophyll-a concentration in seawater (not log-transformed), generated by SeaDAS using OC4v6 for SeaWiFS (52)
  • Chlorophyll-a concentration in seawater, generated by SeaDAS using OC4v6 for SeaWiFS (14)
  • Column number of the pixel in the original grid (1)
  • Count of the number of observations from the MERIS sensor contributing to this bin cell (108)
  • Count of the number of observations from the MODIS (Aqua) sensor contributing to this bin cell (88)
  • Count of the number of observations from the MODIS sensor contributing to this bin cell (20)
  • Count of the number of observations from the SeaWiFS sensor contributing to this bin cell (108)
  • Count of the total number of observations contributing to this bin cell (108)
  • Day / Night Flag (3)
  • Day(100) or Night(110) Flag (6)
  • Downwelling attenuation coefficient at 490nm, derived using Lee 2005 equation and bbw from Zhang 2009 (following the SeaDAS Kd lee algorithm) (62)
  • Dry airmass per layer (8)
  • ECMWF H2O vertical column density (2)
  • Flag (9)
  • Frequency Band (6)
  • Frequency Band Identification (3)
  • Geographical distribution of mean sea level amplitude (2)
  • Geographical distribution of mean sea level phase (2)
  • Geographical distribution of mean sea level trends (2)
  • Geographical distribution of mean sea level trends errors (2)
  • Global mean sea level variations (2)
  • H2O total column (4)
  • H2O total column at 1593 nm (2)
  • H2O total column at 1629 nm (2)
  • H2O total column at 2042 nm (2)
  • Height (2)
  • Indice of the pixel in the vector of observations (1)
  • Instrument view (5)
  • Intensity offset in the O2A-band (6)
  • L2P flags (30)
  • LC map confidence level based on algorithm performance (1)
  • LC map processed area flag (1)
  • LC pixel type mask (1)
  • Land cover class defined in LCCS (1)
  • Latitude (3)
  • Latitude cell boundaries (31)
  • Latitude of the grid center (4)
  • Latitudes of the centre of the grid cells (3)
  • Level 1B name (6)
  • Line number of the pixel in the original grid (1)
  • Log transform RMS uncertainty in chlorophyll-a concentration in seawater. (14)
  • Log transform bias uncertainty in chlorophyll-a concentration in seawater. (14)
  • Longitude (3)
  • Longitude cell boundaries (31)
  • Longitude of the grid center (4)
  • Longitudes of the centre of the grid cells (3)
  • Mean Aerosol Altitude (3)
  • Mean Effective Aerosol Optical Thickness at 550nm over ocean - Best solution (3)
  • Mean Effective Aerosol Optical Thickness at 865nm over ocean - Best solution (3)
  • Mean Effective Radius over ocean - Best solution (3)
  • Mean Fine Mode Aerosol Optical Thickness at 550nm over ocean - Best solution (3)
  • Mean Fine Mode Aerosol Optical Thickness at 865nm over ocean - Best solution (3)
  • Mean Total Ozone Column in Dobson Units (4)
  • Mean of L2 Uncertainty on AOT at 670 nm (4)
  • Mean of L2 uncertainty on AOT at 1600 nm (4)
  • Mean of L2 uncertainty on AOT at 550 nm (4)
  • Mean of L2 uncertainty on AOT at 870 nm (4)
  • Mean of normalised water class 0 membership over the compositing period (12)
  • Mean of normalised water class 1 membership over the compositing period (19)
  • Mean of normalised water class 2 membership over the compositing period (19)
  • Mean of normalised water class 3 membership over the compositing period (19)
  • Mean of normalised water class 4 membership over the compositing period (19)
  • Mean of normalised water class 5 membership over the compositing period (19)
  • Mean of normalised water class 6 membership over the compositing period (19)
  • Mean of normalised water class 7 membership over the compositing period (19)
  • Mean of normalised water class 8 membership over the compositing period (19)
  • Mean of normalised water class 9 membership over the compositing period (19)
  • Non-scattering retrieved XCH4 column (1)
  • Non-scattering retrieved XCO2 column (1)
  • Normalised water class 1 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 1 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 10 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 11 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 12 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 13 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 14 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 2 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 2 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 3 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 3 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 4 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 4 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 5 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 5 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 6 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 6 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 7 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 7 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 8 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 8 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • Normalised water class 9 membership, as determined by Tim Moore's fuzzy classifier algorithm (7)
  • Normalised water class 9 membership, as determined by the fuzzy classification algorithm of Tim Moore (2009) and custom-developed classes to best represent the CCI merged data (36)
  • North-East pixel corner latitude (1)
  • North-East pixel corner longitude (1)
  • North-West pixel corner latitude (1)
  • North-West pixel corner longitude (1)
  • Not bias-corrected XCH4 column (3)
  • Not bias-corrected XCO2 column (1)
  • Number of observations for each grid cell (3)
  • Number of observations used to calculate the mean stratospheric aerosol extinction (550nm) (1)
  • Number of observations used to calculate the mean stratospheric aerosol optical depth (550nm) (1)
  • Observation Timestamp (9)
  • Particulate backscattering coefficient for dissolved and detrital material at 412 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (64)
  • Particulate backscattering coefficient for dissolved and detrital material at 443 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (64)
  • Particulate backscattering coefficient for dissolved and detrital material at 490 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (64)
  • Particulate backscattering coefficient for dissolved and detrital material at 510 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (64)
  • Particulate backscattering coefficient for dissolved and detrital material at 555 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (64)
  • Particulate backscattering coefficient for dissolved and detrital material at 670 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (64)
  • Percent of Saturation Soil Moisture (3)
  • Percent of Saturation Soil Moisture Uncertainty (3)
  • Period of signal (2)
  • Phytoplankton absorption coefficient at 412 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Phytoplankton absorption coefficient at 443 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Phytoplankton absorption coefficient at 490 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Phytoplankton absorption coefficient at 510 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Phytoplankton absorption coefficient at 555 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Phytoplankton absorption coefficient at 670 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Polar Stratospheric Clouds (PSC) occurrence frequency (1)
  • Pressure at the bottom of the atmosphere. (1)
  • RMS uncertainty in absorption coefficient for dissolved and detrital material at 412 nm. (14)
  • RMS uncertainty in absorption coefficient for dissolved and detrital material at 443 nm. (14)
  • RMS uncertainty in absorption coefficient for dissolved and detrital material at 490 nm. (14)
  • RMS uncertainty in absorption coefficient for dissolved and detrital material at 510 nm. (14)
  • RMS uncertainty in absorption coefficient for dissolved and detrital material at 555 nm. (14)
  • RMS uncertainty in absorption coefficient for dissolved and detrital material at 670 nm. (14)
  • RMS uncertainty in downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009 (12)
  • RMS uncertainty in downwelling attenuation coefficient at 490nm (2)
  • RMS uncertainty in phytoplankton absorption coefficient at 412 nm. (14)
  • RMS uncertainty in phytoplankton absorption coefficient at 443 nm. (14)
  • RMS uncertainty in phytoplankton absorption coefficient at 490 nm. (14)
  • RMS uncertainty in phytoplankton absorption coefficient at 510 nm. (14)
  • RMS uncertainty in phytoplankton absorption coefficient at 555 nm. (14)
  • RMS uncertainty in phytoplankton absorption coefficient at 670 nm. (14)
  • RMS uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm. (14)
  • RMS uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm. (14)
  • RMS uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm. (14)
  • RMS uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 510 nm. (14)
  • RMS uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 555 nm. (14)
  • RMS uncertainty in sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 670 nm. (14)
  • Raw retrieved XCH4 column (2)
  • Raw retrieved XCO2 column (2)
  • Raw uncertainty on the XCH4 total column (2)
  • Raw uncertainty on the XCO2 total column (2)
  • Retrieval quality flag (2)
  • Retrieved aerosol peak height (4)
  • Retrieved aerosol total column (4)
  • Retrieved size parameter of the aerosol distribution (4)
  • Root-mean-square-difference of absorption coefficient for dissolved and detrital material at 412 nm. (64)
  • Root-mean-square-difference of absorption coefficient for dissolved and detrital material at 443 nm. (64)
  • Root-mean-square-difference of absorption coefficient for dissolved and detrital material at 490 nm. (64)
  • Root-mean-square-difference of absorption coefficient for dissolved and detrital material at 510 nm. (64)
  • Root-mean-square-difference of absorption coefficient for dissolved and detrital material at 555 nm. (64)
  • Root-mean-square-difference of absorption coefficient for dissolved and detrital material at 670 nm. (64)
  • Root-mean-square-difference of downwelling attenuation coefficient at 490 nm derived using Lee 2005 equation and bbw from Zhang 2009 (48)
  • Root-mean-square-difference of log10-transformed chlorophyll-a concentration in seawater. (52)
  • Root-mean-square-difference of phytoplankton absorption coefficient at 412 nm. (64)
  • Root-mean-square-difference of phytoplankton absorption coefficient at 443 nm. (64)
  • Root-mean-square-difference of phytoplankton absorption coefficient at 490 nm. (64)
  • Root-mean-square-difference of phytoplankton absorption coefficient at 510 nm. (64)
  • Root-mean-square-difference of phytoplankton absorption coefficient at 555 nm. (64)
  • Root-mean-square-difference of phytoplankton absorption coefficient at 670 nm. (64)
  • Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm. (52)
  • Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm. (52)
  • Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm. (52)
  • Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 510 nm. (52)
  • Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 555 nm. (52)
  • Root-mean-square-difference of sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 670 nm. (52)
  • SSES bias estimate (30)
  • SSES standard deviation (30)
  • Satellite Mode (3)
  • Satellite Mode (6)
  • Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 412 nm. (66)
  • Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 443 nm. (66)
  • Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 490 nm. (66)
  • Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 510 nm. (66)
  • Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 555 nm. (66)
  • Sea surface reflectance defined as the ratio of water-leaving radiance to surface irradiance at 670 nm. (66)
  • Sensor (9)
  • Sensor zenith angle (13)
  • Solar zenith angle (8)
  • Solar zenith angle averaged for each grid cell (3)
  • South-East pixel corner latitude (1)
  • South-East pixel corner longitude (1)
  • South-West pixel corner latitude (1)
  • South-West pixel corner longitude (1)
  • Standard Deviation of Aerosol Altitude (3)
  • Standard Deviation of Effective Aerosol Optical Thickness at 550nm over ocean - Best solution (3)
  • Standard Deviation of Effective Aerosol Optical Thickness at 865nm over ocean - Best solution (3)
  • Standard Deviation of Effective Radius over ocean - Best solution (3)
  • Standard Deviation of Fine Mode Aerosol Optical Thickness at 550nm over ocean - Best solution (3)
  • Standard Deviation of Fine Mode Aerosol Optical Thickness at 865nm over ocean - Best solution (3)
  • Standard Deviation of the Mean Total Ozone Column in Dobson Units (4)
  • Standard Error of the Mean Total Ozone Column in Dobson Units (4)
  • Standard deviation of the surface elevation (6)
  • Standard error on global mean sea level variations tendency (2)
  • Statistical uncertainty on the XCH4 total column (2)
  • Statistical uncertainty on the XCO2 total column (2)
  • Surface albedo at 1593 nm (6)
  • Surface albedo at 1629 nm (6)
  • Surface albedo at 2042 nm (6)
  • Surface albedo at 758 nm (6)
  • Surface temperature (2)
  • Tendency of global mean sea level variations (2)
  • The number of measurements use to derive the Mean Total Ozone Column in Dobson Units (4)
  • Time and depth adjustment uncertainty (30)
  • Time cell boundaries (31)
  • Total absorption coefficient at 412 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Total absorption coefficient at 443 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Total absorption coefficient at 490 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Total absorption coefficient at 510 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Total absorption coefficient at 555 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Total absorption coefficient at 670 nm as derived using the QAA model, generated by SeaDAS for SeaWiFS (78)
  • Total uncertainty in sea surface temperature depth (30)
  • Uncertainty from errors likely to be correlated over large scales (30)
  • Uncertainty from errors likely to be correlated over synoptic scales (30)
  • Uncertainty from errors unlikely to be correlated between SSTs (30)
  • Volumetric Soil Moisture (6)
  • Volumetric Soil Moisture Uncertainty (6)
  • a priori dry air mole fraction profile of atmospheric carbon dioxide (2)
  • a priori dry air mole fraction profile of atmospheric methane (2)
  • a priori dry-air mole fraction profile of atmospheric carbon dioxide (7)
  • a priori dry-air mole fraction profile of atmospheric carbondioxide (1)
  • a priori dry-air mole fraction profile of atmospheric methane (5)
  • a priori profile of dry-air mole fraction of atmospheric methane (ppb) (2)
  • absorbing AOD (4)
  • aerosol optical thickness at 1600 nm (4)
  • aerosol optical thickness at 550 nm (4)
  • aerosol optical thickness at 670 nm (4)
  • aerosol optical thickness at 870 nm (4)
  • aerosol type (5)
  • air pressure at layer boundaries (1)
  • air temperature apriori (5)
  • algorithm uncertainty (one standard deviation) of concentration of sea ice (8)
  • altitude (5)
  • analysed sea surface temperature (2)
  • angstrom exponent computed on AOD550nm and AOD870nm (4)
  • aod type1 (3)
  • aod type2 (3)
  • burned area in vegetation class (1)
  • cer histogram bin border values (6)
  • cer histogram bin centres (6)
  • ch4 profile apriori (3)
  • cirrus (3)
  • cloud abedo1 histogram bin centres (6)
  • cloud albedo at 0.6 um (6)
  • cloud albedo at 0.6 um correlated uncertainty (6)
  • cloud albedo at 0.6 um propagated uncertainty (6)
  • cloud albedo at 0.6 um standard deviation (6)
  • cloud albedo at 0.6 um uncertainty (6)
  • cloud albedo at 0.8 um (5)
  • cloud albedo at 0.8 um correlated uncertainty (5)
  • cloud albedo at 0.8 um propagated uncertainty (5)
  • cloud albedo at 0.8 um standard deviation (5)
  • cloud albedo at 0.8 um uncertainty (5)
  • cloud albedo at 1.6 um (1)
  • cloud albedo at 1.6 um correlated uncertainty (1)
  • cloud albedo at 1.6 um propagated uncertainty (1)
  • cloud albedo at 1.6 um standard deviation (1)
  • cloud albedo at 1.6 um uncertainty (1)
  • cloud albedo1 histogram bin border values (6)
  • cloud albedo2 histogram bin border values (6)
  • cloud albedo2 histogram bin centres (6)
  • cloud effective emissivity at 10.8 um (5)
  • cloud effective emissivity at 10.8 um correlated uncertainty (5)
  • cloud effective emissivity at 10.8 um propagated uncertainty (5)
  • cloud effective emissivity at 10.8 um standard deviation (5)
  • cloud effective emissivity at 10.8 um uncertainty (5)
  • cloud effective radius (6)
  • cloud effective radius correlated uncertainty (6)
  • cloud effective radius propagated uncertainty (6)
  • cloud effective radius standard deviation (6)
  • cloud effective radius uncertainty (6)
  • cloud fraction (16)
  • cloud fraction correlated uncertainty (6)
  • cloud fraction day (6)
  • cloud fraction high (10)
  • cloud fraction low (10)
  • cloud fraction middle (10)
  • cloud fraction night (6)
  • cloud fraction propagated uncertainty (6)
  • cloud fraction standard deviation (6)
  • cloud fraction std (10)
  • cloud fraction twilight (6)
  • cloud fraction uncertainty (16)
  • cloud fraction uncertainty std (10)
  • cloud fraction wm (10)
  • cloud fraction wstd (10)
  • cloud ice water path (16)
  • cloud ice water path correlated uncertainty (6)
  • cloud ice water path propagated uncertainty (6)
  • cloud ice water path standard deviation (6)
  • cloud ice water path std (10)
  • cloud ice water path uncertainty (16)
  • cloud ice water path uncertainty std (10)
  • cloud ice water path wm (10)
  • cloud ice water path wstd (10)
  • cloud liquid water path (16)
  • cloud liquid water path correlated uncertainty (6)
  • cloud liquid water path propagated uncertainty (6)
  • cloud liquid water path standard deviation (6)
  • cloud liquid water path std (10)
  • cloud liquid water path uncertainty (16)
  • cloud liquid water path uncertainty std (10)
  • cloud liquid water path wm (10)
  • cloud liquid water path wstd (10)
  • cloud mask flag ascending (8)
  • cloud mask flag descending (8)
  • cloud optical thickness (16)
  • cloud optical thickness ascending (8)
  • cloud optical thickness correlated uncertainty (6)
  • cloud optical thickness descending (8)
  • cloud optical thickness logarithmic (10)
  • cloud optical thickness logarithmically averaged (6)
  • cloud optical thickness median (10)
  • cloud optical thickness propagated uncertainty (6)
  • cloud optical thickness standard deviation (6)
  • cloud optical thickness std (10)
  • cloud optical thickness uncertainty (16)
  • cloud optical thickness uncertainty ascending (8)
  • cloud optical thickness uncertainty descending (8)
  • cloud optical thickness uncertainty std (10)
  • cloud optical thickness wm (10)
  • cloud optical thickness wstd (10)
  • cloud phase flag ascending (8)
  • cloud phase flag descending (8)
  • cloud top height (16)
  • cloud top height ascending (8)
  • cloud top height correlated uncertainty (6)
  • cloud top height descending (8)
  • cloud top height median (10)
  • cloud top height propagated uncertainty (6)
  • cloud top height standard deviation (6)
  • cloud top height std (10)
  • cloud top height uncertainty (16)
  • cloud top height uncertainty ascending (8)
  • cloud top height uncertainty descending (8)
  • cloud top height uncertainty std (10)
  • cloud top height wm (10)
  • cloud top height wstd (10)
  • cloud top pressure (16)
  • cloud top pressure ascending (8)
  • cloud top pressure correlated uncertainty (6)
  • cloud top pressure descending (8)
  • cloud top pressure logarithmic (10)
  • cloud top pressure logarithmically averaged (6)
  • cloud top pressure logarithmiccally averaged (1)
  • cloud top pressure median (10)
  • cloud top pressure propagated uncertainty (6)
  • cloud top pressure standard deviation (6)
  • cloud top pressure std (10)
  • cloud top pressure uncertainty (16)
  • cloud top pressure uncertainty ascending (8)
  • cloud top pressure uncertainty descending (8)
  • cloud top pressure uncertainty std (10)
  • cloud top pressure wm (10)
  • cloud top pressure wstd (10)
  • cloud top temperature (16)
  • cloud top temperature ascending (8)
  • cloud top temperature correlated uncertainty (6)
  • cloud top temperature descending (8)
  • cloud top temperature median (10)
  • cloud top temperature propagated uncertainty (6)
  • cloud top temperature standard deviation (6)
  • cloud top temperature std (10)
  • cloud top temperature uncertainty (16)
  • cloud top temperature uncertainty ascending (8)
  • cloud top temperature uncertainty descending (8)
  • cloud top temperature uncertainty std (10)
  • cloud top temperature wm (10)
  • cloud top temperature wstd (10)
  • cloud water path (10)
  • cloud water path ascending (8)
  • cloud water path descending (8)
  • cloud water path median (10)
  • cloud water path std (10)
  • cloud water path uncertainty (10)
  • cloud water path uncertainty ascending (8)
  • cloud water path uncertainty descending (8)
  • cloud water path uncertainty std (10)
  • cloud water path wm (10)
  • cloud water path wstd (10)
  • co2 profile apriori (5)
  • column-average dry-air mole fraction of atmospheric carbon dioxide (6)
  • column-average dry-air mole fraction of atmospheric carbon dioxide (ppm) as used in XCH4 proxy (1)
  • column-average dry-air mole fraction of atmospheric methane (5)
  • column-average dry-air mole fraction of atmospheric methane (ppb) (2)
  • column-average dry-air mole fraction of atmospheric methane (ppb), includes tentative bias correction using H2O columns (2)
  • column-averaged dry air mole fraction of atmospheric carbon dioxide (2)
  • column-averaged dry air mole fraction of atmospheric methane (2)
  • concentration of sea ice (4)
  • concentration of sea ice (values retrieved outside [0% - 100%] validity range) (4)
  • corner latitudes (4)
  • corner longitudes (4)
  • cot histogram bin border values (6)
  • cot histogram bin centres (6)
  • cot histogram bins (7)
  • cot histogram border values (7)
  • cot ctp hist2d (7)
  • ctp histogram bin border values (6)
  • ctp histogram bin centres (6)
  • ctp histogram bins (7)
  • ctp histogram border values (7)
  • ctt histogram bin border values (6)
  • ctt histogram bin centres (6)
  • cwp histogram bin border values (6)
  • cwp histogram bin centres (6)
  • daytime fraction of liquid water clouds (6)
  • daytime fraction of liquid water clouds standard deviation (6)
  • effective radius (10)
  • effective radius ascending (8)
  • effective radius descending (8)
  • effective radius median (10)
  • effective radius std (10)
  • effective radius uncertainty (10)
  • effective radius uncertainty ascending (8)
  • effective radius uncertainty descending (8)
  • effective radius uncertainty std (10)
  • effective radius wm (10)
  • effective radius wstd (10)
  • error in the weighted average of the number density (#molecules/cm3) (1)
  • error in the weighted average of the partial ozone columns (DU/layer) (1)
  • error in the weighted average of the volume mixing ratio (ppmv) (1)
  • estimated error standard deviation of analysed sst (2)
  • exposure id (6)
  • exposure id (5)
  • fine mode AOD (4)
  • flag for land / ocean soundings (6)
  • flag for normal / sunglint soundings (6)
  • fraction of liquid water clouds (16)
  • fraction of liquid water clouds standard deviation (6)
  • fraction of liquid water clouds std (10)
  • fraction of observed area (1)
  • fully filtered concentration of sea ice using atmospheric correction of brightness temperatures and open water filters (4)
  • gain (11)
  • grid box mean of cloud ice water path (6)
  • grid box mean of cloud liquid water path (6)
  • grid eastward wind (6)
  • grid northward wind (6)
  • ground scene number (4)
  • h2o profile apriori (5)
  • high level cloud fraction (6)
  • histogram of cloud albedo at 0.6 um (6)
  • histogram of cloud albedo at 0.8 um (5)
  • histogram of cloud albedo at 1.6 um (1)
  • histogram of cloud effective radius (6)
  • histogram of cloud optical thickness (6)
  • histogram of cloud top pressure (6)
  • histogram of cloud top temperature (6)
  • histogram of cloud water path (6)
  • ice cloud optical thickness (1)
  • ice cloud optical thickness logarithmic (1)
  • ice cloud optical thickness median (1)
  • ice cloud optical thickness std (1)
  • ice cloud optical thickness uncertainty (1)
  • ice cloud optical thickness uncertainty std (1)
  • ice cloud optical thickness wm (1)
  • ice cloud optical thickness wstd (1)
  • ice effective radius (1)
  • ice effective radius median (1)
  • ice effective radius std (1)
  • ice effective radius uncertainty (1)
  • ice effective radius uncertainty std (1)
  • ice effective radius wm (1)
  • ice effective radius wstd (1)
  • ice water cloud albedo at 0.6 um (5)
  • ice water cloud albedo at 0.6 um standard deviation (5)
  • ice water cloud albedo at 0.6 um uncertainty (5)
  • ice water cloud albedo at 0.8 um (5)
  • ice water cloud albedo at 0.8 um standard deviation (5)
  • ice water cloud albedo at 0.8 um uncertainty (5)
  • ice water cloud effective radius (6)
  • ice water cloud effective radius correlated uncertainty (6)
  • ice water cloud effective radius propagated uncertainty (6)
  • ice water cloud effective radius standard deviation (6)
  • ice water cloud effective radius uncertainty (6)
  • ice water cloud optical thickness (6)
  • ice water cloud optical thickness correlated uncertainty (6)
  • ice water cloud optical thickness propagated uncertainty (6)
  • ice water cloud optical thickness standard deviation (6)
  • ice water cloud optical thickness uncertainty (6)
  • inter-quartile mean Uncertainty on surface reflectance at 1600 nm (5)
  • inter-quartile mean Uncertainty on surface reflectance at 550 nm (5)
  • inter-quartile mean Uncertainty on surface reflectance at 670 nm (5)
  • inter-quartile mean Uncertainty on surface reflectance at 870 nm (5)
  • inter-quartile mean aerosol Angstrom exponent between 550 and 870 nm (5)
  • inter-quartile mean aerosol absorption optical thickness at 550 nm (5)
  • inter-quartile mean aerosol effective radius (5)
  • inter-quartile mean aerosol optical thickness at 1600 nm (5)
  • inter-quartile mean aerosol optical thickness at 550 nm (5)
  • inter-quartile mean aerosol optical thickness at 670 nm (5)
  • inter-quartile mean aerosol optical thickness at 870 nm (5)
  • inter-quartile mean dust aerosol optical thickness at 550 nm (5)
  • inter-quartile mean fine-mode aerosol optical thickness at 550 nm (5)
  • inter-quartile mean surface bihemispherical reflectance at 1600 nm (5)
  • inter-quartile mean surface bihemispherical reflectance at 550 nm (5)
  • inter-quartile mean surface bihemispherical reflectance at 670 nm (5)
  • inter-quartile mean surface bihemispherical reflectance at 870 nm (5)
  • inter-quartile mean uncertainty on AOT at 550 nm (5)
  • inter-quartile mean uncertainty on AOT at 870 nm (5)
  • inter-quartile mean uncertainty on aerosol effective radius (5)
  • joint histogram of cloud optical thickness and cloud top pressure (6)
  • joint histogram of cloud optical thickness and cloud top pressure 2 (1)
  • l2 processor id (4)
  • latitude (32)
  • latitude grid cell lower boundary (5)
  • latitude grid cell upper boundary (5)
  • liquid water cloud albedo at 0.6 um (5)
  • liquid water cloud albedo at 0.6 um standard deviation (5)
  • liquid water cloud albedo at 0.6 um uncertainty (5)
  • liquid water cloud albedo at 0.8 um (5)
  • liquid water cloud albedo at 0.8 um standard deviation (5)
  • liquid water cloud albedo at 0.8 um uncertainty (5)
  • liquid water cloud effective radius (6)
  • liquid water cloud effective radius correlated uncertainty (6)
  • liquid water cloud effective radius propagated uncertainty (6)
  • liquid water cloud effective radius standard deviation (6)
  • liquid water cloud effective radius uncertainty (6)
  • liquid water cloud optical thickness (6)
  • liquid water cloud optical thickness correlated uncertainty (6)
  • liquid water cloud optical thickness propagated uncertainty (6)
  • liquid water cloud optical thickness standard deviation (6)
  • liquid water cloud optical thickness uncertainty (6)
  • longitude (32)
  • longitude grid cell lower boundary (5)
  • longitude grid cell upper boundary (5)
  • low level cloud fraction (6)
  • lower quartile Uncertainty on surface reflectance at 1600 nm (5)
  • lower quartile Uncertainty on surface reflectance at 550 nm (5)
  • lower quartile Uncertainty on surface reflectance at 670 nm (5)
  • lower quartile Uncertainty on surface reflectance at 870 nm (5)
  • lower quartile aerosol Angstrom exponent between 550 and 870 nm (5)
  • lower quartile aerosol absorption optical thickness at 550 nm (5)
  • lower quartile aerosol effective radius (5)
  • lower quartile aerosol optical thickness at 1600 nm (5)
  • lower quartile aerosol optical thickness at 550 nm (5)
  • lower quartile aerosol optical thickness at 670 nm (5)
  • lower quartile aerosol optical thickness at 870 nm (5)
  • lower quartile dust aerosol optical thickness at 550 nm (5)
  • lower quartile fine-mode aerosol optical thickness at 550 nm (5)
  • lower quartile surface bihemispherical reflectance at 1600 nm (5)
  • lower quartile surface bihemispherical reflectance at 550 nm (5)
  • lower quartile surface bihemispherical reflectance at 670 nm (5)
  • lower quartile surface bihemispherical reflectance at 870 nm (5)
  • lower quartile uncertainty on AOT at 550 nm (5)
  • lower quartile uncertainty on AOT at 870 nm (5)
  • lower quartile uncertainty on aerosol effective radius (5)
  • maximum L2 Uncertainty on AOT at 670 nm (4)
  • maximum L2 uncertainty on AOT at 1600 nm (4)
  • maximum L2 uncertainty on AOT at 550 nm (4)
  • maximum L2 uncertainty on AOT at 870 nm (4)
  • mean Cloud fraction (5)
  • mean Cost function at solution (5)
  • mean Land / sea flag (5)
  • mean Relative Azimuth angle (5)
  • mean Retrieval iterations (5)
  • mean Satellite zenith angle (5)
  • mean Solar zenith angle (5)
  • mean TAI70 time (5)
  • mean Uncertainty on surface reflectance at 1600 nm (5)
  • mean Uncertainty on surface reflectance at 550 nm (5)
  • mean Uncertainty on surface reflectance at 670 nm (5)
  • mean Uncertainty on surface reflectance at 870 nm (5)
  • mean aerosol Angstrom exponent between 550 and 870 nm (5)
  • mean aerosol absorption optical thickness at 550 nm (5)
  • mean aerosol effective radius (5)
  • mean aerosol optical thickness at 1600 nm (5)
  • mean aerosol optical thickness at 550 nm (5)
  • mean aerosol optical thickness at 670 nm (5)
  • mean aerosol optical thickness at 870 nm (5)
  • mean bidirectional surface reflectance (nadir) (4)
  • mean dust aerosol optical thickness at 550 nm (5)
  • mean fine-mode aerosol optical thickness at 550 nm (5)
  • mean fraction of cloud flagged pixels in 10km bin (4)
  • mean land fraction (4)
  • mean surface bihemispherical reflectance at 1600 nm (5)
  • mean surface bihemispherical reflectance at 550 nm (5)
  • mean surface bihemispherical reflectance at 670 nm (5)
  • mean surface bihemispherical reflectance at 870 nm (5)
  • mean uncertainty on AOT at 550 nm (5)
  • mean uncertainty on AOT at 870 nm (5)
  • mean uncertainty on aerosol effective radius (5)
  • median Uncertainty on surface reflectance at 1600 nm (5)
  • median Uncertainty on surface reflectance at 550 nm (5)
  • median Uncertainty on surface reflectance at 670 nm (5)
  • median Uncertainty on surface reflectance at 870 nm (5)
  • median aerosol Angstrom exponent between 550 and 870 nm (5)
  • median aerosol absorption optical thickness at 550 nm (5)
  • median aerosol effective radius (5)
  • median aerosol optical thickness at 1600 nm (5)
  • median aerosol optical thickness at 550 nm (5)
  • median aerosol optical thickness at 670 nm (5)
  • median aerosol optical thickness at 870 nm (5)
  • median dust aerosol optical thickness at 550 nm (5)
  • median fine-mode aerosol optical thickness at 550 nm (5)
  • median surface bihemispherical reflectance at 1600 nm (5)
  • median surface bihemispherical reflectance at 550 nm (5)
  • median surface bihemispherical reflectance at 670 nm (5)
  • median surface bihemispherical reflectance at 870 nm (5)
  • median tropopause height used for the integration in the stratosphere (1)
  • median uncertainty on AOT at 550 nm (5)
  • median uncertainty on AOT at 870 nm (5)
  • median uncertainty on aerosol effective radius (5)
  • mid level cloud fraction (6)
  • minimum L2 Uncertainty on AOT at 670 nm (4)
  • minimum L2 uncertainty on AOT at 1600 nm (4)
  • minimum L2 uncertainty on AOT at 550 nm (4)
  • minimum L2 uncertainty on AOT at 870 nm (4)
  • model level number == layer number, starting at 1 (1)
  • model xco2 (1)
  • model xco2 median diff (1)
  • model xco2 range (1)
  • nn result ascending (8)
  • nn result descending (8)
  • non-spherical dust AOD (4)
  • normalized column averaging kernel (13)
  • number of burn patches (1)
  • number of clear daytime observations (6)