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NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2A)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SURFACE (RADIATIVE) FLUX↗

NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-MODIS_Edition2B)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

SURFACE (RADIATIVE) FLUX↗

NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM1-MODIS_Edition2A)

ICE WATER PATH↗

NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=1999-07-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

LONGWAVE UNFILTERED RADIANCE↗

NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Edition1B)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

LONGWAVE UNFILTERED RADIANCE↗

NASA NTRSDate not supplied

CERES Single Satellite Footprint, TOA and Surface Fluxes, Clouds (SSF) data in HDF (CER_SSF_Aqua-FM4-MODIS_Ed2A-NoSW)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

LIQUID WATER PATH↗

NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_Terra-FM2-MODIS_Edition2B)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-01-01] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

ICE WATER PATH↗

NASA NTRSDate not supplied

CERES Single Scanner Satellite Footprint, TOA, Surface Fluxes and Clouds (SSF) data in HDF (CER_SSF_TRMM-PFM-VIRS_Edition2A)

The Single Scanner Footprint TOA/Surface Fluxes and Clouds (SSF) product contains one hour of instantaneous Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The SSF combines instantaneous CERES data with scene information from a higher-resolution imager such as Visible/Infrared Scanner (VIRS) on TRMM or Moderate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Scene identification and cloud properties are defined at the higher imager resolution and these data are averaged over the larger CERES footprint. For each CERES footprint, the SSF contains the number of cloud layers and for each layer the cloud amount, height, temperature, pressure, optical depth, emissivity, ice and liquid water path, and water particle size. The SSF also contains the CERES filtered radiances for the total, shortwave (SW), and window (WN) channels and the unfiltered SW, longwave (LW), and WN radiances. The SW, LW, and WN radiances at spacecraft altitude are converted to Top-of-the-Atmosphere (TOA) fluxes based on the imager defined scene. These TOA fluxes are used to estimate surface fluxes. Only footprints with adequate imager coverage are included on CER_SSF_TRMM-PFM-VIRS_Subset_Edition1the SSF which is much less than the full set of footprints on the CERES ES-8 product. The following CERES SSF data sets are currently available: CER_SSF_TRMM-PFM-VIRS_Edition1 CER_SSF_TRMM-PFM-VIRS_Subset_Edition1 CER_SSF_TRMM-PFM-VIRS_Edition2A CER_SSF_TRMM-SIM-VIRS_Edition2_VIRSonly CER_SSF_TRMM-PFM-VIRS_Edition2A-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B-TransOps CER_SSF_TRMM-PFM-VIRS_Edition2B CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition1A CER_SSF_Terra-FM1-MODIS_Edition2A CER_SSF_Terra-FM2-MODIS_Edition2A CER_SSF_Terra-FM1-MODIS_Edition2B CER_SSF_Terra-FM2-MODIS_Edition2B CER_SSF_Aqua-FM4-MODIS_Beta1 CER_SSF_Aqua-FM3-MODIS_Beta2 CER_SSF_Aqua-FM4-MODIS_Beta2. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2000-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

ICE WATER PATH↗

NASA NTRS1993

A Regional Analysis of Cloudy Mean Spherical Albedo over the Marine Stratocumulus Region and the Tropical Atlantic Ocean

Since clouds are the largest variable in Earth's radiation budget, it is critical to determine both the spatial and temporal characteristics of their radiative properties. This study examines the relationships between cloud properties and cloud fraction in order to supplement grid scale parameterizations. The satellite data used in this study is from three hourly ISCCP (International Satellite Cloud Climatology Project) and monthly ERBE (Earth Radiation Budget Experiment) data on a 2.50 x 2.50 latitude-longitude grid. Mean cloud spherical albedo, the mean optical depth distribution and cloud fraction are examined and compared off the coast of California and the mid-tropical Atlantic for July 1987 and 1988. Individual grid boxes and spatial averages over several grid boxes are correlated to Coakleys (1991) theory of reflection for uniform and broken layered cloud and to Kedem, et al.(1990) findings that rainfall volume and fractional area of rain in convective systems is linear. Kedem's hypothesis can be expressed in terms of cloud properties. That is, the total volume of liquid in a box is a linear function of cloud fraction. Results for the marine stratocumulus regime indicate that albedo is often invariant for cloud fractions of 20% to 80%. Coakley's satellite model of small and large clouds with cores (1 km) and edges (100 in) is consistent with this observation. The cores maintain high liquid water concentrations and large droplets while the edges contain low liquid water concentrations and small droplets. Large clouds are just a collection of cores. The mean optical depth (TAU) distributions support the above observation with TAU values of 3.55 to 9.38 favored across all cloud fractions. From these results, a method based upon Kedem, et al. theory is proposed to separate the cloud fraction and liquid water path (LWP) calculations in a general circulation model (GCM). In terms of spatial averaging, a linear relationship between albedo and cloud fraction is observed. For tropical locations outside the Intertropical Convergence Zone (ITCZ), results of cloud fraction and albedo spatial averaging followed that of the stratus boxes containing few overcast scenes. Both the ideas of Coakley and Kedem, et al. apply. Within the ITCZ, the grid boxes tended to have the same statistical properties as stratus boxes containing many overcast scenes. Because different dynamical forcing mechanisms are present, it is difficult to devise a method for determining subgrid scale variations. Neither of the theories proposed by Kedem, et al. or Coakley works well for the boxes with numerous overcast scenes.

Ginger, Kathryn M.↗

NASA NTRS1993

A regional analysis of cloudy mean spherical albedo over the marine stratocumulus region and the tropical Atlantic Ocean

Since clouds are the largest variable in Earth's radiation budget, it is critical to determine both the spatial and temporal characteristics of their radiative properties. The relationships between cloud properties and cloud fraction are studied in order to supplement grid scale parameterizations. The satellite data used is from three hourly ISCCP (International Satellite Cloud Climatology Project) and monthly ERBE (Earth Radiation Budget Experiment) data on a 2.5 deg x 2.5 deg latitude-longitude grid. Mean cloud spherical albedo, the mean optical depth distribution, and cloud fraction are examined and compared off the coast of California and the mid-tropical Atlantic for July 1987 and 1988. Individual grid boxes and spatial averages over several grid boxes are correlated to Coakley's theory of reflection for uniform and broken layered cloud and to Kedem, et al.'s findings that rainfall volume and fractional area of rain in convective systems is linear. Kedem's hypothesis can be expressed in terms of cloud properties. That is, the total volume of liquid in a box is a linear function of cloud fraction. Results for the marine stratocumulus regime indicate that albedo is often invariant for cloud fractions of 20% to 80%. Coakley's satellite model of small and large clouds with cores (1 km) and edges (100 m) is consistent with this observation. The cores maintain high liquid water concentrations and large droplets while the edges contain low liquid water concentrations and small droplets. Large clouds are just a collection of cores. The mean optical depth (TAU) distributions support the above observation with TAU values of 3.55 to 9.38 favored across all cloud fractions. From these results, a method based upon Kedem, et al's theory is proposed to separate the cloud fraction and liquid water path (LWP) calculations in a general circulation model (GCM). In terms of spatial averaging, a linear relationship between albedo and cloud fraction is observed. For tropical locations outside the Intertropical Convergence Zone (ITCZ), results of cloud fraction and albedo spatial averaging followed that of the stratus boxes containing few overcast scenes. Both the ideas of Coakley and Kedem, et al. apply. Within the ITCZ, the grid boxes tended to have the same statistical properties as stratus boxes containing many overcast scenes. Because different dynamical forcing mechanisms are present, it is difficult to devise a method for determining subgrid scale variations. Neither of the theories proposed by Kedem, et al. or Coakley works well for the boxes with numerous overcast scenes.

Ginger, Kathryn M.↗

NASA NTRS1978

Effects of cloud size and cloud particles on satellite-observed reflected brightness

Satellite observations allowed obtaining data on the visible brightness of cumulus clouds over South Park, Colorado, while aircraft observations were made in cloud to obtain the drop size distributions and liquid water content of the cloud. Attention is focused on evaluating the relationship between cloud brightness, horizontal dimension, and internal microphysical structure. A Monte Carlo cloud model for finite clouds was run using different distributions of drop sizes and numbers, while varying the cloud depth and width to determine how theory would predict what the satellite would view from its given location in space. Comparison of these results to the satellite observed reflectances is presented. Theoretical results are found to be in good agreement with observations. For clouds of optical thickness between 20 and 60, monitoring cloud brightness changes in clouds of uniform depth and variable width gives adequate information about a cloud's liquid water content. A cloud having a 10:1 width to depth ratio is almost reaching its maximum brightness for a specified optical thickness.

Reynolds, D. W.↗

NASA NTRS2008

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.

Minnis, Patrick↗

NASA NTRS2004

Near-Real Time Cloud Properties and Aircraft Icing Indices from GEO and LEO Satellites

Imagers on many of the current and future operational meteorological satellites in geostationary Earth orbit (GEO) and lower Earth orbit (LEO) have enough spectral channels to derive cloud microphysical properties useful for a variety of applications. The products include cloud amount, phase, optical depth, temperature, height and pressure, thickness, effective particle size, and ice or liquid water path, shortwave albedo, and outgoing longwave radiation for each imager pixel. Because aircraft icing depends on cloud temperature, droplet size, and liquid water content as well as aircraft variables, it is possible to estimate the potential icing conditions from the cloud phase, temperature, effective droplet size, and liquid water path. A prototype icing index is currently being derived over the contiguous USA in near-real time from Geostationary Operational Environmental Satellite (GOES-10 and 12) data on a half-hourly basis and from NOAA- 16 Advanced Very High Resolution (AVHRR) data when available. Because the threshold-based algorithm is sensitive to small errors and differences in satellite imager and icing is complex process, a new probability based icing diagnosis technique is developed from a limited set of pilot reports. The algorithm produces reasonable patterns of icing probability and intensities when compared with independent model and pilot report data. Methods are discussed for improving the technique for incorporation into operational icing products.

Minnis, Patrick↗

NASA NTRS1990

A GCM parameterization for the shortwave radiative properties of water clouds

A new parameterization was developed for predicting the shortwave radiative properties of water clouds, suitable for inclusion in general circulation models (GCMs). The parameterization makes use of the simple relationships found by Slingo and Schrecker, giving the three input parameters required to calculate the cloud radiative properties (the optical depth, single scatter albedo and asymmetry parameter) in terms of the liquid water path and equivalent radius of the drop size distribution. The input parameters are then used to derive the cloud radiative properties, using standard two-stream equations for a single layer. The relationships were originally derived for fairly narrow spectral bands but it was found that it is possible to average the coefficients so as to use a much smaller number of bands, without sacrificing accuracy in calculating the cloud radiative properties. This makes the parameterization fast enough to be included in GCMs. The parameterization was programmed into the radiation scheme used in the U.K. Meteorological Office GCM. This scheme and the 24 band Slingo/Schrecker scheme were compared with each other and with observations, using a variety of published datasets. There is good agreement between the two schemes for both cloud albedo and absorption, even when only four spectral bands are employed in the GCM.

Slingo, A.↗

NASA NTRS2007

Aerosol Radiative Effects on Deep Convective Clouds and Associated Radiative Forcing

The aerosol radiative effects (ARE) on the deep convective clouds are investigated by using a spectral-bin cloud-resolving model (CRM) coupled with a radiation scheme and an explicit land surface model. The sensitivity of cloud properties and the associated radiative forcing to aerosol single-scattering albedo (SSA) are examined. The ARE on cloud properties is pronounced for mid-visible SSA of 0.85. Relative to the case excluding the ARE, cloud fraction and optical depth decrease by about 18% and 20%, respectively. Cloud droplet and ice particle number concentrations, liquid water path (LWP), ice water path (IWP), and droplet size decrease significantly when the ARE is introduced. The ARE causes a surface cooling of about 0.35 K and significantly high heating rates in the lower troposphere (about 0.6K/day higher at 2 km), both of which lead to a more stable atmosphere and hence weaker convection. The weaker convection and the more desiccation of cloud layers explain the less cloudiness, lower cloud optical depth, LWP and IWP, smaller droplet size, and less precipitation. The daytime-mean direct forcing induced by black carbon is about 2.2 W/sq m at the top of atmosphere (TOA) and -17.4 W/sq m at the surface for SSA of 0.85. The semi-direct forcing is positive, about 10 and 11.2 W/sq m at the TOA and surface, respectively. Both the TOA and surface total radiative forcing values are strongly negative for the deep convective clouds, attributed mostly to aerosol indirect forcing. Aerosol direct and semi-direct effects are very sensitive to SSA. Because the positive semi-direct forcing compensates the negative direct forcing at the surface, the surface temperature and heat fluxes decrease less significantly with the increase of aerosol absorption (decreasing SSA). The cloud fraction, optical depth, convective strength, and precipitation decrease with the increase of absorption, resulting from a more stable and dryer atmosphere due to enhanced surface cooling and atmospheric heating.

Fan, J.↗

NASA NTRS2000

Top-of-Atmosphere Albedo Estimation from Angular Distribution Models using Scene Identification from Satellite Cloud Property Retrievals

The next generation of Earth radiation budget satellite instruments will routinely merge estimates of global top-of-atmosphere radiative fluxes with cloud properties. This information will offer many new opportunities for validating radiative transfer models and cloud parameterizations in climate models. In this study, five months of POLarization and Directionality of the Earth's Reflectances (POLDER) 670 nm radiance measurements are considered in order to examine how satellite cloud property retrievals can be used to define empirical Angular Distribution Models (ADMs) for estimating top-of-atmosphere (TOA) albedo. ADMs are defined for 19 scene types defined by satellite retrievals of cloud fraction and cloud optical depth. Two approaches are used to define the ADM scene types: The first assumes there are no biases in the retrieved cloud properties and defines ADMs for fixed discrete intervals of cloud fraction and cloud optical depth (fixed-tau approach). The second approach involves the same cloud fraction intervals, but uses percentile intervals of cloud optical depth instead (percentile-tau approach). Albedos generated using these methods are compared with albedos inferred directly from the mean observed reflectance field. Albedos based on ADMs that assume cloud properties are unbiased (fixed-tau approach) show a strong systematic dependence on viewing geometry. This dependence becomes more pronounced with increasing solar zenith angle, reaching approximately equals 12% (relative) between near-nadir and oblique viewing zenith angles for solar zenith angles between 60 deg and 70 deg. The cause for this bias is shown to be due to biases in the cloud optical depth retrievals. In contrast, albedos based on ADMs built using percentile intervals of cloud optical depth (percentile-tau approach) show very little viewing zenith angle dependence and are in good agreement with albedos obtained by direct integration of the mean observed reflectance field (less than 1% relative error). When the ADMs are applied separately to populations consisting of only liquid water and ice clouds, significant biases in albedo with viewing geometry are observed (particularly at low sun elevations), highlighting the need to account for cloud phase both in cloud optical depth retrievals and in defining ADM scene types. ADM-derived monthly mean albedos determined for all 5 deg x 5 deg latitude/longitude regions over ocean are in good agreement (regional RMS relative errors less than 2%) with those obtained by direct integration when ADM albedos inferred from specific angular bins are averaged together. Albedos inferred from near-nadir and oblique viewing zenith angles are the least accurate, with regional RMS errors reaching approximately 5-10% (relative). Compared to an earlier study involving ERBE ADMs, regional mean albedos based on the 19 scene types considered here show a factor of 4 reduction in bias error and a factor of 3 reduction in RMS error.

Loeb, N. G.↗

NASA NTRSDate not supplied

Cloud-Type Mean Cloud Properties and Associated Cloud Radiative Effects in the Tropical “Chimney” Zones Using 20 Years High-Resolution CERES Satellite Data

It has been well known that convection tends to be more intense over land than over ocean and continental convection generally contains wider cores that are protected from entrainment than their oceanic counterparts. How does this difference in convective intensity impact the rest of cloud types and associated cloud radiative effects (CREs)? We select five regions in the tropical “chimney” zones, with two regions over land (Africa and Amazon) and three regions over ocean (eastern and western Pacific, and Atlantic) to understand the differences in the cloud-type mean cloud properties and associated CREs using 20-years high-resolution (2x2 km2) CERES satellite data. The cloud types are based upon the ISCCP classification using the joint cloud-top pressure and cloud optical depth distribution. These five regions are compared to the entire tropics (25°S to 25°N). First, we compare the frequencies of occurrence of cloud types among the regions. Compared to the entire tropics, the “chimney” zones are cloudier, particularly, for cloud types with moderate cloud optical depths in the middle and upper troposphere. Except for the eastern Pacific region, the low-level cloud types are less abundant over land (due to higher boundary layers) and ocean (due to weaker lower-tropospheric subsidence). Over Africa, upper-level clouds are scarcer, due perhaps to weak production of convective anvils related to the drier atmosphere. Second, liquid water path (LWP) and ice water path (IWP) are compared among the regions. Compared to the entire tropics, mean LWPs for moderate cloud optical depths are higher for oceanic regions but lower for Africa while they are slightly lower in the lower troposphere but slightly higher in the middle troposphere for Amazon. Not surprisingly, mean IWPs are higher over land than over ocean, which is directly related to the difference in convective intensity. That is, the explanations to this result are the relatively weak convective intensity over the eastern Pacific and the abundance of anvil clouds over the western Pacific. Both reduce the mean IWPs. The CRE results are still being analyzed because the totally-clear grids (1° x 1°) of the CERES data product should be removed before taking a regional mean of clear-sky fluxes, which cause the wrong signs of CREs for a few cloud types.

cloud radiative effects↗

NASA NTRS1998

Microwave Brightness Temperatures of Tilted Convective Systems

Aircraft and ground-based radar data from the Tropical Ocean and Global Atmosphere Coupled-Ocean Atmosphere Response Experiment (TOGA COARE) show that convective systems are not always vertical. Instead, many are tilted from vertical. Satellite passive microwave radiometers observe the atmosphere at a viewing angle. For example, the Special Sensor Microwave/Imager (SSM/I) on Defense Meteorological Satellite Program (DMSP) satellites and the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) on the TRMM satellite have an incident angle of about 50deg. Thus, the brightness temperature measured from one direction of tilt may be different than that viewed from the opposite direction due to the different optical depth. This paper presents the investigation of passive microwave brightness temperatures of tilted convective systems. To account for the effect of tilt, a 3-D backward Monte Carlo radiative transfer model has been applied to a simple tilted cloud model and a dynamically evolving cloud model to derive the brightness temperature. The radiative transfer results indicate that brightness temperature varies when the viewing angle changes because of the different optical depth. The tilt increases the displacements between high 19 GHz brightness temperature (Tb(sub 19)) due to liquid emission from lower level of cloud and the low 85 GHz brightness temperature (Tb(sub 85)) due to ice scattering from upper level of cloud. As the resolution degrades, the difference of brightness temperature due to the change of viewing angle decreases dramatically. The dislocation between Tb(sub 19) and Tb(sub 85), however, remains prominent.

Hong, Ye↗