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- Author or Editor: Shashi K. Gupta x
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Abstract
A parameterization has been developed for computing downward, upward, and net longwave radiation at the earth's surface using meteorological data from NOAA's operational sun-synchronous satellites. The parameterization was developed using a narrowband radiative transfer model and a large meteorological database consisting of satellite and in situ soundings. Clear-sky downward flux was represented as a function of surface and lower tropospheric temperatures and water vapor burden of the atmosphere. Cloud contribution to the downward flux was represented in terms of cloud base temperature and water vapor burden of the atmosphere below the cloud. Upward flux was computed directly from the surface temperature. Results obtained with the parameterization were verified against detailed radiative transfer computations for an independent set of satellite and in situ soundings.
The parameterization was applied to satellite soundings for the month of April 1982 from a large region in the tropical Pacific Ocean. Averaged net fluxes for this month showed striking similarities with 8-yr averages of monthly-mean values obtained for the same region by an earlier investigator. Sensitivity studies were conducted to estimate random and systematic errors in computed fluxes due to probable errors in TOYS-derived parameters Random errors in fluxes computed for individual satellite soundings were estimated to be 20–25 W m−, but were reduced to <2 W m−2 for monthly averages over 5°×5° regions when fluxes for about 200 soundings were averaged. Biases as large as 8–10 W m−2 could still be present in the results, mainly because of the errors in TOYS-derived cloud parameters. This problem may be rectified in the near future with the availability of data from the International Satellite Cloud Climatology Project.
Abstract
A parameterization has been developed for computing downward, upward, and net longwave radiation at the earth's surface using meteorological data from NOAA's operational sun-synchronous satellites. The parameterization was developed using a narrowband radiative transfer model and a large meteorological database consisting of satellite and in situ soundings. Clear-sky downward flux was represented as a function of surface and lower tropospheric temperatures and water vapor burden of the atmosphere. Cloud contribution to the downward flux was represented in terms of cloud base temperature and water vapor burden of the atmosphere below the cloud. Upward flux was computed directly from the surface temperature. Results obtained with the parameterization were verified against detailed radiative transfer computations for an independent set of satellite and in situ soundings.
The parameterization was applied to satellite soundings for the month of April 1982 from a large region in the tropical Pacific Ocean. Averaged net fluxes for this month showed striking similarities with 8-yr averages of monthly-mean values obtained for the same region by an earlier investigator. Sensitivity studies were conducted to estimate random and systematic errors in computed fluxes due to probable errors in TOYS-derived parameters Random errors in fluxes computed for individual satellite soundings were estimated to be 20–25 W m−, but were reduced to <2 W m−2 for monthly averages over 5°×5° regions when fluxes for about 200 soundings were averaged. Biases as large as 8–10 W m−2 could still be present in the results, mainly because of the errors in TOYS-derived cloud parameters. This problem may be rectified in the near future with the availability of data from the International Satellite Cloud Climatology Project.
Abstract
Several improvements have been made recently to the parameterization for surface longwave radiation described by Gupta. Model constants have been modified in order to use meteorological data from the International Satellite Cloud Climatology Project instead of from the TIROS Operational Vertical Sounder data, primarily to take advantage of the vastly superior cloud information available from the former. Additional modifications were made to improve the estimation of cloud effect in the presence of low-level clouds. The latter modifications reduced the systematic error of the overcast-sky fluxes from 10.0 to 1.7 W m−2 and the random error from ±18.9 to ±6.3 W m−2 when compared to the fluxes computed with a detailed radiative transfer model.
Abstract
Several improvements have been made recently to the parameterization for surface longwave radiation described by Gupta. Model constants have been modified in order to use meteorological data from the International Satellite Cloud Climatology Project instead of from the TIROS Operational Vertical Sounder data, primarily to take advantage of the vastly superior cloud information available from the former. Additional modifications were made to improve the estimation of cloud effect in the presence of low-level clouds. The latter modifications reduced the systematic error of the overcast-sky fluxes from 10.0 to 1.7 W m−2 and the random error from ±18.9 to ±6.3 W m−2 when compared to the fluxes computed with a detailed radiative transfer model.
Abstract
An extensive study has been carried out to validate a satellite technique for estimating downward longwave radiation at the surface. The technique, mostly developed earlier, uses operational sun-synchronous satellite data and a radiative transfer model to provide the surface flux estimates. The satellite-derived fluxes were compared directly with corresponding ground-measured fluxes at four different sites in the United States for a common one-year data period. This provided a study of seasonal variations as well as a diversity of meteorological conditions. Dome heating errors in the ground-measured fluxes were also investigated and were corrected prior to the comparisons. Comparison of the monthly averaged fluxes from the satellite and ground sources for all four sites for the entire year showed a correlation coefficient of 0.98 and a standard error of estimate of 10 W m−2. A brief description of the technique is provided, and the results validating the technique are presented.
Abstract
An extensive study has been carried out to validate a satellite technique for estimating downward longwave radiation at the surface. The technique, mostly developed earlier, uses operational sun-synchronous satellite data and a radiative transfer model to provide the surface flux estimates. The satellite-derived fluxes were compared directly with corresponding ground-measured fluxes at four different sites in the United States for a common one-year data period. This provided a study of seasonal variations as well as a diversity of meteorological conditions. Dome heating errors in the ground-measured fluxes were also investigated and were corrected prior to the comparisons. Comparison of the monthly averaged fluxes from the satellite and ground sources for all four sites for the entire year showed a correlation coefficient of 0.98 and a standard error of estimate of 10 W m−2. A brief description of the technique is provided, and the results validating the technique are presented.
Abstract
A new technique is presented for generating downward longwave flux at the Earth's surface from satellite meteorological data and a radiative transfer model The technique was tested by using TIROS-N data from 41 passes over a ground site covering a period of one month. Satellite-derived fluxes were compared with those measured by a ground-based pyrgeometer during each overpass. The standard error of the satellite-derived fluxes relative to the mean ground-measured values was found to be 6.5%.
Abstract
A new technique is presented for generating downward longwave flux at the Earth's surface from satellite meteorological data and a radiative transfer model The technique was tested by using TIROS-N data from 41 passes over a ground site covering a period of one month. Satellite-derived fluxes were compared with those measured by a ground-based pyrgeometer during each overpass. The standard error of the satellite-derived fluxes relative to the mean ground-measured values was found to be 6.5%.
Abstract
Parameterized shortwave and longwave algorithms developed at the Langley Research Center have been used to derive surface radiative fluxes in the processing of the Clouds and the Earth's Radiant Energy System (CERES) data obtained from flight aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. Retrieved fluxes were validated on an instantaneous–footprint basis using coincident surface measurements obtained from the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) central facility, the ARM/SGP network of extended facilities, and a number of surface sites of the Baseline Surface Radiation Network (BSRN) and the Climate Monitoring and Diagnostics Laboratory (CMDL). Validation was carried out separately for clear-sky and all-sky conditions. For the shortwave, systematic errors varied from −12 to 10 W m−2 for clear skies and from −5 to 35 W m−2 for all-sky conditions. Random errors varied from 20 to 40 W m−2 for clear skies but were much larger (45–85 W m−2) for all-sky conditions. For the longwave, systematic errors were comparatively small for both clear-sky and all-sky conditions (0 to −10 W m−2) and random errors were within about 20 W m−2. In general, comparisons with surface data from the ARM/SGP site (especially the central facility) showed the best agreement. Large systematic errors in shortwave comparisons for some sites were related to flaws in the surface measurements. Larger errors in longwave fluxes for some footprints were found to be related to the errors in cloud mask retrievals, mostly during the nighttime. Smaller longwave errors related to potential errors in the operational analysis products used in satellite retrievals were also found. Still, longwave fluxes obtained with the present algorithm nearly meet the accuracy requirements for climate research.
Abstract
Parameterized shortwave and longwave algorithms developed at the Langley Research Center have been used to derive surface radiative fluxes in the processing of the Clouds and the Earth's Radiant Energy System (CERES) data obtained from flight aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. Retrieved fluxes were validated on an instantaneous–footprint basis using coincident surface measurements obtained from the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) central facility, the ARM/SGP network of extended facilities, and a number of surface sites of the Baseline Surface Radiation Network (BSRN) and the Climate Monitoring and Diagnostics Laboratory (CMDL). Validation was carried out separately for clear-sky and all-sky conditions. For the shortwave, systematic errors varied from −12 to 10 W m−2 for clear skies and from −5 to 35 W m−2 for all-sky conditions. Random errors varied from 20 to 40 W m−2 for clear skies but were much larger (45–85 W m−2) for all-sky conditions. For the longwave, systematic errors were comparatively small for both clear-sky and all-sky conditions (0 to −10 W m−2) and random errors were within about 20 W m−2. In general, comparisons with surface data from the ARM/SGP site (especially the central facility) showed the best agreement. Large systematic errors in shortwave comparisons for some sites were related to flaws in the surface measurements. Larger errors in longwave fluxes for some footprints were found to be related to the errors in cloud mask retrievals, mostly during the nighttime. Smaller longwave errors related to potential errors in the operational analysis products used in satellite retrievals were also found. Still, longwave fluxes obtained with the present algorithm nearly meet the accuracy requirements for climate research.
Abstract
The annual cycles of surface shortwave flux are investigated using the 8-yr dataset of the surface radiation budget (SRB) components for the period July 1983–June 1991. These components include the downward, upward, and net shortwave radiant fluxes at the earth's surface. The seasonal cycles are quantified in terms of principal components that describe the temporal variations and empirical orthogonal functions (EOFs) that describe the spatial patterns. The major part of the variation is simply due to the variation of the insolation at the top of the atmosphere, especially for the first term, which describes 92.4% of the variance for the downward shortwave flux. However, for the second term, which describes 4.1% of the variance, the effect of clouds is quite important and the effect of clouds dominates the third term, which describes 2.4% of the variance. To a large degree the second and third terms are due to the response of clouds to the annual cycle of solar forcing. For net shortwave flux at the surface, similar variances are described by each term. The regional values of the EOFs are related to climate classes, thereby defining the range of annual cycles of shortwave radiation for each climate class.
Abstract
The annual cycles of surface shortwave flux are investigated using the 8-yr dataset of the surface radiation budget (SRB) components for the period July 1983–June 1991. These components include the downward, upward, and net shortwave radiant fluxes at the earth's surface. The seasonal cycles are quantified in terms of principal components that describe the temporal variations and empirical orthogonal functions (EOFs) that describe the spatial patterns. The major part of the variation is simply due to the variation of the insolation at the top of the atmosphere, especially for the first term, which describes 92.4% of the variance for the downward shortwave flux. However, for the second term, which describes 4.1% of the variance, the effect of clouds is quite important and the effect of clouds dominates the third term, which describes 2.4% of the variance. To a large degree the second and third terms are due to the response of clouds to the annual cycle of solar forcing. For net shortwave flux at the surface, similar variances are described by each term. The regional values of the EOFs are related to climate classes, thereby defining the range of annual cycles of shortwave radiation for each climate class.
Abstract
A technique is presented for estimating insulation at the Earth's surface using only sun-synchronous satellite data. The technique was tested by comparing the insolation results from year-long satellite datasets with simultaneous ground-measured insolation taken at five continental United States sites Monthly average insolation values derived from the satellite data showed a standard error of 4.2 W m−2, or 2.7% of the average ground insulation value.
Abstract
A technique is presented for estimating insulation at the Earth's surface using only sun-synchronous satellite data. The technique was tested by comparing the insolation results from year-long satellite datasets with simultaneous ground-measured insolation taken at five continental United States sites Monthly average insolation values derived from the satellite data showed a standard error of 4.2 W m−2, or 2.7% of the average ground insulation value.
Abstract
The Clouds and the Earth’s Radiant Energy System (CERES) project uses two shortwave (SW) and two longwave (LW) algorithms to derive surface radiative fluxes on an instantaneous footprint basis from a combination of top-of-atmosphere fluxes, ancillary meteorological data, and retrieved cloud properties. Since the CERES project examines the radiative forcings and feedbacks for Earth’s entire climate system, validation of these models for a wide variety of surface conditions is paramount. The present validation effort focuses upon the ability of these surface-only flux algorithms to produce accurate CERES Edition 2B single scanner footprint data from the Terra and Aqua spacecraft measurements. To facilitate the validation process, high-quality radiometric surface observations have been acquired that were coincident with the CERES-derived surface fluxes. For both SW models, systematic errors range from −20 to −12 W m−2 (from −2.8% to −1.6%) for global clear-sky cases, while for the all-sky SW model, the systematic errors range from 14 to 21 W m−2 (3.2%–4.8%) for global cloudy-sky cases. Larger systematic errors were seen for the individual surface types, and significant random errors where observed, especially for cloudy-sky cases. While the SW models nearly achieved the 20 W m−2 accuracy requirements established for climate research, further improvements are warranted. For the clear-sky LW model, systematic errors were observed to fall within ±5.4 W m−2 (±1.9%) except for the polar case in which systematic errors on the order from −15 to −11 W m−2 (from −13% to −7.2%) occurred. For the all-sky LW model, systematic errors were less than ±9.2 W m−2 (±7.6%) for both the clear-sky and cloudy-sky cases. The random errors were less than 17 W m−2 (6.2%) for clear-sky cases and 28 W m−2 (13%) for cloudy-sky cases, except for the desert cases in which very high surface skin temperatures caused an overestimation in the model-calculated surface fluxes. Overall, however, the LW models met the accuracy requirements for climate research.
Abstract
The Clouds and the Earth’s Radiant Energy System (CERES) project uses two shortwave (SW) and two longwave (LW) algorithms to derive surface radiative fluxes on an instantaneous footprint basis from a combination of top-of-atmosphere fluxes, ancillary meteorological data, and retrieved cloud properties. Since the CERES project examines the radiative forcings and feedbacks for Earth’s entire climate system, validation of these models for a wide variety of surface conditions is paramount. The present validation effort focuses upon the ability of these surface-only flux algorithms to produce accurate CERES Edition 2B single scanner footprint data from the Terra and Aqua spacecraft measurements. To facilitate the validation process, high-quality radiometric surface observations have been acquired that were coincident with the CERES-derived surface fluxes. For both SW models, systematic errors range from −20 to −12 W m−2 (from −2.8% to −1.6%) for global clear-sky cases, while for the all-sky SW model, the systematic errors range from 14 to 21 W m−2 (3.2%–4.8%) for global cloudy-sky cases. Larger systematic errors were seen for the individual surface types, and significant random errors where observed, especially for cloudy-sky cases. While the SW models nearly achieved the 20 W m−2 accuracy requirements established for climate research, further improvements are warranted. For the clear-sky LW model, systematic errors were observed to fall within ±5.4 W m−2 (±1.9%) except for the polar case in which systematic errors on the order from −15 to −11 W m−2 (from −13% to −7.2%) occurred. For the all-sky LW model, systematic errors were less than ±9.2 W m−2 (±7.6%) for both the clear-sky and cloudy-sky cases. The random errors were less than 17 W m−2 (6.2%) for clear-sky cases and 28 W m−2 (13%) for cloudy-sky cases, except for the desert cases in which very high surface skin temperatures caused an overestimation in the model-calculated surface fluxes. Overall, however, the LW models met the accuracy requirements for climate research.
Abstract
Surface radiative fluxes have been derived with the objective of supplementing top-of-atmosphere (TOA) radiative fluxes being measured under NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project. This has been accomplished by using combinations of CERES TOA measurements, parameterized radiative transfer algorithms, and high-quality meteorological datasets available from reanalysis projects. Current CERES footprint-level products include surface fluxes derived from two shortwave (SW) and three longwave (LW) algorithms designated as SW models A and B and LW models A, B, and C. The SW and LW models A work for clear conditions only; the other models work for both clear and cloudy conditions. The current CERES Edition-4A computed surface fluxes from all models are validated against ground-based flux measurements from high-quality surface networks like the Baseline Surface Radiation Network and NOAA’s Surface Radiation Budget Network (SURFRAD). Validation results as systematic and random errors are provided for all models, separately for five different surface types and combined for all surface types as tables and scatterplots. Validation of surface fluxes is now a part of CERES processing and is used to continually improve the above algorithms. Since both models B work for clear and cloudy conditions alike and meet the accuracy requirement, their results are considered to be the most reliable and most likely to be retained for future work. Both models A have limited use given that they work for clear skies only. Models B will continue to undergo further improvement as more validation results become available.
Abstract
Surface radiative fluxes have been derived with the objective of supplementing top-of-atmosphere (TOA) radiative fluxes being measured under NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project. This has been accomplished by using combinations of CERES TOA measurements, parameterized radiative transfer algorithms, and high-quality meteorological datasets available from reanalysis projects. Current CERES footprint-level products include surface fluxes derived from two shortwave (SW) and three longwave (LW) algorithms designated as SW models A and B and LW models A, B, and C. The SW and LW models A work for clear conditions only; the other models work for both clear and cloudy conditions. The current CERES Edition-4A computed surface fluxes from all models are validated against ground-based flux measurements from high-quality surface networks like the Baseline Surface Radiation Network and NOAA’s Surface Radiation Budget Network (SURFRAD). Validation results as systematic and random errors are provided for all models, separately for five different surface types and combined for all surface types as tables and scatterplots. Validation of surface fluxes is now a part of CERES processing and is used to continually improve the above algorithms. Since both models B work for clear and cloudy conditions alike and meet the accuracy requirement, their results are considered to be the most reliable and most likely to be retained for future work. Both models A have limited use given that they work for clear skies only. Models B will continue to undergo further improvement as more validation results become available.
Abstract
The surface radiation budget of a region is strongly tied to its climate. An 8-yr climatology of surface radiation budget components for 2.5° regions over the earth is examined in order to learn how the regional climate and surface radiation are related. The yearly cycles of a few individual regions were studied by plotting monthly mean net longwave flux as a function of net shortwave flux at the surface. These plots show trajectories that are characteristic of the climate class. The behavior of the trajectories of surface radiation and their relation to the regional climate can be understood with simple conceptual models for many cases.
From an examination of these trajectories, a set of parameters is developed, such as mean net longwave flux and range of net shortwave flux, which distinguish various climate classes on the basis of the surface radiation. These criteria are applied to produce a map of regional climate classes based on surface radiation, similar to those of Koeppen or Trewartha and Horn, which were based on vegetation, temperature, and precipitation. The current maps can be used to explore the relationships between surface radiation and regional climate.
Abstract
The surface radiation budget of a region is strongly tied to its climate. An 8-yr climatology of surface radiation budget components for 2.5° regions over the earth is examined in order to learn how the regional climate and surface radiation are related. The yearly cycles of a few individual regions were studied by plotting monthly mean net longwave flux as a function of net shortwave flux at the surface. These plots show trajectories that are characteristic of the climate class. The behavior of the trajectories of surface radiation and their relation to the regional climate can be understood with simple conceptual models for many cases.
From an examination of these trajectories, a set of parameters is developed, such as mean net longwave flux and range of net shortwave flux, which distinguish various climate classes on the basis of the surface radiation. These criteria are applied to produce a map of regional climate classes based on surface radiation, similar to those of Koeppen or Trewartha and Horn, which were based on vegetation, temperature, and precipitation. The current maps can be used to explore the relationships between surface radiation and regional climate.
