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- Author or Editor: Anne C. Wilber x
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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
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
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 annual cycles of upward and downward longwave fluxes at the earth’s surface are investigated by use of the NASA Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget Dataset. Principal component analysis is used to quantify the annual cycles. Because of the immense difference between the heat capacity of land and ocean, the surface of the earth is partitioned into these two categories. Over land, the first principal component describes over 95% of the variance of the annual cycle of the upward and downward longwave fluxes. Over ocean the first term describes more than 87% of these annual cycles. Empirical orthogonal functions show the corresponding geographical distributions of these cycles. Phase-plane diagrams of the annual cycles of upward longwave fluxes as a function of net shortwave flux show the thermal inertia of land and ocean.
Abstract
The annual cycles of upward and downward longwave fluxes at the earth’s surface are investigated by use of the NASA Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget Dataset. Principal component analysis is used to quantify the annual cycles. Because of the immense difference between the heat capacity of land and ocean, the surface of the earth is partitioned into these two categories. Over land, the first principal component describes over 95% of the variance of the annual cycle of the upward and downward longwave fluxes. Over ocean the first term describes more than 87% of these annual cycles. Empirical orthogonal functions show the corresponding geographical distributions of these cycles. Phase-plane diagrams of the annual cycles of upward longwave fluxes as a function of net shortwave flux show the thermal inertia of land and ocean.
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.
Abstract
Climatological averages of surface radiation budget parameters, namely, the shortwave and longwave surface radiative fluxes, have been derived for each month of the year on a global scale. These climatological averages were derived from an 8-yr (96 month) time series of monthly average fluxes. The monthly averages were computed using fast radiation parameterizations and satellite data from the International Satellite Cloud Climatology Project and the Earth Radiation Budget Experiment. Results are presented as time series of hemispheric and global averages and as geographical distributions and time–latitude cross sections of climatological averages. The spatial/temporal variabilities of the results were found to be clearly related to the corresponding variabilities of meteorological and other inputs to the parameterizations. Numerous comparisons of the present results were made with available surface measurements for the purpose of validation. In most cases, the differences were found to be within the uncertainties of the measurements. In some cases, where they were large, the differences were attributable to identifiable deficiencies in the meteorological inputs and/or the surface measurements. However, large differences remained unexplained in a few cases. Anomalies of shortwave and longwave surface fluxes during the 1986/87 El Niño–Southern Oscillation episode show a strong relationship with corresponding top-of-atmosphere anomalies derived from an independent data source. Comparisons with results from several general circulation models showed large differences, but, in most cases, these were attributable to well-recognized deficiencies in model simulations. Global annual average downward and net shortwave fluxes were found to be about 185 and 161 W m−2, respectively. These values are 10–20 W m−2 lower than those obtained from the general circulation models, but they are in good agreement with other satellite-derived estimates. Global annual average downward and net longwave fluxes were found to be about 348 and −48 W m−2, respectively, which are about 10–15 W m−2 higher than corresponding values from general circulation models. Atmospheric shortwave absorption derived from the present results is 10–15 W m−2 larger than from the general circulation models, but it is in good agreement with another estimate based on satellite data.
Abstract
Climatological averages of surface radiation budget parameters, namely, the shortwave and longwave surface radiative fluxes, have been derived for each month of the year on a global scale. These climatological averages were derived from an 8-yr (96 month) time series of monthly average fluxes. The monthly averages were computed using fast radiation parameterizations and satellite data from the International Satellite Cloud Climatology Project and the Earth Radiation Budget Experiment. Results are presented as time series of hemispheric and global averages and as geographical distributions and time–latitude cross sections of climatological averages. The spatial/temporal variabilities of the results were found to be clearly related to the corresponding variabilities of meteorological and other inputs to the parameterizations. Numerous comparisons of the present results were made with available surface measurements for the purpose of validation. In most cases, the differences were found to be within the uncertainties of the measurements. In some cases, where they were large, the differences were attributable to identifiable deficiencies in the meteorological inputs and/or the surface measurements. However, large differences remained unexplained in a few cases. Anomalies of shortwave and longwave surface fluxes during the 1986/87 El Niño–Southern Oscillation episode show a strong relationship with corresponding top-of-atmosphere anomalies derived from an independent data source. Comparisons with results from several general circulation models showed large differences, but, in most cases, these were attributable to well-recognized deficiencies in model simulations. Global annual average downward and net shortwave fluxes were found to be about 185 and 161 W m−2, respectively. These values are 10–20 W m−2 lower than those obtained from the general circulation models, but they are in good agreement with other satellite-derived estimates. Global annual average downward and net longwave fluxes were found to be about 348 and −48 W m−2, respectively, which are about 10–15 W m−2 higher than corresponding values from general circulation models. Atmospheric shortwave absorption derived from the present results is 10–15 W m−2 larger than from the general circulation models, but it is in good agreement with another estimate based on satellite data.
Abstract
The Clouds and the Earth’s Radiant Energy Systems (CERES) project utilizes radiometric measurements taken aboard the Terra and Aqua spacecrafts to derive the world-class data products needed for climate research. Achieving the exceptional fidelity of the CERES data products, however, requires a considerable amount of processing to assure quality and to verify accuracy and precision, which results in the CERES data being released more than 6 months after the satellite observations. For most climate studies such delays are of little consequence; however, there are a significant number of near–real time uses for CERES data products. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was therefore developed to provide a rapid release version of the CERES results, which could be made available to the research and applications communities within 1 week of the satellite observations by exchanging some accuracy for speed. FLASHFlux has both achieved this 1-week processing objective and demonstrated the ability to provide remarkably good agreement when compared with the CERES data products for both the instantaneous single-scanner footprint (SSF) fluxes and the time- and space-averaged (TISA) fluxes. This paper describes the methods used to expedite the production of the FLASHFlux SSF fluxes by utilizing data from the CERES and Moderate Resolution Imaging Spectroradiometer instruments, as well as other meteorological sources. This paper also reports on the validation of the FLASHFlux SSF results against ground-truth measurements and the intercomparison of FLASHFlux and CERES SSF results. A complementary paper will discuss the production and validation of the FLASHFlux TISA fluxes.
Abstract
The Clouds and the Earth’s Radiant Energy Systems (CERES) project utilizes radiometric measurements taken aboard the Terra and Aqua spacecrafts to derive the world-class data products needed for climate research. Achieving the exceptional fidelity of the CERES data products, however, requires a considerable amount of processing to assure quality and to verify accuracy and precision, which results in the CERES data being released more than 6 months after the satellite observations. For most climate studies such delays are of little consequence; however, there are a significant number of near–real time uses for CERES data products. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was therefore developed to provide a rapid release version of the CERES results, which could be made available to the research and applications communities within 1 week of the satellite observations by exchanging some accuracy for speed. FLASHFlux has both achieved this 1-week processing objective and demonstrated the ability to provide remarkably good agreement when compared with the CERES data products for both the instantaneous single-scanner footprint (SSF) fluxes and the time- and space-averaged (TISA) fluxes. This paper describes the methods used to expedite the production of the FLASHFlux SSF fluxes by utilizing data from the CERES and Moderate Resolution Imaging Spectroradiometer instruments, as well as other meteorological sources. This paper also reports on the validation of the FLASHFlux SSF results against ground-truth measurements and the intercomparison of FLASHFlux and CERES SSF results. A complementary paper will discuss the production and validation of the FLASHFlux TISA fluxes.
Abstract
An improvement was developed and tested for surface longwave flux algorithms used in the Clouds and the Earth’s Radiant Energy System processing based on lessons learned during the validation of global results of those algorithms. The algorithms involved showed significant overestimation of downward longwave flux for certain regions, especially dry–arid regions during hot times of the day. The primary cause of this overestimation was identified and the algorithms were modified to (i) detect meteorological conditions that would produce an overestimation, and (ii) apply a correction when the overestimation occurred. The application of this correction largely eliminated the positive bias that was observed in earlier validation studies. Comparisons of validation results before and after the application of correction are presented.
Abstract
An improvement was developed and tested for surface longwave flux algorithms used in the Clouds and the Earth’s Radiant Energy System processing based on lessons learned during the validation of global results of those algorithms. The algorithms involved showed significant overestimation of downward longwave flux for certain regions, especially dry–arid regions during hot times of the day. The primary cause of this overestimation was identified and the algorithms were modified to (i) detect meteorological conditions that would produce an overestimation, and (ii) apply a correction when the overestimation occurred. The application of this correction largely eliminated the positive bias that was observed in earlier validation studies. Comparisons of validation results before and after the application of correction are presented.
