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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 FROM AUTHOR]

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 FROM AUTHOR]

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 FROM AUTHOR]

Occasionally, a need arises to downscale a time series of data from a coarse temporal resolution to a finer one, a typical example being from monthly means to daily means. For this case, daily means derived as such are used as inputs of climatic or atmospheric models so that the model results may exhibit variance on the daily time scale and retain the monthly mean of the original data set without an abrupt change from the end of one month to the beginning of the next. Different methods have been developed which often need assumptions, free parameters and the solution of simultaneous equations. Here we derive a generalized formulation by means of Fourier transform and inversion so that it can be used to directly compute daily means from a series of an arbitrary number of monthly means. The formulation can be used to transform any coarse temporal resolution to a finer one. From the derived results, the original data can be recovered almost identically. As a real application, we use this method to derive the daily counterpart of the MAC-v1 aerosol climatology that provides monthly mean aerosol properties for 18 shortwave bands and 12 longwave bands for the years from 1860 to 2100. The derived daily means are to be used as inputs of the shortwave and longwave algorithms of the NASA GEWEX SRB project. [ABSTRACT FROM AUTHOR]

The longwave downward fluxes at the Earth׳s surface are a significant part of the products of the NASA GEWEX SRB (Surface Radiation Budget) project which has produced and archived a 24.5-year continuous record from July 1983 to December 2007 of global shortwave (SW) and longwave (LW) radiation fluxes at TOA and the surface from satellite measurements. The data are generated on a system of grid boxes ranging from 1° latitude by 1° longitude at lower latitudes to 1° latitude by 120° longitude next to the poles. The LW datasets, which are available as 3-hourly, 3-hourly–monthly, daily and monthly means, are produced from two sets of algorithms, the GEWEX LW (GLW) algorithm which is designated as primary and the Langley Parameterized LW (LPLA) algorithm which is designated as quality-check. The inputs of the latest versions, GLW (V3.1) and LPLA (V3.0), include the Geostationary Satellite system (GEOS) Version 4.0.3 meteorological information and cloud properties derived from the International Satellite Cloud Climatology Project (ISCCP) DX data. In this paper, we compare the LW downward fluxes at the Earth׳s surface from both algorithms against over 4000 site-months of the Baseline Surface Radiation Network (BSRN) data from among the 59 BSRN sites. The comparisons are made for the 3-hourly, daily and monthly means each for the entire record, and on a month-by-month basis as well as a site-by-site basis. It is found that the overall daily mean bias/RMS for the GLW (V3.1) and LPLA (V3.0) algorithms are, respectively, 1.1/22.1 and 4.6/22.8 W m −2 , their monthly counterparts are, respectively, 0.9/11.1 and 4.5/12.9 W m −2 . Anomaly time series for a subset of more continuous BSRN measurement data sets show a standard deviation of 2.3 W m −2 and a correlation of 0.82 indicating the accurate replication of month-to-month variability. Clusters of similar surface types are analyzed showing that the uncertainties are largest over the polar regions. Finally, Kolmogorov–Smirnov (KS) two-sample test and Cramér–von Mises (CvM) two-sample test are used to show that the GLW is able to replicate the cumulative frequency distribution of the measurements at the 0.01 significance level. [ABSTRACT FROM AUTHOR]