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  • Author or Editor: Paul W. Stackhouse Jr x
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Ehrhard Raschke, Stefan Kinne, William B. Rossow, Paul W. Stackhouse Jr, and Martin Wild

Abstract

This study examines radiative flux distributions and local spread of values from three major observational datasets (CERES, ISCCP, and SRB) and compares them with results from climate modeling (CMIP3). Examinations of the spread and differences also differentiate among contributions from cloudy and clear-sky conditions. The spread among observational datasets is in large part caused by noncloud ancillary data. Average differences of at least 10 W m−2 each for clear-sky downward solar, upward solar, and upward infrared fluxes at the surface demonstrate via spatial difference patterns major differences in assumptions for atmospheric aerosol, solar surface albedo and surface temperature, and/or emittance in observational datasets. At the top of the atmosphere (TOA), observational datasets are less influenced by the ancillary data errors than at the surface. Comparisons of spatial radiative flux distributions at the TOA between observations and climate modeling indicate large deficiencies in the strength and distribution of model-simulated cloud radiative effects. Differences are largest for lower-altitude clouds over low-latitude oceans. Global modeling simulates stronger cloud radiative effects (CRE) by +30 W m−2 over trade wind cumulus regions, yet smaller CRE by about −30 W m−2 over (smaller in area) stratocumulus regions. At the surface, climate modeling simulates on average about 15 W m−2 smaller radiative net flux imbalances, as if climate modeling underestimates latent heat release (and precipitation). Relative to observational datasets, simulated surface net fluxes are particularly lower over oceanic trade wind regions (where global modeling tends to overestimate the radiative impact of clouds). Still, with the uncertainty in noncloud ancillary data, observational data do not establish a reliable reference.

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Shashi K. Gupta, David P. Kratz, Paul W. Stackhouse Jr., Anne C. Wilber, Taiping Zhang, and Victor E. Sothcott

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.

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David P. Kratz, Paul W. Stackhouse Jr., Shashi K. Gupta, Anne C. Wilber, Parnchai Sawaengphokhai, and Greg R. McGarragh

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.

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