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Wesley Berg, William Olson, Ralph Ferraro, Steven J. Goodman, and Frank J. LaFontaine

Abstract

Rainfall estimates produced from the Special Sensor Microwave/Imager (SSM/I) data have been utilized operationally by the United States Navy since the launch of the first SSM/I sensor in June of 1987. The navy initially contracted Hughes Aircraft Company to develop a rainfall-retrieval algorithm prior to the launch of SSM/I. This first-generation operational navy rainfall retrieval algorithm, referred to as the D-Matrix algorithm, was used until the development of the second-generation algorithm by the SSM/I Calibration/Validation team, which has subsequently been replaced by a third-generation algorithm developed by the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data and Information System. Results from both the D-Matrix and Cal/Val algorithms have been included in a total of five algorithm intercomparison projects conducted through the Global Precipitation Climatology Project and WetNet. A comprehensive summary of both quantitative and qualitative results from these intercomparisons is given detailing many of the strengths and weaknesses of the algorithms. Based on these results, the D-Matrix algorithm was found to produce excessively large estimates over land and to poorly represent the spatial structure of rainfall systems, especially at higher latitudes. The Cal/Val algorithm produces more realistic structure within storm systems but appears to overestimate the region of precipitation for many systems and significantly underestimates regions of intense rainfall. While the Cal/Val algorithm appears to provide better instantaneous rainfall estimates in the Tropics, the D-Matrix algorithm provides reasonable time-averaged results for monthly or longer periods.

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Stephen M. Saleeby, Wesley Berg, Susan van den Heever, and Tristan L’Ecuyer

Abstract

Cloud-nucleating aerosols emitted from mainland China have the potential to influence cloud and precipitation systems that propagate through the region of the East China Sea. Both simulations from the Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS) and observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) reveal plumes of pollution that are transported into the East China Sea via frontal passage or other offshore flow. Under such conditions, satellite-derived precipitation estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) frequently produce discrepancies in rainfall estimates that are hypothesized to be a result of aerosol modification of cloud and raindrop size distributions. Cloud-resolving model simulations were used to explore the impact of aerosol loading on three identified frontal-passage events in which the TMI and PR precipitation estimates displayed large discrepancies. Each of these events was characterized by convective and stratiform elements in association with a frontal passage. Area-averaged time series for each event reveal similar monotonic cloud and rain microphysical responses to aerosol loading. The ratio in the vertical distribution of cloud water to rainwater increased. Cloud droplet concentration increased and the mean diameters decreased, thereby reducing droplet autoconversion and collision–coalescence growth. As a result, raindrop concentration decreased, while the drop mean diameter increased; furthermore, average rainwater path magnitude and area fraction both decreased. The average precipitation rate fields reveal a complex modification of the timing and spatial coverage of rainfall. This suggests that the warm-rain microphysical response to aerosols, in addition to the precipitation life cycle, microphysical feedbacks, and evaporative effects, play an important role in determining surface rainfall.

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Ralph R. Ferraro, Eric A. Smith, Wesley Berg, and George J. Huffman

Abstract

The success of any passive microwave precipitation retrieval algorithm relies on the proper identification of rain areas and the elimination of surface areas that produce a signature similar to that of precipitation. A discussion on the impact of and on methods that identify areas of rain, snow cover, deserts, and semiarid conditions over land, and rain, sea ice, strong surface winds, and clear, calm conditions over ocean, are presented. Additional artifacts caused by coastlines and Special Sensor Microwave/Imager data errors are also discussed, and methods to alleviate their impact are presented. The strengths and weaknesses of the “screening” techniques are examined through application on various case studies used in the WetNet PIP-2. Finally, a methodology to develop a set of screens for use as a common rainfall indicator for the intercomparison of the wide variety of algorithms submitted to PIP-2 is described.

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