Cloudsat precipitation profiling algorithm-model description

Cristian Mitrescu, Tristan L'Ecuyer, John Matthew Haynes, Steven D Miller, Joseph Turk

Research output: Contribution to journalArticleResearchpeer-review

45 Citations (Scopus)


Identifying and quantifying the intensity of light precipitation at global scales is still a difficult problem for most of the remote sensing algorithms in use today. The variety of techniques and algorithms employed for such a task yields a rather wide spectrum of possible values for a given precipitation event, further hampering the understanding of cloud processes within the climate. The ability of CloudSat s millimeter-wavelength Cloud Profiling Radar (CPR) to profile not only cloud particles but also light precipitation brings some hope to the above problems. Introduced as version zero, the present work uses basic concepts of detection and retrieval of light precipitation using spaceborne radars. Based on physical principles of remote sensing, the radar model relies on the description of clouds and rain particles in terms of a drop size distribution function. Use of a numerical model temperature and humidity profile ensures the coexistence of mixed phases otherwise undetected by the CPR. It also provides grounds for evaluating atmospheric attenuation, important at this frequency. Related to the total attenuation, the surface response is used as an additional constraint in the retrieval algorithm. Practical application of the profiling algorithm includes a 1-yr preliminary analysis of global rainfall incidence and intensity. These results underscore once more the role of CloudSat rainfall products for improving and enhancing current estimates of global light rainfall, mostly at higher latitudes, with the goal of understanding its role in the global energy and water cycle.
Original languageEnglish
Pages (from-to)991 - 1003
Number of pages13
JournalJournal of Applied Meteorology and Climatology
Issue number5
Publication statusPublished - 2010

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