TRMM Precipitation Feature Database

One way to summarize the precipitation events from the TRMM dataset is to define Precipitation Features (PFs, Nesbitt et al., 2000). This method groups the pixels with near surface PR reflectivity > 20 dBZ or ice scattering signal defined by TMI 85 GHz Polarization Corrected Temperature (PCT, Spencer et al., 1989) < 250 K. Using this definition and the similar feature grouping concept, results have included rainfall estimates validation (Nesbitt et al., 2004), diurnal cycle of precipitation systems (Nesbitt and Zipser, 2003), global distribution of storms with LIS-detected lightning (Cecil et al., 2005), deep convection reaching the tropical tropopause layer (Liu and Zipser, 2005), rainfall production and convective organization (Nesbitt et al. 2006), and the categorization of extreme thunderstorms by their intensity proxies (Zipser et al., 2006). In 2008, a set of new definitions of precipitation features and cloud features are introduced (Liu et al. 2008).

structureData Structure (see large picture)

The schematic diagram of the TRMM cloud and precipitation feature database with three levels of TRMM data processing is shown in the left Figure . First, the measurements from multiple instruments are temporally and spatially collocated. Then the cloud and precipitation features are defined with different criteria using these collocated data. Using the characteristics of defined features, global climatologies of cloud and precipitation feature populations, occurrences and other statistics are generated.

Using the collocated level-1 products, precipitation feature definitions are introduced by contiguous 2A25 near surface raining pixels (RPFs) and contiguous 2A12 surface raining pixels (TPFs). To fully utilize the three dimensional information from PR reflectivity profiles, Radar Projection Precipitation Features (RPPFs) are introduced by grouping the area of ground projection of radar reflectivity greater than 20 dBZ, which includes thick anvils aloft. Cold PCT features (PCTFs) are also defined by pixels with 85 GHz PCT < 250 K, for continuity with the longer record of SSM/I measurements. Cloud features are defined by using VIRS 10.8 mm brightness temperature (TB11) < 210 K (C210F), 235 K (C235F) and 273 K (C273F). Characteristics of features are summarized from measurements and retrievals from PR, TMI, VIRS and LIS at the grouped pixels (Details in Liu, 2007).

It is also important to study the climatologies of characteristics of these systems. For this purpose, we summarize the statistics of feature properties onto a 1x1 degree grid, such as the total volumetric rain, the maximum reflectivity found over a specific region, etc. Because TRMM observations include information of the diurnal variation of properties of cloud and precipitation systems, they are categorized into 8 local time periods. Level-3 products are processed for monthly, yearly, before boost (January 1998- July 2001), after boost (September 2001-December 2006), seasonally (DJF, MAM, JJA, SON), and 9 years (1998-2006). (Details in Liu, 2007).

Data Download All three levels of PF database are open to public from http server at:

SoftwareThe software in IDL is provided for reading three levels of product. Any questions regarding the usage of the dataset, please try to find the answer from the FAQ first. If there is no answer there, please contact us.

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