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Precipitation Measuring Missions (PMM)

Precipitation Measuring Missions (PMM) including TRMM and GPM are NASA projects focusing on measuring the precipitation globally. The Tropical Rainfall Measuring Mission (TRMM, Kummerow et al., 1998) was launched in November 1997 with the data archieve dating from December 1997. On the TRMM satellite, the Precipitation Radar (PR) can provide detailed vertical distribution of radar refectivity, related to the number and especially the size of precipitation inside systems. The TRMM Microwave Imager (TMI) can provide information related to the vertically integrated ice and water path. The Visible and Infrared Scanner (VIRS) can provide information on cloud top temperature and reflectance. At the same time, the Lightning Imaging Sensor (LIS) estimates lightning flash rates. This webpage is dedicated to providing a searching tool of the past TRMM and future GPM observations and distributing some general scientifically ready products to the public from the Texas A&M University at Corpus Christi (TAMU-CC) precipitation feature database as an extension of NASA's GSFC PMM data service PPS.

Precipitation Features

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 greater or equal to 20 dBZ, or with an ice scattering signal defined by TMI 85 GHz Polarization Corrected Temperature (PCT, Spencer et al., 1989) less or equal to 250 K. Using this definition and the similar feature grouping concept, results have included validation of rainfall estimates (Nesbitt et al., 2004), the diurnal cycle of precipitation systems and their rainfall (Nesbitt and Zipser, 2003), the 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), expanding capabilities for analysis.

Rainfall Estimates Measuring the amount of rainfall reaching the ground is challenging, because there is no single rainfall product that can represent the ground truth. Products from rain gauges have reliable estimation of rainfall only over areas with dense rain gauge networks. Rainfall retrieved from the space borne radar and microwave instrument has global coverage, but suffers from uncertainties in the observations and retrieval algorithms. (see detail)

Precipitation Features (PFs) It is important to understand what kind of the precipitation systems bring the rain to different regions on the Earth. For example, rainfall of 100 mm per month might fall in frequent, numerous small showers, or in one or two massive mesoscale storm systems, with the remaining days rainless. Some regions might receive 200 mm per month from shallow cloud systems with little or no lightning, while other regions might receive the same amount of rainfall, 80 percent of it from thunderstorm systems. Our motivation for sorting rainfall events into PFs is to facilitate study of the physical causes of the events as well as cataloging the total rainfall or frequency of rainfall.(see detail)

Severe Storms Where are the most severe thunderstorms on Earth? Using the precipitation feature definition, we may sort and evaluate the severity of the storms based on their echo top, vertical distribution of reflectivity, lightning flash rate, ice scattering signal and other proxies. (see detail)

ClimatologyTRMM has been observing rainfall and storms over the tropics and subtropics for more than 10 years. During this 10 year period, we have experienced one strong El Nino Southern Oscillation (ENSO) cycle and at least one weaker cycle. How does the distribution of PFs and intense storms vary with the ENSO cycle? This is but one example of how the TRMM database may be used in the climate model validation. (see detail)

Tropical Cyclones There has been a major improvement in the tropical cyclone track forecasting in the past decade. However, prediction of tropical cyclone intensity change and rainfall is still challenging, and of immense practical importance.? The TRMM database is a promising tool for developing improved predictions of tropical cyclone rainfall after landfall. (coming soon)

OthersThe TRMM database is not only valuable by itself for research leading to better detection and understanding of significant rainfall, storm, and tropical cyclone events. ?More can be achieved by careful comparison of TRMM data with products from other satellites and models, e.g., the suite of ?A-Train satellites, and through use of cloud resolving models. (coming soon)

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