This note is intended to serve primarily as a reference guide to users wishing to make use of the Tropical Rainfall Measuring Mission data. It covers each of the three primary rainfall instruments: the passive microwave radiometer, the precipitation radar, and the Visible and Infrared Radiometer System on board the spacecraft. Radiometric characteristics, scanning geometry, calibration procedures, and data products are described for each of these three sensors.

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The Tropical Rainfall Measuring Mission (TRMM) Sensor Package

Precipitation affects many aspects of our everyday life. It is the primary source of freshwater and has significant socioeconomic impacts resulting from natural hazards such as hurricanes, floods, droughts, and landslides. Fundamentally, precipitation is a critical component of the global water and energy cycle that governs the weather, climate, and ecological systems. Accurate and timely knowledge of when, where, and how much it rains or snows is essential for understanding how the Earth system functions and for improving the prediction of weather, climate, freshwater resources, and natural hazard events. The Global Precipitation Measurement (GPM) mission is an international satellite mission specifically designed to set a new standard for the measurement of precipitation from space and to provide a new generation of global rainfall and snowfall observations in all parts of the world every 3 h. The National Aeronautics and Space Administration (NASA) and the Japan Aerospace and Exploration Agency (JAXA) ...

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The Global Precipitation Measurement Mission

A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5,000–12,000 stations, which represent 2.3–4.5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, ...

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APHRODITE: Constructing a Long-Term Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on 27 November 1997, and data from all the instruments first became available approximately 30 days after the launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, and applications of these results to areas such as data assimilation and model initialization. The TRMM Microwave Imager (TMI) calibration has been corrected and verified to account for a small source of radiation leaking into the TMI receiver. The precipitation radar calibration has been adjusted upward slightly (by 0.6 dB Z) to match better the ground reference targets; the visible and infrared sensor calibration remains largely unchanged. Two versions of the TRMM rainfall algorithms are discussed. The at-launch (version 4) algorithms showed differences of 40% when averaged over the global Tropics over 30-day periods. The improvements to the rainfall algorithms that were undertaken after launch are presented, and intercomparisons of these products (version 5) show agreement improving to 24% for global tropical monthly averages. The ground-based radar rainfall product generation is discussed. Quality-control issues have delayed the routine production of these products until the summer of 2000, but comparisons of TRMM products with early versions of the ground validation products as well as with rain gauge network data suggest that uncertainties among the TRMM algorithms are of approximately the same magnitude as differences between TRMM products and ground-based rainfall estimates. The TRMM field experiment program is discussed to describe active areas of measurements and plans to use these data for further algorithm improvements. In addition to the many papers in this special issue, results coming from the analysis of TRMM products to study the diurnal cycle, the climatological description of the vertical profile of precipitation, storm types, and the distribution of shallow convection, as well as advances in data assimilation of moisture and model forecast improvements using TRMM data, are discussed in a companion TRMM special issue in the Journal of Climate (1 December 2000, Vol. 13, No. 23).

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The status of the tropical rainfall measuring mission (TRMM) after two years in orbit

Describes an outline of the algorithm that estimates the instantaneous profiles of the true radar reflectivity factor and rainfall rate from the radar reflectivity profiles observed by the precipitation radar (PR) onboard the TRMM satellite. The major challenge of the algorithm lies in the correction of rain attenuation with the non-uniform beam filling effect. The algorithm was tested with synthetic data and the result is shown.

Rain profiling algorithm for the TRMM precipitation radar

To provide useful precipitation measurements from space, two requirements must be met: adequate spatial and temporal sampling of the storm and sufficient accuracy in the estimate of precipitation intensity. Although presently no single instrument or method completely satisfies both requirements, the visible/IR, microwave radiometer and radar methods can be used in a complementary manner. Visible/IR instruments provide good temporal sampling and rain area depiction, but recourse must be made to microwave measurements for quantitative rainfall estimates. The inadequacy of microwave radiometer measurements over land suggests, in turn, the use of radar. Several recently developed attenuating-wavelength radar methods are discussed in terms of their accuracy, dynamic range and system implementation. Traditionally, the requirements of high resolution and adequate dynamic range led to fairly costly and complex radar systems. Some simplications and cost reduction can be made; however, by using K-band wavelengths which have the advantages of greater sensitivity at the low rain rates and higher resolution capabilities. Several recently proposed methods of this kind are reviewed in terms of accuracy and system implementation. Finally, an adaptive-pointing multi-sensor instrument is described that would exploit certain advantages of the IR, radiometric and radar methods.

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The outlook for precipitation measurements from space

Although most parameterizations of the drop size distributions (DSD) use the gamma function, there are several advantages to the log-normal form, particularly if we want to characterize the large scale space-time variability of the DSD and rain rate. The advantages of the distribution are twofold: the logarithm of any moment can be expressed as a linear combination of the individual parameters of the distribution; the parameters of the distribution are approximately normally distributed. Since all radar and rainfall-related parameters can be written approximately as a moment of the DSD, the first property allows us to express the logarithm of any radar/rainfall variable as a linear combination of the individual DSD parameters. Another consequence is that any power law relationship between rain rate, reflectivity factor, specific attenuation or water content can be expressed in terms of the covariance matrix of the DSD parameters. The joint-normal property of the DSD parameters has applications to the description of the space-time variation of rainfall in the sense that any radar-rainfall quantity can be specified by the covariance matrix associated with the DSD parameters at two arbitrary space-time points. As such, the parameterization provides a means by which we can use the spaceborne radar-derived DSD parameters to specify in part the covariance matrices globally. However, since satellite observations have coarse temporal sampling, the specification of the temporal covariance must be derived from ancillary measurements and models. Work is presently underway to determine whether the use of instantaneous rain rate data from the TRMM Precipitation Radar can provide good estimates of the spatial correlation in rain rate from data collected in 5(sup 0)x 5(sup 0) x 1 month space-time boxes. To characterize the temporal characteristics of the DSD parameters, disdrometer data are being used from the Wallops Flight Facility site where as many as 4 disdrometers have been used to acquire data over a 2 km path. These data should help quantify the temporal form of the covariance matrix at this site.

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On the use of the log-normal particle size distribution to characterize global rain

A spaceborne precipitation radar samples the vertical structure of precipitating hydrometeors from the top down The viewing geometry and operating frequency result in certain limitations and opportunities Among the limitations is attenuation of the radar signal that can cause the measured radar reflectivity factor to be substantially less than the desired quantity, the true radar reflectivity factor Another error source is the spatial variability in precipitation rates that occurs at scales smaller than the sensor field of view (FOV), giving rise to the nonuniform beamfilling (NUBF) effect The opportunities arise when the radar return from the surface can be used to obtain constraints on the path-integrated attenuation (PIA) for use in hybrid attenuation correction algorithms The surface return can also provide some information on the degree of NUBF at off-nadir viewing angles In this paper ground-based radar data are used to simulate spaceborne radar data at nadir and off-nadir viewing angl

https://journals.ametsoc.org/doi/pdf/10.1175/JTECH-D-15-0021.1

Reduction of Nonuniform Beamfilling Effects by Multiple Constraints: A Simulation Study

Global Precipitation Measurement (GPM) mission's core satellite has been collecting precipitation data from space for more than a year. This paper reviews the performance of precipitation retrieval algorithm and evaluates the rainfall rates estimated with the Dual-frequency Precipitation Radar (DPR) onboard the GPM's core satellite. Differences between the rain estimates with TRMM's Precipitation Radar (PR) and those with GPM's DPR are examined.

Precipitation rates estimated with GPM's Dual-frequency Radar

The primary goal of the dual-frequency precipitation radar (DPR) aboard the Global Precipitation Measurement (GPM) Core Observatory satellite is to infer precipitation rate and raindrop/particle size distributions (DSD/PSD). The focus of this paper is threefold: (1) to describe the DPR retrieval algorithm that uses an adjustable relationship between rain rate (R) and the mass-weighted diameter (Dm) or an R-Dm relationship in solving for R and Dm simultaneously; (2) to evaluate the DPR algorithm based on the physical simulations that employ measured DSD/PSD to understand the mechanism and error characteristics of the retrieval method; (3) to review ground validation studies for DPR products as well as to analyze the strengths and weaknesses of ground radar and rain gauge/disdrometer validations. Overall, the DPR Version 6 algorithm provides reasonably accurate estimates of R and Dm in rain. Non-uniformity in the rain profile, however, tends to degrade the accuracy of the R and Dm estimates to some extent as the range-independent assumption of the adjustable parameter (ε) of the R-Dm relation is not able to fully account for natural variation of DSD in the vertical profile. The DPR snow rate is underestimated as compared with the independent dual-frequency ratio (DFR) technique. This is possibly the result of the constraint associated with the path integral attenuation (PIA)/differential PIA (δPIA) used in the DPR algorithm to find the best ε and range-independent ε assumption. A range-variable ε model, proposed in the DPR Version 7 algorithm, is expected to improve rain and snow retrieval.

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Robert Meneghini

Papers

The outlook for precipitation measurements from space

On the use of the log-normal particle size distribution to characterize global rain

Reduction of Nonuniform Beamfilling Effects by Multiple Constraints: A Simulation Study

Precipitation rates estimated with GPM's Dual-frequency Radar

GPM DPR Retrievals: Algorithm, Evaluation, and Validation