Documents

Date Last Updated
March 11th, 2019
Document Description

In IMERG up through V05, the cloud motion vector computation approach used is that pioneered in CMORPH (Joyce et al. 2011), in which motion vectors are computed from 4-km geosynchronous infrared (GEO-IR) brightness temperatures. Hence, the motion vectors reflect cloud top motions. However, there are two main limitations in using GEO-IR. The first limitation is that cloud top motions may not match precipitation motions due to both wind shear and the growth and decay of precipitation systems.

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Date Last Updated
October 10th, 2017
Document Description

This document describes the file naming conventions that will be used to name data products produced by the Precipitation Processing System (PPS) for the Global Precipitation Measurement (GPM) Mission. These file naming conventions are also intended to apply to files produced or reprocessed from the Tropical Rainfall Measuring Mission (TRMM) satellite during the period of GPM operations.

Date Last Updated
January 17th, 2020
Document Description

This document describes the data file formats for all GPM products. Metadata is described in Metadata for GPM Products. The purpose of this file specification document is to define the file content and format for the GPM data products.The file specifications have been reviewed by the algorithm developers. Formats are
expected to change for each processing cycle.

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Date Last Updated
October 1st, 2018
Document Description

This document describes the basic idea of DPR data processing. It was originally written for the
algorithm used in the at-launch version (V03). The algorithm has been modi ed and improved
since then. Although the basic idea of data processing remains the same, the actual ow of
processing, in particular that in the solver module, has changed substantially. As a result, some
part of description in section 3.1 may not be relevant any more.

Changes in the DPR algorithm from V05 to V06

Date Last Updated
January 18th, 2018
Document Description

The GPM Combined Radar-Radiometer Algorithm performs two basic functions: first, it provides, in principle, the most accurate, high resolution estimates of surface rainfall rate and precipitation vertical distributions that can be achieved from a spaceborne platform, and it is therefore valuable for applications where information regarding instantaneous storm structure are vital.

Date Last Updated
April 17th, 2018
Document Description

This ATBD describes the Global Precipitation Measurement (GPM) passive microwave rainfall algorithm, which is a parametric algorithm used to serve all GPM constellation radiometers. The output parameters of the algorithm are enumerated in Table 1. It is based upon the concept that the GPM core satellite, with its Dual Frequency Radar (DPR) and GPM Microwave Imager (GMI), will be used to build a consistent a-priori database of cloud and precipitation profiles to help constrain possible solutions from the constellation radiometers.

Date Last Updated
April 1st, 2016
Document Description

Level 1C (L1C) algorithms are a collection of algorithms that produce common calibrated brightness temperature products for the Global Precipitation Measurement (GPM) Core and Constellation satellites.

This document describes the GPM Level 1C algorithms. It consists of physical and mathematical bases for orbitization, satellite intercalibration, and quality control, as well as the software architecture and implementation for the Level 1C algorithms.

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Date Last Updated
October 1st, 2016
Document Description

This document describes the GMI Level 1B algorithm developed by PPS. It consists of physical bases and mathematical equations for GMI calibration, as well as after-launch activities. The document also presents high-level software design. Parts of this document are from the Remote Sensing Systems (RSS) GMI Calibration ATBD and the BATC Calibration Data Book as contributed by the BATC GMI manufactory contract. The GMI L1B geolocation algorithm is described in a separate Geolocation Toolkit ATBD.

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Date Last Updated
August 1st, 2015
Document Description

The Level 3 DPR product provides space-time statistics of the level 2 DPR results. High and low spatial resolution grids are defined such that the high-resolution grid is 0.250 × 0.250 (lat×lon) while the lowresolution grid is 50 ×50. For the variables defined on the low-resolution grid, the statistics include mean, standard deviation, counts and histogram. For variables defined on the high-resolution grid, the same
statistics are computed with the exception of a histogram, which is omitted.

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Date Last Updated
April 17th, 2018
Document Description

GPROF V05 is the rainfall algorithm used in TRMM V8. It matches in all ways the algorithm from the retrieval for GPM GMI and other satellites in the constellation. The Goddard Profiling Algorithm is a Bayesian approach that nominally uses the GPM Combined algorithm to create it's a-priori databases. Given the importance of these databases to the final product, they are worth reviewing before discussing particular changes to the algorithm. GPROF V03 was implemented at the launch of the GPM mission and thus had no databases from the GPM satellite itself.

Date Last Updated
April 22nd, 2020
Document Description

NASA produces a GIS translation of IMERG for various accumulation periods that maintains the 0.1-degree resolution and global coverage of the original HDF5 data product. In April 2019, Version 6 of IMERG was released in both the HDF5 and the GIS formats. Version 6 is the first version to cover the approximately 20-year period from June 2000 to the present. This long-duration archive will be a boon to scientific research and will provide an expanded training set for realtime applications such as disaster monitoring.

Date Last Updated
March 15th, 2019
Document Description

Users have requested a “simple” quality index (QI) to give some guidance on when they should most trust the Integrated Multi-satellitE Retrievals for GPM (IMERG). While the goal is reasonable, there is no agreement about how this quantity should be defined. After some discussion within the team, two distinctly different quality indices were chosen for the half-hourly and monthly data fields (QIh and QIm, respectively) for implementation in Version 05 and continued in V06.

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Date Last Updated
May 2nd, 2019
Document Description

The algorithm for the Integrated Multi-satellitE Retrievals for GPM (IMERG) has now been upgraded to Version 06. The transition to V05 for the IMERG Final Run began 13 March 2019 at PPS and the new data started flowing down to the GES DISC as well. However, on 15 March 2019 an error was discovered in processing the initial batches of V06 IMERG Final Run months. A design choice in the code ended up retaining microwave precipitation estimates in the latitude band 60°N-S when there is snow/ice on the surface, rather than masking out the estimates due to low performance in such cases.

Date Last Updated
April 26th, 2019
Document Description

The Integrated Multi-satelliE Retrievals for GPM (*IMERG*) is the unified U.S. algorithm that provides the multi-satellite precipitation product for the U.S. GPM team.  The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2017 version of the Goddard Profiling Algorithm (GPROF2017), then gridded, intercalibrated to the GPM Combined Radar Radiometer Analysis product (with GPCP climatological calibration), and combined into half-hourly 0.1°x0.1° fields.

Date Last Updated
April 26th, 2019
Document Description

This document describes the algorithm and processing sequence for the Integrated Multi-satellitE Retrievals for GPM (IMERG).  This algorithm is intended to intercalibrate, merge, and interpolate “all” satellite microwave precipitation estimates, together with microwave-calibrated infrared (IR) satellite estimates, precipitation gauge analyses, and potentially other precipitation estimators at fine time and space scales for the TRMM and GPM eras over the entire globe.

Date Last Updated
November 1st, 2019
Document Description

The transition from the Tropical Rainfall Measuring Mission (TRMM) data products to the Global Precipitation Measurement (GPM) mission products has begun. This document specifically addresses the multi-satellite products, the TRMM Multi-satellite Precipitation Analysis (TMPA), the real-time TMPA (TMPA-RT), and the Integrated Multi-satellitE Retrievals for GPM (IMERG).

Document Description

A table comparing the older TRMM Multi-satellite Preciptiation Analysis (TMPA) datasets with the new Integrated Multi-satellitE Retrievals for GPM (IMERG) datasets.