Algorithm Information

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.

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.

The Level-3 radar products provide daily and monthly global statistics of the Level-2 Ku, Ka and DPR products on a latitude-longitude grid. In version 7 (V07), the organization of the products has changed with the highest-level categorization into FS (full swath), MS (matched or inner swath) and HS (high sensitivity) swath products. The next level of division is into high and low spatial resolution grids that are defined such that the low-resolution grid (G1) is 50×50 (lat×lon) while the high-resolution grid (G2) is 0.250× 0.250.

Latent heating (LH) cannot be measured directly with current techniques, including current remote sensing or in situ instruments, which explains why nearly all satellite retrieval schemes depend heavily on some type of cloud-resolving model or CRM (Tao et al. 2006, 2016). This is true for the current CSH algorithm (Tao et al. 2010).

Input: Combined 2BCMB (DPR + GMI) rainfall products

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. 

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).

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.  The system is run several times for each observation time, first giving a quick estimate and successively providin

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.

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.

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 precipitation distributions that can be achieved from a spaceborne platform, and it is therefore valuable for applications where information regarding instantaneous storm structure are vital.