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 providing better estimates as more data arrive. The final step uses monthly gauge data to create research-level products. Background information and references are provided to describe the context and the relation to other similar missions. Issues involved in understanding the accuracies obtained from the calculations are discussed. Throughout, a baseline Day-1 product is described, together with options and planned improvements that might be instituted before or after launch depending on maturity and project constraints.
Download File:GPM Integrated Multi-Satellite Retrievals for GPM (IMERG) Algorithm Theoretical Basis Document (ATBD) v5.2Author(s):Publication Date:02/07/2018
Download File:GPM Combined Radar-Radiometer Precipitation Algorithm Theoretical Basis Document (ATBD) (Version 03)Publication Date:11/30/2011
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. Second, long-term accumulation of combined algorithm estimates will yield a single common reference dataset that will be used to “cross-calibrate” rain rate estimates from all of the passive microwave radiometers in the GPM constellation. The cross-calibration of the radiometer estimates is crucial for developing a consistent, high-time-resolution precipitation record for climate science and prediction model validation applications. Because of the Combined Algorithm’s essential roles as accurate reference and calibrator, the GPM Project is supporting a Combined Algorithm Team to implement and test the algorithm prior to launch. In the pre-launch phase, GPM-funded science investigations may lead to significant improvements in algorithm function, but the basic algorithm architecture has been formulated. This algorithm architecture is largely consistent with the successful TRMM Combined Algorithm design, but it has been updated and modularized to take advantage of improvements in the representation of physics, new climatological background information, and model- based analyses that may become available at any stage of the mission. This document presents a description of the GPM Combined Algorithm architecture, scientific basis, inputs/outputs, and supporting ancillary datasets.
Download File:GPM Microwave Imager (GMI) Level 1B Algorithm Theoretical Basis Document (ATBD) (Version 3)Author(s):Publication Date:11/01/2010
This document describes the GMI Level 1B algorithm. It consists of physical bases and mathematical equations for GMI calibration, as well as pre-launch and post-launch activities. The document also presents high-level software design. However, detailed software descriptions will be presented separately in the Level 1B Software Design Document. Parts of this document are from the RSS GMI Calibration ATBD as contributed by the Ball Aerospace GMI manufactory contract. The GMI L1B geolocation algorithm is described in a separate Geolocation Toolkit (GeoTK) ATBD.
Download File:GPM Level 1C Algorithm Theoretical Basis Document (ATBD) (Version 4)Publication Date:04/01/2016
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 Level 1C algorithms transform equivalent Level 1B radiance data into Level 1C products. The input source data are geolocated and radiometric calibrated antenna temperature (Ta) or brightness temperature (Tb). The output Level 1C products are common intercalibrated brightness temperature (Tc) products using the GPM Microwave Imager (GMI) as the reference standard.
Download File:GPM GPROF (Level 2) Algorithm Theoretical Basis Document (ATBD) (Version 4)Author(s):Publication Date:08/01/2014
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.
In particular, this document identifies sources of input data and output from the retrieval algorithm and describes the physical theory upon which the algorithm is based. The document includes implementation details, as well as the assumptions and limitations of the adopted approach. Because the algorithm is being developed by a broad team of scientists, this document additionally serves to keep each developer abreast of all the algorithm details and formats needed to interact with the code. The version number and date of the ATBD will therefore always correspond to the version number and date of the algorithm – even if changes are trivial.
Download File:GPM: Chapter 6 from "Precipitation: Advances in Measurement, Estimation, and Prediction"Publication Date:03/01/2008
Observations of the space-time variability of precipitation around the globe are imperative for understanding how climate change affects the global energy and water cycle (GWEC) in terms of changes in regional precipitation characteristics (type, frequency, intensity), as well as extreme hydrologic events, such as floods and droughts. The GWEC is driven by a host of complex processes and interactions, many of which are not yet well understood. Precipitation, which converts atmospheric water vapor into rain and snow, is a central element of the GWEC. Precipitation regulates the global energy and radiation balance through coupling to clouds and water vapor (the primary greenhouse gas) and shapes global winds and atmospheric transport through latent heat release. Surface precipitation directly affects soil moisture and land hydrology and is also the primary source of freshwater in a world that is facing an emerging freshwater crisis. Accurate and timely knowledge of global precipitation is essential for understanding the multi-scale interaction of the weather, climate and ecological systems and for improving our ability to manage freshwater resources and predicting high-impact weather events including hurricanes, floods, droughts and landslides.
In terms of measurements of precipitation, it is critical that data be collected at local scales over a global domain to capture the spatial and temporal diversity of falling rain and snow in meso-scale, synoptic-scale and planetary-scale events. However, given the limited weather station networks on land and the impracticality of making extensive rainfall measurements over oceans, a comprehensive description of the space and time variability of global precipitation can only be achieved from the vantage point of space.
A.Y. Hou, G. Skofronick-Jackson, C. Kummerow, and J. M. Shepherd, Global Precipitation Measurement, Chapter 6 in Precipitation: Advances in Measurement, Estimation and Prediction Editor: Silas Michaelides, Springer-Verlag, March 2008, 540pp, ISBN: 978-3-540-77654-3.
Download File:A First Approach to Global Runoff Simulation using Satellite Rainfall EstimationPublication Date:08/11/2007Motivated by the recent increasing availability of global remote sensing data for estimating precipitation and describing land surface characteristics, this note reports an approximate assessment of quasi-global runoff computed by incorporating satellite rainfall data and other remote sensing products in a relatively simple rainfall-runoff simulation approach: the Natural Resources Conservation Service (NRCS) runoff curve number (CN) method. Using an antecedent precipitation index (API) as a proxy of antecedent moisture conditions, this note estimates time-varying NRCS-CN values determined by the 5-day normalized API. Driven by a multiyear (1998–2006) Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis, quasi-global runoff was retrospectively simulated with the NRCS-CN method and compared to Global Runoff Data Centre data at global and catchment scales. Results demonstrated the potential for using this simple method when diagnosing runoff values from satellite rainfall for the globe and for medium to large river basins. This work was done with the simple NRCS-CN method as a first-cut approach to understanding the challenges that lie ahead in advancing the satellite-based inference of global runoff. We expect that the successes and limitations revealed in this study will lay the basis for applying more advanced methods to capture the dynamic variability of the global hydrologic process for global runoff monitoring in real time. The essential ingredient in this work is the use of global satellite-based rainfall estimation.
Download File:GPM Ground Validation: Strategy and EffortsKeywords:Publication Date:
The validation of satellite products is classically defined as a ground-based observing strategy intended to assess whether satellite products meet their stated accuracy requirements and objectives. In the case of the Tropical Rainfall Measurement Mission (TRMM), this philosophy was translated to the quasi-continuous operation of four ground radar sites for which TRMM satellite sensor-based and ground-based rainfall products were compared. The findings from these four sites revealed that TRMM products generally met their stated objectives. In addition, a number of lessons have also been learned in the course of these efforts: (a) quality control and careful construction of ground validation datasets is very labor intensive, but methods that make calibration and quality control techniques more efficient continue to improve; (b) despite every effort, ground validation data has its own set of uncertainties, consisting of both biases (currently ~ 5%) and random errors that are difficult to quantify on short time/space scales such as a single satellite overpass; and (c) direct comparison between rainfall estimates from the TRMM Precipitation Radar (PR) and microwave imager (TMI) reveal that instrument differences have regional and seasonal components that require validation results to be interpreted in a similar fashion.
Download File:International Ground Validation Research Programme of GPM: Report of 1st International GPM GV Requirements WorkshopAuthor(s):Keywords:Publication Date:
Report of the 1st International GPM GV Requirements Workshop.
Download File:2DVD at Egbert, CARE, CanadaAuthor(s):Publication Date:
Presentation of CSU's 2-Dimensional Video Disdrometer for the Canadian CloudSat/CALIPSO Validation Programme