Latest Documents

  • GPM GPROF (Level 2) Algorithm Theoretical Basis Document (ATBD) (Version 4)
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    Publication Date:
    08/01/2014
    Abstract / Summary:

    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.

  • GPM/DPR Level 2 Algorithm Theoretical Basis Document (ATBD)
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    Publication Date:
    08/01/2017
    Abstract / Summary:

    The objective of the level 2 DPR algorithms is to generate from the level 1 DPR products radar-only derived meteorological quantities on an instantaneous FOV (field of view) basis. A subset of the results will be used by the level 2 combined radar-radiometer algorithm and the level 3 combined and radar-only products.

    The general idea behind the algorithms is to determine general characteristics of the precipitation, correct for attenuation and estimate profiles of the precipitation water content, rainfall rate and, when dual-wavelength data are available, information on the particle size distributions in rain and snow. It is particularly important that dual-wavelength data will provide better estimates of rainfall and snowfall rates than the TRMM PR data by using the particle size information and the capability of estimating, even in convective storms, the height at which the precipitation transitions from solid to liquid.

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    GPM Integrated Multi-Satellite Retrievals for GPM (IMERG) Algorithm Theoretical Basis Document (ATBD) v5.2
    Publication Date:
    02/07/2018
    Abstract / Summary:

    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.

  • GPM Combined Radar-Radiometer Precipitation Algorithm Theoretical Basis Document (ATBD) (Version 03)
    Publication Date:
    11/30/2011
    Abstract / Summary:

    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.

  • GPM: Chapter 6 from "Precipitation: Advances in Measurement, Estimation, and Prediction"
    Publication Date:
    03/01/2008
    Abstract / Summary:

    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.

     

  • A First Approach to Global Runoff Simulation using Satellite Rainfall Estimation
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    Publication Date:
    08/11/2007
    Abstract / Summary:
    Motivated 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.
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    2DVD at Egbert, CARE, Canada
    Author(s):
    Keywords:
    Publication Date:
    Abstract / Summary:

    Presentation of CSU's 2-Dimensional Video Disdrometer for the Canadian CloudSat/CALIPSO Validation Programme

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    A GPM-DOE Midlatitude Continental Convective Clouds Experiment (MC3E)
    Keywords:
    Publication Date:
    Abstract / Summary:

    To improve the fidelity of radiometer-based rainfall estimates over land at short temporal and spatial scales, the Global Precipitation Measurement mission (GPM) requires development of physically-based passive microwave (PMW) precipitation retrieval algorithms anchored by dual-frequency precipitation radar (DPR) drop size distribution (DSD), hydrometeor profile and rain rate retrievals. Emphasizing this need, the 2nd GPM Ground Validation White Paper (Kummerow and Petersen, 2006; hereafter GVWP) outlined the many significant challenges involved with the development and validation of these algorithms. To broadly paraphrase the GVWP, PMW algorithm development/validation over land requires not only an improved understanding of cloud and precipitation microphysics (particularly in the ice and mixed phases), but an improved representation of microphysical processes/properties (at the bulk and particle scales) in relevant cloud and/or empirical models- to include improved formulation of the radiative transfer occurring in a variable background of land-surface emissivity. Considering that 1) precipitation estimates made by the GPM satellite constellation will rely most heavily on PMW and combined DPR/PMW retrieval algorithms; 2) there are currently no robust physically-based PMW precipitation retrieval algorithms available for use over land1; and 3) GPM objectives ascribe considerable importance to making accurate measurements over land where people live, water resources are managed, and flooding occurs; the ability to accurately retrieve precipitation over land using combined DPR/PMW and or PMW-only algorithms, especially those areas not covered by radar and/or rain gauge networks, is critical to the overall success of GPM. The proposed GPM GV effort thus devotes significant effort and resources to improving the basic understanding required for developing and validating physically based PMW algorithms over land.

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    GPM Ground Validation: Strategy and Efforts
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    Publication Date:
    Abstract / Summary:

    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.

  • International Ground Validation Research Programme of GPM: Report of 1st International GPM GV Requirements Workshop
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    Publication Date:
    Abstract / Summary:

    Report of the 1st International GPM GV Requirements Workshop.

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