GPM Documents

  • GPM/DPR Level 2 Algorithm Theoretical Basis Document (ATBD)
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    Publication Date:
    10/01/2018
    Abstract / Summary:

    The objective of the level 2 DPR algorithms is to generate from the level 1 DPR products radaronly 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: 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.

     

  • International Ground Validation Research Programme of GPM: Report of 1st International GPM GV Requirements Workshop
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    Report of the 1st International GPM GV Requirements Workshop.

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    2DVD at Egbert, CARE, Canada
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    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)
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    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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    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.

  • Snowflake Size Distribution Measurements in South Central Ontario, Canada
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    Parsivel Distrometer Results presented at the American Geophysical Union, Spring 2007.

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    C3VP 2007 IOP3 Case Summary
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    n all, 9 snowfall events were observed during IOP-3. All of these events were observed by the King City radars, 8 of the events were observed by the University of Massachusetts 3-frequency (W-, Ka, and Ku-band) Advanced Multi-Frequency Radar (AMFR), and 3 of the events were also observed with Convar-580 overflights.

    This document is a case summary of the dates, times, snowfall types, and instruments used during these 9 IOP-3 snowfall events.

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    Snowflake Video Imager at C3VP
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    The NASA Snowflake Video Imager obtained nearly continuous data from 1 Dec 06 thru 7 Mar 07.

    This presentation contains a summary for the entire data set, which is sorted into (a) priority days selected by GSFC investigators, and (b) non-priority days.

    The results are displayed in images of DSD(t), which reveal (a) the large variability of snowflakes sizes during events and (b) the intermittency of snowfall – even during intense storms.

    Additionally, results from a preliminary study of snowflake orientation reveals that there is a higher occurrence of snowflakes that are ‘horizontally’ orientated than ‘vertically’ orientated.

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