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  • Author or Editor: Eric J. Nelkin x
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George J. Huffman
,
David T. Bolvin
,
Eric J. Nelkin
,
David B. Wolff
,
Robert F. Adler
,
Guojun Gu
,
Yang Hong
,
Kenneth P. Bowman
, and
Erich F. Stocker

Abstract

The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining precipitation estimates from multiple satellites, as well as gauge analyses where feasible, at fine scales (0.25° × 0.25° and 3 hourly). TMPA is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The dataset covers the latitude band 50°N–S for the period from 1998 to the delayed present. Early validation results are as follows: the TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate–dependent low bias due to lack of sensitivity to low precipitation rates over ocean in one of the input products [based on Advanced Microwave Sounding Unit-B (AMSU-B)]. At finer scales the TMPA is successful at approximately reproducing the surface observation–based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other finescale estimators. Examples are provided of a flood event and diurnal cycle determination.

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Daniel C. Watters
,
Patrick N. Gatlin
,
David T. Bolvin
,
George J. Huffman
,
Robert Joyce
,
Pierre Kirstetter
,
Eric J. Nelkin
,
Sarah Ringerud
,
Jackson Tan
,
Jianxin Wang
, and
David Wolff

Abstract

NASA’s multisatellite precipitation product from the Global Precipitation Measurement (GPM) mission, the Integrated Multi-satellitE Retrievals for GPM (IMERG) product, is validated over tropical and high-latitude oceans from June 2014 to August 2021. This oceanic study uses the GPM Validation Network’s island-based radars to assess IMERG when the GPM Core Observatory’s Microwave Imager (GMI) observes precipitation at these sites (i.e., IMERG-GMI). Error tracing from the Level 3 (gridded) IMERG V06B product back through to the input Level 2 (satellite footprint) Goddard Profiling Algorithm GMI V05 climate (GPROF-CLIM) product quantifies the errors separately associated with each step in the gridding and calibration of the estimates from GPROF-CLIM to IMERG-GMI. Mean relative bias results indicate that IMERG-GMI V06B overestimates Alaskan high-latitude oceanic precipitation by +147% and tropical oceanic precipitation by +12% with respect to surface radars. GPROF-CLIM V05 overestimates Alaskan oceanic precipitation by +15%, showing that the IMERG algorithm’s calibration adjustments to the input GPROF-CLIM precipitation estimates increase the mean relative bias in this region. In contrast, IMERG adjustments are minimal over tropical waters with GPROF-CLIM overestimating oceanic precipitation by +14%. This study discovered that the IMERG V06B gridding process incorrectly geolocated GPROF-CLIM V05 precipitation estimates by 0.1° eastward in the latitude band 75°N–75°S, which has been rectified in the IMERG V07 algorithm. Correcting for the geolocation error in IMERG-GMI V06B improved oceanic statistics, with improvements greater in tropical waters than Alaskan waters. This error tracing approach enables a high-precision diagnosis of how different IMERG algorithm steps contribute to and mitigate errors, demonstrating the importance of collaboration between evaluation studies and algorithm developers.

Significance Statement

Evaluation of IMERG’s oceanic performance is very limited to date. This study uses the GPM Validation Network to conduct the first extensive assessment of IMERG V06B at its native resolution over both high-latitude and tropical oceans, and traces errors in IMERG-GMI back through to the input GPROF-CLIM GMI product. IMERG-GMI overestimates tropical oceanic precipitation (+12%) and strongly overestimates Alaskan oceanic precipitation (+147%) with respect to the island-based radars studied. IMERG’s GMI estimates are assessed as these should be the optimal estimates within the multisatellite product due to the GMI’s status as calibrator of the GPM passive microwave constellation.

Open access
Robert F. Adler
,
George J. Huffman
,
Alfred Chang
,
Ralph Ferraro
,
Ping-Ping Xie
,
John Janowiak
,
Bruno Rudolf
,
Udo Schneider
,
Scott Curtis
,
David Bolvin
,
Arnold Gruber
,
Joel Susskind
,
Philip Arkin
, and
Eric Nelkin

Abstract

The Global Precipitation Climatology Project (GPCP) Version-2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5° latitude × 2.5° longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and surface rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The dataset is extended back into the premicrowave era (before mid-1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the rain gauge analysis. The dataset archive also contains the individual input fields, a combined satellite estimate, and error estimates for each field. This monthly analysis is the foundation for the GPCP suite of products, including those at finer temporal resolution. The 23-yr GPCP climatology is characterized, along with time and space variations of precipitation.

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