Editorial Type:
Article
Article Type:
Research Article

Comparison of TRMM 2A25 Products, Version 6 and Version 7, with NOAA/NSSL Ground Radar–Based National Mosaic QPE

Pierre-Emmanuel Kirstetter * School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, Oklahoma
NOAA/National Severe Storms Laboratory, Norman, Oklahoma
Atmospheric Radar Research Center, National Weather Center, Norman, Oklahoma

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Y. Hong * School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, Oklahoma
Atmospheric Radar Research Center, National Weather Center, Norman, Oklahoma

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J. J. Gourley NOAA/National Severe Storms Laboratory, Norman, Oklahoma

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M. Schwaller NASA Goddard Space Flight Center, Greenbelt, Maryland

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W. Petersen NASA Wallops Flight Facility, Wallops Island, Virginia

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J. Zhang NOAA/National Severe Storms Laboratory, Norman, Oklahoma

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Print Publication:
01 Apr 2013
DOI:
https://doi.org/10.1175/JHM-D-12-030.1
Page(s):
661–669
Restricted access

Abstract

Characterization of the error associated with satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. The authors focus here on the relative error structure of Tropical Rainfall Measurement Mission (TRMM) precipitation radar (PR) quantitative precipitation estimation (QPE) at the ground by comparison of 2A25 products with reference values derived from NOAA/NSSL’s ground radar–based National Mosaic and QPE system (NMQ/Q2). The primary contribution of this study is to compare the new 2A25, version 7 (V7), products that were recently released as a replacement of version 6 (V6). Moreover, the authors supply uncertainty estimates of the rainfall products so that they may be used in a quantitative manner for applications like hydrologic modeling. This new version is considered superior over land areas and will likely be the final version for TRMM PR rainfall estimates. Several aspects of the two versions are compared and quantified, including rainfall rate distributions, systematic biases, and random errors. All analyses indicate that V7 is in closer agreement with the reference rainfall compared to V6.

Corresponding author address: Professor Yang Hong, National Weather Center, 120 David L. Boren Blvd., Atmospheric Radar Research Center, Suite 4610, Norman, OK 73072-7303. E-mail: yanghong@ou.edu

Abstract

Characterization of the error associated with satellite rainfall estimates is a necessary component of deterministic and probabilistic frameworks involving spaceborne passive and active microwave measurements for applications ranging from water budget studies to forecasting natural hazards related to extreme rainfall events. The authors focus here on the relative error structure of Tropical Rainfall Measurement Mission (TRMM) precipitation radar (PR) quantitative precipitation estimation (QPE) at the ground by comparison of 2A25 products with reference values derived from NOAA/NSSL’s ground radar–based National Mosaic and QPE system (NMQ/Q2). The primary contribution of this study is to compare the new 2A25, version 7 (V7), products that were recently released as a replacement of version 6 (V6). Moreover, the authors supply uncertainty estimates of the rainfall products so that they may be used in a quantitative manner for applications like hydrologic modeling. This new version is considered superior over land areas and will likely be the final version for TRMM PR rainfall estimates. Several aspects of the two versions are compared and quantified, including rainfall rate distributions, systematic biases, and random errors. All analyses indicate that V7 is in closer agreement with the reference rainfall compared to V6.

Corresponding author address: Professor Yang Hong, National Weather Center, 120 David L. Boren Blvd., Atmospheric Radar Research Center, Suite 4610, Norman, OK 73072-7303. E-mail: yanghong@ou.edu
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Journal of Hydrometeorology

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