Is Precipitation a Good Metric for Model Performance?

Francisco J. Tapiador Earth and Space Sciences Group, Department of Environmental Sciences, Institute of Environmental Sciences, University of Castilla–La Mancha, Toledo, Spain

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Rémy Roca Laboratoire d’Etudes en Géophysique et Océanographie Spatiales, Observatoire Midi-Pyrénées, Toulouse, France

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Anthony Del Genio NASA Goddard Institute for Space Studies, New York, New York

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Boris Dewitte Laboratoire d’Etudes en Géophysique et Océanographie Spatiales, Observatoire Midi-Pyrénées, Toulouse, France, and Centro de Estudios Avanzado en Zonas Áridas, and Departamento de Biología, Facultad de Ciencias del Mar, Universidad Católica del Norte, Coquimbo, Chile

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Walt Petersen ST-11, Earth Science Office, NASA Marshall Space Flight Center, and National Space Science and Technology Center, Huntsville, Alabama

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Fuqing Zhang Department of Meteorology and Atmospheric Science, and Center for Advanced Data Assimilation and Predictability Techniques, The Pennsylvania State University, University Park, Pennsylvania

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Abstract

Precipitation has often been used to gauge the performances of numerical weather and climate models, sometimes together with other variables such as temperature, humidity, geopotential, and clouds. Precipitation, however, is singular in that it can present a high spatial variability and probably the sharpest gradients among all meteorological fields. Moreover, its quantitative measurement is plagued with difficulties, and there are even notable differences among different reference datasets. Several additional issues sometimes lead to questions about its usefulness in model validation. This essay discusses the use of precipitation for model verification and validation and the crucial role of highly precise and reliable satellite estimates, such as those from NASA’s Global Precipitation Mission Core Observatory.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Francisco J. Tapiador, francisco.tapiador@uclm.es

Abstract

Precipitation has often been used to gauge the performances of numerical weather and climate models, sometimes together with other variables such as temperature, humidity, geopotential, and clouds. Precipitation, however, is singular in that it can present a high spatial variability and probably the sharpest gradients among all meteorological fields. Moreover, its quantitative measurement is plagued with difficulties, and there are even notable differences among different reference datasets. Several additional issues sometimes lead to questions about its usefulness in model validation. This essay discusses the use of precipitation for model verification and validation and the crucial role of highly precise and reliable satellite estimates, such as those from NASA’s Global Precipitation Mission Core Observatory.

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Francisco J. Tapiador, francisco.tapiador@uclm.es
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