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Optimization of Cloud-Radiation Databases for Passive Microwave Precipitation Retrievals over Ocean

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  • 1 Department of Earth Science Education, Kongju National University, Chungnam, South Korea
  • | 2 Applied Meteorological Research Division, National Institute of Meteorological Sciences, Jeju, South Korea
  • | 3 Goddard Earth Sciences Technology and Research Center, Morgan State University, Baltimore, Maryland, and Laboratory for Atmospheres, NASA Goddard Space Flight Center, Greenbelt, Maryland
  • | 4 National Meteorological Satellite Center, Korea Meteorological Administration, Jincheon-gun, South Korea
  • | 5 Florida State University, Tallahassee, Florida
  • | 6 Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, Los Angeles, California
  • | 7 Colorado State University, Fort Collins, Colorado
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Abstract

Using Tropical Rainfall Measuring Mission (TRMM) observations from storms collected over the oceans surrounding East Asia, during summer, a method of creating physically consistent cloud-radiation databases to support satellite radiometer retrievals is introduced. In this method, vertical profiles of numerical model-simulated cloud and precipitation fields are optimized against TRMM radar and radiometer observations using a hybrid empirical orthogonal function (EOF)–one-dimensional variational (1DVAR) approach.The optimization is based on comparing simulated to observed radar reflectivity profiles and the corresponding passive microwave observations at the frequencies of the TRMM Microwave Imager (TMI) instrument. To minimize the discrepancies between the actual and the synthetic observations, the simulated cloud and precipitation profiles are optimized by adjusting the contents of the hydrometeors. To reduce the dimension of the hydrometeor content profiles in the optimization, multivariate relations among hydrometeor species are used.

After applying the optimization method to modify the simulated clouds, the optimized cloud-radiation database has a joint distribution of reflectivity and associated brightness temperatures that is considerably closer to that observed by TRMM PR and TMI, especially at 85 GHz. This implies that the EOF–1DVAR approach can generate profiles with realistic distributions of frozen hydrometeors, such as snow and graupel. This approach may be similarly adapted to operate with the variety and capabilities of the passive microwave radiometers that compose the Global Precipitation Measurement (GPM) constellation. Furthermore, it can be extended to other oceanic regions and seasons.

Publisher’s Note: This article was revised on 9 August 2016 to correct the affiliation of the third author.

Corresponding author address: Eun-Kyoung Seo, Department of Earth Science Education, Kongju National University, 56 GongjuDaehak-Ro, Kongju, Chungnam 32588, South Korea. E-mail: ekseo@kongju.ac.kr

This article is included in the Precipitation Retrieval Algorithms for GPM special collection.

Abstract

Using Tropical Rainfall Measuring Mission (TRMM) observations from storms collected over the oceans surrounding East Asia, during summer, a method of creating physically consistent cloud-radiation databases to support satellite radiometer retrievals is introduced. In this method, vertical profiles of numerical model-simulated cloud and precipitation fields are optimized against TRMM radar and radiometer observations using a hybrid empirical orthogonal function (EOF)–one-dimensional variational (1DVAR) approach.The optimization is based on comparing simulated to observed radar reflectivity profiles and the corresponding passive microwave observations at the frequencies of the TRMM Microwave Imager (TMI) instrument. To minimize the discrepancies between the actual and the synthetic observations, the simulated cloud and precipitation profiles are optimized by adjusting the contents of the hydrometeors. To reduce the dimension of the hydrometeor content profiles in the optimization, multivariate relations among hydrometeor species are used.

After applying the optimization method to modify the simulated clouds, the optimized cloud-radiation database has a joint distribution of reflectivity and associated brightness temperatures that is considerably closer to that observed by TRMM PR and TMI, especially at 85 GHz. This implies that the EOF–1DVAR approach can generate profiles with realistic distributions of frozen hydrometeors, such as snow and graupel. This approach may be similarly adapted to operate with the variety and capabilities of the passive microwave radiometers that compose the Global Precipitation Measurement (GPM) constellation. Furthermore, it can be extended to other oceanic regions and seasons.

Publisher’s Note: This article was revised on 9 August 2016 to correct the affiliation of the third author.

Corresponding author address: Eun-Kyoung Seo, Department of Earth Science Education, Kongju National University, 56 GongjuDaehak-Ro, Kongju, Chungnam 32588, South Korea. E-mail: ekseo@kongju.ac.kr

This article is included in the Precipitation Retrieval Algorithms for GPM special collection.

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