Cumulus Parameterization and Rainfall Rates I

T. N. Krishnamurti Department of Meteorology, Florida State University, Tallahassee 32306

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Y. Ramanathan Department of Meteorology, Florida State University, Tallahassee 32306

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Hua-Lu Pan Department of Meteorology, Florida State University, Tallahassee 32306

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Richard J. Pasch Department of Meteorology, Florida State University, Tallahassee 32306

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John Molinari Department of Meteorology, Florida State University, Tallahassee 32306

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Abstract

Modeling of convective rainfall rates is a central problem in tropical meteorology. Toward numerical weather prediction efforts the semi-prognostic approach (i.e., a one time-step prediction of rainfall rates) provides a relevant test of cumulus parameterization methods. In this paper we compare five currently available cumulus parameterization schemes using the semi-prognostic approach. The calculated rainfall rates are compared with observed estimates provided in the recent publication of Hudlow and Patterson (1979). Among these the scheme proposed by Kuo (1974) provides the least root-mean-square error between the calculated and the observed estimates, slightly better than that of Arakawa and Schubert (1974), which was used by Lord (1978a). The simplicity of the approach holds promise for numerical weather prediction. Unlike some of the other schemes this method is not sensitive to and does not require computation of internal parameters such as profiles of cloud mass flux updrafts and downdrafts, detrainment of cloud matter and entrainment of environmental air. The present paper does not address the prognostic evolution and verification of the vertical distribution of temperature, humidity or momentum. These will be compared for the different methods in more detail separately.

Abstract

Modeling of convective rainfall rates is a central problem in tropical meteorology. Toward numerical weather prediction efforts the semi-prognostic approach (i.e., a one time-step prediction of rainfall rates) provides a relevant test of cumulus parameterization methods. In this paper we compare five currently available cumulus parameterization schemes using the semi-prognostic approach. The calculated rainfall rates are compared with observed estimates provided in the recent publication of Hudlow and Patterson (1979). Among these the scheme proposed by Kuo (1974) provides the least root-mean-square error between the calculated and the observed estimates, slightly better than that of Arakawa and Schubert (1974), which was used by Lord (1978a). The simplicity of the approach holds promise for numerical weather prediction. Unlike some of the other schemes this method is not sensitive to and does not require computation of internal parameters such as profiles of cloud mass flux updrafts and downdrafts, detrainment of cloud matter and entrainment of environmental air. The present paper does not address the prognostic evolution and verification of the vertical distribution of temperature, humidity or momentum. These will be compared for the different methods in more detail separately.

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