Title
Mechanisms of tropical precipitation biases in climate models
Date Issued
01 January 2021
Access level
metadata only access
Resource Type
journal article
Publisher(s)
Springer Science and Business Media Deutschland GmbH
Abstract
We investigate the possible causes for inter-model spread in tropical zonal-mean precipitation pattern, which is divided into hemispherically symmetric and anti-symmetric modes via empirical orthogonal function analysis. The symmetric pattern characterizes the leading mode and is tightly related to the seasonal amplitude of maximum precipitation position. The energetic constraints link the symmetric pattern to the seasonal amplitude in cross-equatorial atmospheric energy transport AET and the annual-mean equatorial net energy input NEI. Decomposition of AET into the energetics variables indicates that the inter-model spread in symmetric precipitation pattern is correlated with the inter-model spread in clear-sky atmospheric shortwave absorption, which most likely arises due to differences in radiative transfer parameterizations rather than water vapor patterns. Among the components that consist NEI , the inter-model spread in symmetric precipitation pattern is mostly associated with the inter-model spread in net surface energy flux in the equatorial region, which is modulated by the strength of cooling by equatorial upwelling. Our results provide clues to understand the mechanism of tropical precipitation bias, thereby providing guidance for model improvements.
Start page
17
End page
27
Volume
56
Issue
February 1
Language
English
OCDE Knowledge area
Meteorología y ciencias atmosféricas
Publication version
Version of Record
Scopus EID
2-s2.0-85093816167
Source
Climate Dynamics
ISSN of the container
09307575
Sponsor(s)
SMK and HK were supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2016R1A1A3A04005520). AGP was supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy’s Office of Biological & Environmental Research (BER) via NSF IA 1844590; NCAR is sponsored by the National Science Foundation (NSF) under Cooperative Agreement No. 1947282. AD’s work was supported by the National Science Foundation Paleo Perspective on Climate Change (P2C2) Grant number AGS-1702827. All CMIP data were acquired from Earth System Grid Federation (ESGF) node hosted by Lawrence Livermore National Laboratory (LLNL). The authors express special thanks to all of the modeling groups who make CMIP data available and two anonymous reviewers for helpful comments. SMK and HK were supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2016R1A1A3A04005520). AGP was supported by the Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling Program of the U.S. Department of Energy’s Office of Biological & Environmental Research (BER) via NSF IA 1844590; NCAR is sponsored by the National Science Foundation (NSF) under Cooperative Agreement No. 1947282. AD’s work was supported by the National Science Foundation Paleo Perspective on Climate Change (P2C2) Grant number AGS-1702827. All CMIP data were acquired from Earth System Grid Federation (ESGF) node hosted by Lawrence Livermore National Laboratory (LLNL). The authors express special thanks to all of the modeling groups who make CMIP data available and two anonymous reviewers for helpful comments.
Sources of information: Directorio de Producción Científica Scopus