Impact of Lateral Boundary Errors on the Simulation of Clouds with a Nonhydrostatic Regional Climate Model

Junya Uchida Atmosphere and Ocean Research Institute, University of Tokyo, Chiba, Japan

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Masato Mori Research Center for Advanced Science and Technology, University of Tokyo, Tokyo, Japan

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Masayuki Hara Center for Environmental Science in Saitama, Saitama, Japan

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Masaki Satoh Atmosphere and Ocean Research Institute, University of Tokyo, Chiba, Japan

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Daisuke Goto National Institute for Environmental Studies, Ibaraki, Japan

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Takahito Kataoka Atmosphere and Ocean Research Institute, University of Tokyo, Chiba, Japan

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Kentaroh Suzuki Atmosphere and Ocean Research Institute, University of Tokyo, Chiba, Japan

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Teruyuki Nakajima Earth Observation Research Center, Japan Aerospace Exploration Agency (JAXA), Ibaraki, Japan

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Abstract

A nonhydrostatic, regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible nonhydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with horizontal grid intervals of 14, 28, and 56 km in the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to the unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extratropical cyclones and orographic precipitation are not severely affected. It was concluded that the errors of the precipitation distribution are not due to the difference of the model configurations but rather to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.

© 2017 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: Junya Uchida, junya@aori.u-tokyo.ac.jp

Abstract

A nonhydrostatic, regional climate limited-area model (LAM) was used to analyze lateral boundary condition (LBC) errors and their influence on the uncertainties of regional models. Simulations using the fully compressible nonhydrostatic LAM (D-NICAM) were compared against the corresponding global quasi-uniform-grid Nonhydrostatic Icosahedral Atmospheric Model (NICAM) and a stretched-grid counterpart (S-NICAM). By this approach of sharing the same dynamical core and physical schemes, possible causes of model bias and LBC errors are isolated. The simulations were performed for a 395-day period from March 2011 through March 2012 with horizontal grid intervals of 14, 28, and 56 km in the region of interest. The resulting temporal mean statistics of the temperatures at 500 hPa were generally well correlated between the global and regional simulations, indicating that LBC errors had a minor impact on the large-scale flows. However, the time-varying statistics of the surface precipitation showed that the LBC errors lead to the unpredictability of convective precipitation, which affected the mean statistics of the precipitation distributions but induced only minor influences on the large-scale systems. Specifically, extratropical cyclones and orographic precipitation are not severely affected. It was concluded that the errors of the precipitation distribution are not due to the difference of the model configurations but rather to the uncertainty of the system itself. This study suggests that applications of ensemble runs, internal nudging, or simulations with longer time scales are needed to obtain more statistically significant results of the precipitation distribution in regional climate models.

© 2017 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: Junya Uchida, junya@aori.u-tokyo.ac.jp
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