气候变化领域集成服务门户(CCPortal): Data Assimilation for Climate Research: Model Parameter Estimation of Large-Scale Condensation Scheme

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DOI	10.1029/2019JD031304
	Data Assimilation for Climate Research: Model Parameter Estimation of Large-Scale Condensation Scheme
	Kotsuki S.; Sato Y.; Miyoshi T.
发表日期	2020
ISSN	2169897X
卷号	125 期号:1
英文摘要	This study proposes using data assimilation (DA) for climate research as a tool for optimizing model parameters objectively. Mitigating radiation bias is very important for climate change assessments with general circulation models. With the Nonhydrostatic ICosahedral Atmospheric Model (NICAM), this study estimated an autoconversion parameter in a large-scale condensation scheme. We investigated two approaches to reducing radiation bias: examining useful satellite observations for parameter estimation and exploring the advantages of estimating spatially varying parameters. The parameter estimation accelerated autoconversion speed when we used liquid water path, outgoing longwave radiation, or outgoing shortwave radiation (OSR). Accelerated autoconversion reduced clouds and mitigated overestimated OSR bias of the NICAM. An ensemble-based DA with horizontal localization can estimate spatially varying parameters. When liquid water path was used, the local parameter estimation resulted in better cloud representations and improved OSR bias in regions where shallow clouds are dominant. ©2020. The Authors.
英文关键词	data assimilation; global climate model; large-scale condensation; liquid water path; parameter estimation; radiation
语种	英语
来源期刊	Journal of Geophysical Research: Atmospheres
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/186250
作者单位	RIKEN Center for Computational Science, Kobe, Japan; Center for Center for Environmental Remote Sensing, Chiba University, Chiba, Japan; PRESTO, Japan Science and Technology Agency, Chiba, Japan; RIKEN interdisciplinary Theoretical and Mathematical Sciences Program, Kobe, Japan; RIKEN Cluster for Pioneering Research, Kobe, Japan; Department of Earth and Planetary Sciences, Faculty of Science, Hokkaido University, Sapporo, Japan; Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan; Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, United States
推荐引用方式 GB/T 7714	Kotsuki S.,Sato Y.,Miyoshi T.. Data Assimilation for Climate Research: Model Parameter Estimation of Large-Scale Condensation Scheme[J],2020,125(1).
APA	Kotsuki S.,Sato Y.,&Miyoshi T..(2020).Data Assimilation for Climate Research: Model Parameter Estimation of Large-Scale Condensation Scheme.Journal of Geophysical Research: Atmospheres,125(1).
MLA	Kotsuki S.,et al."Data Assimilation for Climate Research: Model Parameter Estimation of Large-Scale Condensation Scheme".Journal of Geophysical Research: Atmospheres 125.1(2020).