气候变化领域集成服务门户(CCPortal): Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking

CCPortal

DOI	10.1007/s00382-018-4294-0
	Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking
	Chang W.; Wang J.; Marohnic J.; Kotamarthi V.R.; Moyer E.J.
发表日期	2020
ISSN	0930-7575
起始页码	175
结束页码	192
卷号	55
英文摘要	Dynamical downscaling with high-resolution regional climate models may offer the possibility of realistically reproducing precipitation and weather events in climate simulations. As resolutions fall to order kilometers, the use of explicit rather than parametrized convection may offer even greater fidelity. However, these increased resolutions both allow and require increasingly complex diagnostics for evaluating model fidelity. In this study we focus on precipitation evaluation and analyze five 2-month-long dynamically downscaled model runs over the continental United States that employ different convective and microphysics parameterizations, including one high-resolution convection-permitting simulation. All model runs use the Weather Research and Forecasting Model driven by National Center for Environmental Prediction reanalysis data. We show that employing a novel rainstorm identification and tracking algorithm that allocates essentially all rainfall to individual precipitation events (Chang et al. in J Clim 29(23):8355–8376, 2016) allows new insights into model biases. Results include that, at least in these runs, model wet bias is driven by excessive areal extent of individual precipitating events, and that the effect is time-dependent, producing excessive diurnal cycle amplitude. This amplified cycle is driven not by new production of events but by excessive daytime enlargement of long-lived precipitation events. We further show that in the domain average, precipitation biases appear best represented as additive offsets. Of all model configurations evaluated, convection-permitting simulations most consistently reduced biases in precipitation event characteristics. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.
英文关键词	Convection permitting simulation; Parameterization; Precipitation; Rainstorm tracking
语种	英语
scopus关键词	algorithm; atmospheric convection; climate modeling; computer simulation; precipitation (climatology); rainstorm; regional climate; weather forecasting; United States
来源期刊	Climate Dynamics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/145419
作者单位	Department of Mathematical Sciences, University of Cincinnati, Cincinnati, OH, United States; Environmental Science Division, Argonne National Laboratory, Lemont, IL, United States; Center for Robust Decision Making on Climate and Energy Policy, University of Chicago, Chicago, IL, United States; Department of the Geophysical Sciences, University of Chicago, Chicago, IL, United States
推荐引用方式 GB/T 7714	Chang W.,Wang J.,Marohnic J.,et al. Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking[J],2020,55.
APA	Chang W.,Wang J.,Marohnic J.,Kotamarthi V.R.,&Moyer E.J..(2020).Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking.Climate Dynamics,55.
MLA	Chang W.,et al."Diagnosing added value of convection-permitting regional models using precipitation event identification and tracking".Climate Dynamics 55(2020).