DOI: 10.1002/2017MS001154
Scopus记录号: 2-s2.0-85041547907
论文题名: Precipitation Dynamical Downscaling Over the Great Plains
作者: Hu X ; -M ; , Xue M ; , McPherson R ; A ; , Martin E ; , Rosendahl D ; H ; , Qiao L
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2018
卷: 10, 期: 2 起始页码: 421
结束页码: 447
语种: 英语
英文关键词: Discrete cosine transforms
; Dynamics
; Weather forecasting
; Discrete Cosine Transform(DCT)
; Dynamic downscaling
; Precipitation data
; Regional climate projections
; Spectral nudging
; Synoptic scale circulation
; Warm season precipitation
; Weather Research and Forecast models
; Climate models
; cumulus
; discrete choice analysis
; downscaling
; precipitation (climatology)
; regional climate
; spatial distribution
; spectral analysis
; watershed
; Great Plains
; United States
英文摘要: Detailed, regional climate projections, particularly for precipitation, are critical for many applications. Accurate precipitation downscaling in the United States Great Plains remains a great challenge for most Regional Climate Models, particularly for warm months. Most previous dynamic downscaling simulations significantly underestimate warm-season precipitation in the region. This study aims to achieve a better precipitation downscaling in the Great Plains with the Weather Research and Forecast (WRF) model. To this end, WRF simulations with different physics schemes and nudging strategies are first conducted for a representative warm season. Results show that different cumulus schemes lead to more pronounced difference in simulated precipitation than other tested physics schemes. Simply choosing different physics schemes is not enough to alleviate the dry bias over the southern Great Plains, which is related to an anticyclonic circulation anomaly over the central and western parts of continental U.S. in the simulations. Spectral nudging emerges as an effective solution for alleviating the precipitation bias. Spectral nudging ensures that large and synoptic-scale circulations are faithfully reproduced while still allowing WRF to develop small-scale dynamics, thus effectively suppressing the large-scale circulation anomaly in the downscaling. As a result, a better precipitation downscaling is achieved. With the carefully validated configurations, WRF downscaling is conducted for 1980–2015. The downscaling captures well the spatial distribution of monthly climatology precipitation and the monthly/yearly variability, showing improvement over at least two previously published precipitation downscaling studies. With the improved precipitation downscaling, a better hydrological simulation over the trans-state Oologah watershed is also achieved. © 2018. The Authors. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75644
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: Center for Analysis and Prediction of Storms, University of Oklahoma, Norman, OK, United States; School of Meteorology, University of Oklahoma, Norman, OK, United States; South Central Climate Science Center, University of Oklahoma, Norman, OK, United States; Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK, United States; Department of Natural Resource Ecology and Management, Oklahoma State University, Stillwater, OK, United States
Recommended Citation:
Hu X,-M,, Xue M,et al. Precipitation Dynamical Downscaling Over the Great Plains[J]. Journal of Advances in Modeling Earth Systems,2018-01-01,10(2)