Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2018.10.004 |
Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography | |
Carrio, D. S.1; Homar, V.1; Wheatley, D. M.2 | |
2019-02-01 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2019 |
卷号 | 216页码:186-206 |
文章类型 | Article |
语种 | 英语 |
国家 | Spain; USA |
英文摘要 | High-impact weather events over sparse data regions with complex orography, such as the Mediterranean region, remain a challenge for numerical weather prediction. This study evaluates, for the first time, the ability of a multiscale ensemble-based data assimilation system to reproduce a heavy precipitation episode that occurred during the first Special Observation Period (SOP1) of the Hydrological cycle in the Mediterranean Experiment (HyMeX). During the Intense Observation Period (IOP13) from 14 to 15 October 2012, convective maritime activity associated with an advancing cold front affected coastal areas of southern France, Corsica and Italy. With the main objective of improving forecasts of this weather event, a data assimilation (DA) system using the Ensemble Kalman Filter (EnKF) algorithm is implemented. The potential impact of assimilating conventional in situ observations (METAR, aircrafts, buoys and rawinsondes) and single-Doppler reflectivity data to improve numerical representation of growing convective maritime structures that will evolve towards coastal populated areas is evaluated. Results indicate that information provided by both observation sources contribute to initiation and subsequent evolution of convective structures not captured by the conventional runs. Notably, data assimilation experiments produce the best quantitative verification scores for the short range (6-8 h) forecasts of accumulated precipitation. Beyond 6-8 h, data assimilation experiments and those without data assimilation are indistinguishable. Sensitivity experiments, evaluating the impact of increasing the length of the radar data assimilation period, reveal the importance of assimilating high-frequency reflectivity data during a mid-term period (6 h approx.) to better depict deep convective structures initiated over the sea that evolve towards populated coastal areas. |
英文关键词 | Data assimilation EnKF Radar reflectivity HyMeX WRF-DART Western mediterranean |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000452344700017 |
WOS关键词 | KALMAN FILTER ASSIMILATION ; STATIONARY CONVECTIVE SYSTEMS ; SPECIAL OBSERVATION PERIOD ; FLASH-FLOOD EVENT ; BULK PARAMETERIZATION ; EXPLICIT FORECASTS ; RADAR DATA ; ENSEMBLE ; MODEL ; PRECIPITATION |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/38587 |
专题 | 地球科学 |
作者单位 | 1.Univ Illes Balears, Phys Dept, Carretera Valldemossa Km 7-5, Palma De Mallorca 07122, Spain; 2.Univ Oklahoma, Cooperat Inst Mesoscale Meteorol Studies, NOAA OAR Natl Severe Storms Lab, Norman, OK 73019 USA |
推荐引用方式 GB/T 7714 | Carrio, D. S.,Homar, V.,Wheatley, D. M.. Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography[J]. ATMOSPHERIC RESEARCH,2019,216:186-206. |
APA | Carrio, D. S.,Homar, V.,&Wheatley, D. M..(2019).Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography.ATMOSPHERIC RESEARCH,216,186-206. |
MLA | Carrio, D. S.,et al."Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography".ATMOSPHERIC RESEARCH 216(2019):186-206. |
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