气候变化领域集成服务门户(CCPortal): Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography

CCPortal

DOI	10.1016/j.atmosres.2018.10.004
	Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography
	Carrió D.S.; Homar V.; Wheatley D.M.
发表日期	2019
ISSN	0169-8095
起始页码	186
结束页码	206
卷号	216
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. © 2018
英文关键词	Data assimilation; EnKF; HyMeX; Radar reflectivity; Western mediterranean; WRF-DART
语种	英语
scopus关键词	Coastal zones; Radar; Reflection; Weather information services; Data assimilation; EnKF; HyMeX; Radar reflectivities; Western Mediterranean; WRF-DART; Weather forecasting; algorithm; data assimilation; ensemble forecasting; Kalman filter; radar; weather forecasting; Corse; France; Italy; Mediterranean Region
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/162021
作者单位	Universitat de les Illes Balears, Physics Department, Carretera de Valldemossa km 7.5, Palma de Mallorca, 07122, Spain; Cooperative Institute for Mesoscale Meteorological Studies, University of Oklahoma, NOAA/OAR/National Severe Storms Laboratory, Norman, OK, United States
推荐引用方式 GB/T 7714	Carrió D.S.,Homar V.,Wheatley D.M.. Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography[J],2019,216.
APA	Carrió 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.
MLA	Carrió D.S.,et al."Potential of an EnKF Storm-Scale Data Assimilation System Over Sparse Observation Regions with Complex Orography".Atmospheric Research 216(2019).