气候变化领域集成服务门户(CCPortal): The value of satellite observations in the analysis and short-range prediction of Asian dust

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DOI	10.5194/acp-19-987-2019
	The value of satellite observations in the analysis and short-range prediction of Asian dust
	Benedetti A.; Di Giuseppe F.; Jones L.; Peuch V.-H.; Rémy S.; Zhang X.
发表日期	2019
ISSN	16807316
起始页码	987
结束页码	998
卷号	19 期号:2
英文摘要	Asian dust is a seasonal meteorological phenomenon which affects east Asia, and has severe consequences on the air quality of China, North and South Korea and Japan. Despite the continental extent, the prediction of severe episodes and the anticipation of their consequences is challenging. Three 1-year experiments were run to assess the skill of the model of the European Centre for Medium-Range Weather Forecasts (ECMWF) in monitoring Asian dust and understand its relative contribution to the aerosol load over China. Data used were the Moderate Resolution Imaging Spectroradiometer (MODIS) Dark Target and the Deep Blue aerosol optical depth (AOD). In particular the experiments aimed at understanding the added value of data assimilation runs over a model run without any aerosol data. The year 2013 was chosen as representative of the availability of independent AOD data from two established ground-based networks (AERONET, Aerosol Robotic Network, and CARSNET, China Aerosol Remote Sensing Network), which could be used to evaluate experiments. Particulate matter (PM) data from the China Environmental Protection Agency were also used in the evaluation. Results show that the assimilation of satellite AOD data is beneficial to predict the extent and magnitude of desert dust events and to improve the short-range forecast of such events. The availability of observations from the MODIS Deep Blue algorithm over bright surfaces is an asset, allowing for a better localization of the sources and definition of the dust events. In general both experiments constrained by data assimilation perform better than the unconstrained experiment, generally showing smaller normalized mean bias and fractional gross error with respect to the independent verification datasets. The impact of the assimilated satellite observations is larger at analysis time, but lasts into the forecast up to 48 h. The performance of the global model in terms of particulate matter does not show the same degree of skill as the performance in terms of optical depth. Despite this, the global model is able to capture some regional pollution patterns. This indicates that the global model analyses may be used as boundary conditions for regional air quality models at higher resolution, enhancing their performance in situations in which part of the pollution may have originated from large-scale mechanisms. While assimilation is not a substitute for model development and characterization of the emission sources, results indicate that it can play a role in delivering improved monitoring of Asian dust optical depth. © Author(s) 2019.
语种	英语
scopus关键词	aerosol; atmospheric modeling; data assimilation; dust; MODIS; monitoring; optical depth; weather forecasting; China
来源期刊	Atmospheric Chemistry and Physics
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/144698
作者单位	European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, United Kingdom; Institut Pierre-Simon Laplace, CNRS/Sorbonne Université, Paris, France; State Key Laboratory of Severe Weather and Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing, China; Center for Excellence in Regional Atmospheric Environment, IUE, CAS, Beijing, China
推荐引用方式 GB/T 7714	Benedetti A.,Di Giuseppe F.,Jones L.,et al. The value of satellite observations in the analysis and short-range prediction of Asian dust[J],2019,19(2).
APA	Benedetti A.,Di Giuseppe F.,Jones L.,Peuch V.-H.,Rémy S.,&Zhang X..(2019).The value of satellite observations in the analysis and short-range prediction of Asian dust.Atmospheric Chemistry and Physics,19(2).
MLA	Benedetti A.,et al."The value of satellite observations in the analysis and short-range prediction of Asian dust".Atmospheric Chemistry and Physics 19.2(2019).