气候变化领域集成服务门户(CCPortal): Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem

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DOI	10.1016/j.atmosenv.2020.118134
	Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem
	Raman A.; Arellano A.F.; Delle Monache L.; Alessandrini S.; Kumar R.
发表日期	2021
ISSN	1352-2310
卷号	246
英文摘要	We implement and test an analog-based post-processing method to improve short range forecasts of aerosol optical depth (AOD) using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). Model postprocessing of AOD is performed using historical analog forecasts and a Kalman Filter (KF). Analog forecasts are selected from WRF-Chem simulations based on a set of environmental predictors (AOD, wind speed, precipitable water, and particulate matter) that exhibit past values similar to the current forecasts. Space-borne AOD from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard Terra and Aqua satellites corresponding to the analogs are used to build the analog ensemble. This study focuses on a spatial domain covering the AERONET sites in contiguous United States. We use the analog ensemble weighted mean (AN) and Kalman filter analog (KFAN) algorithms, which are both trained using WRF-Chem AOD forecasts for the months of June to August during 2008–2011 and tested during the same months for 2012. Overall, the AOD forecast are more skillful when the forecast errors are corrected using a combination of analogs and Kalman filter in KFAN. This is especially true for the western US where the correlation of AOD with PM2.5, PM10, and surface horizontal wind speed are higher than those for other predictors. In fact, the overall biases in AOD are significantly reduced close to zero, with KFAN AOD being statistically indistinguishable to MODIS. However, both methods show mixed results (albeit still showing overall improvements) in eastern and central U.S., where AOD and its variability are highest. We find that, during the summer, PM is not the only predominant factor driving AOD in these regions, unlike western United States (U.S.) (except New Mexico and Arizona). We note, however, that the quality of the analogs depends on the model's capability to accurately simulate total precipitable water, which in turn influences aerosol sources and sinks. © 2020
关键词	Aerosol optical depth Analog ensemble Kalman filter WRF-Chem
语种	英语
scopus关键词	Aerosols; Kalman filters; Optical properties; Radiometers; Wind; Aerosol optical depths; Moderate resolution imaging spectroradiometer sensors; Particulate Matter; Postprocessing methods; Precipitable water; Total precipitable water; Weather research and forecasting models; Western United States; Weather forecasting; water; AERONET; aerosol; Aqua (satellite); detection method; exploration; forecasting method; MODIS; optical depth; satellite sensor; seasonal variation; spatiotemporal analysis; Terra (satellite); aerosol; air quality; algorithm; Article; biomass; chemistry; circadian rhythm; environmental monitoring; forecasting; Gulf of Mexico; humidity; moisture; optical depth; particulate matter 10; particulate matter 2.5; precipitation; priority journal; radiative forcing; simulation; summer; temperature; United States; water vapor; weather; wind speed; United States; Satellites
来源期刊	ATMOSPHERIC ENVIRONMENT
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/248672
作者单位	Now at Pacific Northwest National Lab, Richland, WA, United States; Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, United States; Scripps Institution of Oceanography, University of California, San Diego, CA, United States; National Center for Atmospheric Research, Research Applications Laboratory, Boulder, CO, United States
推荐引用方式 GB/T 7714	Raman A.,Arellano A.F.,Delle Monache L.,et al. Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem[J],2021,246.
APA	Raman A.,Arellano A.F.,Delle Monache L.,Alessandrini S.,&Kumar R..(2021).Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem.ATMOSPHERIC ENVIRONMENT,246.
MLA	Raman A.,et al."Exploring analog-based schemes for aerosol optical depth forecasting with WRF-Chem".ATMOSPHERIC ENVIRONMENT 246(2021).