Integrating remote sensing data with WRF model for improved 2-m temperature and humidity simulations in China

doi:10.1016/j.dynatmoce.2019.101127

	Integrating remote sensing data with WRF model for improved 2-m temperature and humidity simulations in China
	Yan, Dongdong 4; Liu, Tianya 5; Dong, Wenjie 6; Liao, Xiaohan 1; Luo, Siqiong 7; Wu, Kai 3; Zhu, Xian 6; Zheng, Zhiyuan 6; Wen, Xiaohang 2,5
刊名	DYNAMICS OF ATMOSPHERES AND OCEANS
	2020-03-01
卷号	89 页码:15
关键词	WRF model MODIS-NDVI Temperature Specific humidity
ISSN号	0377-0265
DOI	10.1016/j.dynatmoce.2019.101127
通讯作者	Wen, Xiaohang(wxh@cuit.edu.cn)
英文摘要	The default green vegetation fraction (GVF) in the Weather Research and Forecasting (WRF) Model version 3.7.1 was derived between 1985 and 1990 from the 1990s Normalized Difference Vegetation Index (NDVI) achieved from the NOAA Advanced Very High Resolution Radiometer (AVHRR), and its representation is deteriorating when used to simulate recent weather and climate events. In this study, we applied in WRF v3.7.1 the updated GVF estimated by the real-time NDVI of the Moderate Resolution Imaging Spectroradiometer (MODIS) data to provide a better representation of the prescribed surface GVF condition. A one-year simulation was carried out in China, and the simulated 2-m air temperature and specific humidity were compared between the WRF model control experiment that employs the default GVF data (WRF-CTL), the WRF simulations with updated GVF (WRF-MODIS), and the observations from 824 weather stations in China. Results are significantly improved for both the 2-m air temperature and the specific humidity by WRF-MODIS, which has effectively reproduced the observed pattern and increased the correlation coefficient between the model simulations and observations. The RMSE and bias of specific humidity are also reduced in WRF-MODIS. In general, the real-time MODIS-NDVI based GVF reflected the realistic increase of vegetation cover in China when comparing to the WRF default GVF, and also provided a more accurate seasonal variation for the simulated year of 2009. As a result, the WRF-MODIS simulation significantly improves its representation in the simulated 2-m air temperature and specific humidity, both in spatial distributions and seasonal variations, due to the GVF's great contribution in modulating the coupled land-atmosphere interactions.
资助项目	National Key Research and Development Program of China[2016YFA0602704] ; National Key Research and Development Program of China[2016YFA0602703] ; National Natural Science Foundation of China[41975096] ; National College Students' Innovation and Entrepreneurship Training Program[201810621019]
WOS关键词	FRACTIONAL VEGETATION COVER ; SURFACE-HYDROLOGY MODEL ; URBAN CANOPY MODEL ; DATA ASSIMILATION ; HEAT-ISLAND ; SOIL-MOISTURE ; PART I ; LAND ; CLIMATE ; SYSTEM
WOS研究方向	Geochemistry & Geophysics ; Meteorology & Atmospheric Sciences ; Oceanography
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000521515100003
资助机构	National Key Research and Development Program of China ; National Natural Science Foundation of China ; National College Students' Innovation and Entrepreneurship Training Program
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/133225]
专题	中国科学院地理科学与资源研究所
通讯作者	Wen, Xiaohang
作者单位	1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China 2.China Meteorol Adm, Shenyang Inst Atmospher Environm, Shenyang 110116, Peoples R China 3.Univ Calif Davis, Dept Land Air & Water Resources, Davis, CA 95616 USA 4.Beijing Normal Univ, State Key Lab Earth Surface Proc & Resource Ecol, Beijing 100875, Peoples R China 5.Chengdu Univ Informat Technol, Sch Atmospher Sci, Plateau Atmosphere & Environm Key Lab Sichuan Pro, Chengdu 610225, Peoples R China 6.Sun Yat Sen Univ, Sch Atmospher Sci, Zhuhai 519082, Peoples R China 7.Chinese Acad Sci, Cold & Arid Reg Environm & Engn Res Inst, Key Lab Land Surface Proc & Climate Change Cold &, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Yan, Dongdong,Liu, Tianya,Dong, Wenjie,et al. Integrating remote sensing data with WRF model for improved 2-m temperature and humidity simulations in China[J]. DYNAMICS OF ATMOSPHERES AND OCEANS,2020,89:15.
APA	Yan, Dongdong.,Liu, Tianya.,Dong, Wenjie.,Liao, Xiaohan.,Luo, Siqiong.,...&Wen, Xiaohang.(2020).Integrating remote sensing data with WRF model for improved 2-m temperature and humidity simulations in China.DYNAMICS OF ATMOSPHERES AND OCEANS,89,15.
MLA	Yan, Dongdong,et al."Integrating remote sensing data with WRF model for improved 2-m temperature and humidity simulations in China".DYNAMICS OF ATMOSPHERES AND OCEANS 89(2020):15.