气候变化领域集成服务门户(CCPortal): Integrating Remote-Sensing and Assimilation Data to Improve Air Temperature on Hot Weather in East China

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DOI	10.3390/rs13173409
	Integrating Remote-Sensing and Assimilation Data to Improve Air Temperature on Hot Weather in East China
	Li, Suosuo; Liu, Yuanpu; Pan, Yongjie; Li, Zhe; Lyu, Shihua
通讯作者	Liu, YP (通讯作者)，China Meteorol Adm, Inst Arid Meteorol, Key Lab Arid Climat Change & Reduct Disaster Gans, Lanzhou 730020, Peoples R China.
发表日期	2021
EISSN	2072-4292
卷号	13 期号:17
英文摘要	Land-surface characteristics (LSCs) and land-soil moisture conditions can modulate energy partition at the land surface, impact near-surface atmosphere conditions, and further affect land-atmosphere interactions. This study investigates the effect of land-surface-characteristic parameters (LSCPs) including albedo, leaf-area index (LAI), and soil moisture (SM) on hot weather by in East China using the numerical model. Simulations using the Weather Research and Forecasting (WRF) Model were conducted for a hot weather event with a high spatial resolution of 1 km in domain 3 by using ERA-Interim forcing fields on 20 July 2017 until 16:00 UTC on 25 July 2017. The satellite-based albedo and LAI, and assimilation-based soil-moisture data of high temporal-spatial resolution, which are more accurate to match fine weather forecasts and high-resolution simulations, were used to update the default LSCPs. A control simulation with the default LSCPs (WRF_CTL), a main sensitivity simulation with the updated LSCP albedo, LAI and SM (WRF_CHAR), and a series of other sensitivity simulations with one or two updated LSCPs were performed. Results show that WRF_CTL could reproduce the spatial distribution of hot weather, but overestimated air temperature (Ta) and maximal air temperature (Tamax) with a warming bias of 1.05 and 1.32 degrees C, respectively. However, the WRF_CHAR simulation reduced the warming bias, and improved the simulated Ta and Tamax with reducing relative biases of 33.08% and 29.24%, respectively. Compared to the WRF_CTL, WRF_CHAR presented a negative sensible heat-flux difference, positive latent heat flux, and net radiation difference of the area average. LSCPs modulated the partition of available land-surface energy and then changed the air temperature. On the basis of statistical-correlation analysis, the soil moisture of the top 10 cm is the main factor to improve warming bias on hot weather in East China.
关键词	URBAN HEAT-ISLAND LEAF-AREA INDEX SOIL-MOISTURE INITIALIZATION PART I MODEL IMPACT PREDICTION UNCERTAINTY PRODUCT CLIMATE
英文关键词	land-surface characteristics; hot weather; air temperature; WRF model; East China
语种	英语
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
WOS类目	Environmental Sciences ; Geosciences, Multidisciplinary ; Remote Sensing ; Imaging Science & Photographic Technology
WOS记录号	WOS:000694503700001
来源期刊	REMOTE SENSING
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254519
作者单位	[Li, Suosuo; Pan, Yongjie; Li, Zhe] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Land Surface Proc & Climate Change Cold &, Lanzhou 730000, Peoples R China; [Liu, Yuanpu] China Meteorol Adm, Inst Arid Meteorol, Key Lab Arid Climat Change & Reduct Disaster Gans, Lanzhou 730020, Peoples R China; [Lyu, Shihua] Chengdu Univ Informat Technol, Sch Atmospher Sci, Plateau Atmosphere & Environm Key Lab Sichuan Pro, Chengdu 610225, Peoples R China
推荐引用方式 GB/T 7714	Li, Suosuo,Liu, Yuanpu,Pan, Yongjie,et al. Integrating Remote-Sensing and Assimilation Data to Improve Air Temperature on Hot Weather in East China[J]. 中国科学院西北生态环境资源研究院,2021,13(17).
APA	Li, Suosuo,Liu, Yuanpu,Pan, Yongjie,Li, Zhe,&Lyu, Shihua.(2021).Integrating Remote-Sensing and Assimilation Data to Improve Air Temperature on Hot Weather in East China.REMOTE SENSING,13(17).
MLA	Li, Suosuo,et al."Integrating Remote-Sensing and Assimilation Data to Improve Air Temperature on Hot Weather in East China".REMOTE SENSING 13.17(2021).