当前位置： 首页»科研成果» 2013 MODIS-driven estimation of terrestrial latent heat flux in China based on a modified Priestley–Taylor algorithm 姚云军、梁顺林、程洁、贾坤、赵祥

 

Yunjun Yao^a,b, Shunlin Liang^a,b,c, Jie Cheng^a,b, Shaomin Liu^d, Joshua B. Fisher^e, Xudong Zhang^f, Kun Jia ^a,b, Xiang Zhao^a,b, Qiming Qin^g, Bin Zhao^h, Shijie Hanⁱ, Guangsheng Zhou^j, Guoyi Zhou^k, Yuelin Li^k, Shaohua Zhao^l

 

^a State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and Institute of Remote Sensing Applications, CAS, China

^b College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China

^c Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA

^d State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China

^e Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA

^f The Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China

^g Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China

^h Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Fudan University, Shanghai 200433, China

ⁱ Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China

^j Laboratory of Quantitative Vegetation Ecology, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China

^k South China Botanic Garden, Chinese Academy of Sciences, Guangzhou 510650, China

^l Ministry of Environmental Protection, Environmental Satellite Center, Beijing 100094, China

 

ABSTRACT

Because of China's large size, satellite observations are necessary for estimation of the land surface latent heat flux (LE). We describe here a satellite-driven Priestley–Taylor (PT)-based algorithm constrained by the Normalized Difference Vegetation Index (NDVI) and Apparent Thermal Inertia (ATI) derived from temperature change over time. We compare to the satellite-driven PT-based approach, PT-JPL, and validate both models using data collected from 16 eddy covariance flux towers in China. Like PT-JPL, our proposed algorithm avoids the computational complexities of aerodynamic resistance parameters. We run the algorithms with monthly Moderate Resolution Imaging Spectroradiometer (MODIS) products (0.05° resolution), including albedo, Land Surface Temperature (LST), surface emissivity, and NDVI; and, Insolation from the Japan Aerospace Exploration Agency (JAXA). We find good agreement between our estimates of monthly LE and field-measured LE, with respective Root Mean Square Error (RMSE) and bias differences of 12.5 W m−2 and −6.4 W m−2. As compared with PT-JPL, our proposed algorithm has higher correlations with ground-measurements. Between 2001 and 2010, LE shows generally negative trends in most regions of China, though positive LE trends occur over 39% of the region, primarily in Northeast, North and South China. Our results indicate that the variations of terrestrial LE are responding to large-scale droughts and afforestation caused by human activity with direct links to terrestrial energy exchange, both spatially and temporally.

 

KEY WORDS: Latent heat flux; Evapotranspiration; Priestley–Taylor; MODIS; China

 

PUBLISHED IN: AGRICULTURAL AND FOREST METEOROLOGY, 2013, 171-172: 187-202.

 

SOURCE: http://www.sciencedirect.com/science/article/pii/S016819231200353X