气候变化领域集成服务门户(CCPortal): Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests

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DOI	10.1016/j.jag.2019.04.009
	Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests
	Gomis-Cebolla J.; Jimenez J.C.; Sobrino J.A.; Corbari C.; Mancini M.
发表日期	2019
ISSN	15698432
起始页码	280
结束页码	294
卷号	80
英文摘要	Evapotranspiration (ET) is considered a key variable in the understanding of the Amazonian tropical forests and their response to climate change. Remote-Sensing (RS) based evapotranspiration models are presented as a feasible means in order to provide accurate spatially-distributed ET estimates over this region. In this work, the performance of four commonly used ET RS models was evaluated over Amazonia using Moderate Resolution Imaging Spectroradiometer (MODIS) data. RS models included i) Priestley-Taylor Jet Propulsion Laboratory (PT-JPL), ii) Penman-Monteith MODIS operative parametrization (PM-Mu), iii) Surface Energy Balance System (SEBS), and iv) Satellite Application Facility on Land Surface Analysis (LSASAF). These models were forced using two ancillary meteorological data sources: i) in-situ data extracted from Large-Scale Biosphere-Atmosphere Experiment (LBA) stations (scenario I), and ii) three reanalysis datasets (scenario II), including Modern-Era Retrospective analysis for Research and Application (MERRA-2), European Centre for Medium-range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim), and Global Land Assimilation System (GLDAS-2). Performance of algorithms under the two scenarios was validated using in-situ eddy-covariance measurements. For scenario I, PT-JPL provided the best agreement with in-situ ET observations (RMSE = 0.55 mm/day, R = 0.88). Neglecting water canopy evaporation resulted in an underestimation of ET measurements for LSASAF. SEBS performance was similar to that of PT-JPL, nevertheless SEBS estimates were limited by the continuous cloud cover of the region. A physically-based ET gap-filling method was used in order to alleviate this issue. PM-Mu tended to overestimate in-situ ET observations. For scenario II, quality assessment of reanalysis input data demonstrated that MERRA-2, ERA-Interim and GLDAS-2 contain biases that impact model performance. In particular, biases in radiation inputs were found the main responsible of the observed biases in ET estimates. For the region, MERRA-2 tends to overestimate daily net radiation and incoming solar radiation. ERA-Interim tends to underestimate both variables, and GLDAS tends to overestimate daily radiation while underestimating incoming solar radiation. Discrepancies amongst these reanalysis inputs generally explain the observed discrepancies in model spatial and temporal patterns. © 2019 Elsevier B.V.
英文关键词	Amazonian tropical forests; MODIS; Reanalysis; Terrestrial evapotranspiration
语种	英语
scopus关键词	algorithm; eddy covariance; evapotranspiration; feasibility study; meteorology; MODIS; remote sensing; satellite data; solar radiation; tropical forest; Amazonia
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156454
作者单位	Global Change Unit, Image Processing Laboratory, University of Valencia, Paterna, Valencia, 46010, Spain; DICA Politecnico di Milano, Piazza Leonardo da Vinci, 32, Milano, 20133, Italy
推荐引用方式 GB/T 7714	Gomis-Cebolla J.,Jimenez J.C.,Sobrino J.A.,et al. Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests[J],2019,80.
APA	Gomis-Cebolla J.,Jimenez J.C.,Sobrino J.A.,Corbari C.,&Mancini M..(2019).Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests.International Journal of Applied Earth Observation and Geoinformation,80.
MLA	Gomis-Cebolla J.,et al."Intercomparison of remote-sensing based evapotranspiration algorithms over amazonian forests".International Journal of Applied Earth Observation and Geoinformation 80(2019).