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Title: Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems

Abstract

Accurate estimation of latent heat flux (LE) is critical in characterizing semiarid ecosystems. Many LE algorithms have been developed during the past few decades. However, the algorithms have not been directly compared, particularly over global semiarid ecosystems. In this paper, we evaluated the performance of five LE models over semiarid ecosystems such as grassland, shrub, and savanna using the Fluxnet dataset of 68 eddy covariance (EC) sites during the period 2000–2009. We also used a modern-era retrospective analysis for research and applications (MERRA) dataset, the Normalized Difference Vegetation Index (NDVI) and Fractional Photosynthetically Active Radiation (FPAR) from the moderate resolution imaging spectroradiometer (MODIS) products; the leaf area index (LAI) from the global land surface satellite (GLASS) products; and the digital elevation model (DEM) from shuttle radar topography mission (SRTM30) dataset to generate LE at region scale during the period 2003–2006. The models were the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL), the modified satellite-based Priestley–Taylor LE algorithm (MS-PT), and the semi-empirical Penman LE algorithm (UMD). Direct comparison with ground measured LE showed the PT-JPL and MS-PT algorithms had relative high performance overmore » semiarid ecosystems with the coefficient of determination (R2) ranging from 0.6 to 0.8 and root mean squared error (RMSE) of approximately 20 W/m2. Empirical parameters in the structure algorithms of MOD16 and RRS, and calibrated coefficients of the UMD algorithm may be the cause of the reduced performance of these LE algorithms with R2 ranging from 0.5 to 0.7 and RMSE ranging from 20 to 35 W/m2 for MOD16, RRS and UMD. Sensitivity analysis showed that radiation and vegetation terms were the dominating variables affecting LE Fluxes in global semiarid ecosystem.« less

Authors:
 [1];  [2];  [1];  [1];  [3];  [4];  [5];  [1]; ORCiD logo [1];  [1]
  1. Beijing Normal Univ. (China)
  2. Michigan State Univ., East Lansing, MI (United States)
  3. Beijing Normal Univ. (China); Univ. of Maryland, College Park, MD (United States)
  4. Beijing Normal Univ. (China); Chinese Academy of Sciences (CAS), Beijing (China); Univ. of Chinese Academy of Sciences, Beijing (China)
  5. China Petroleum Pipeline Bureau, Beijing (China)
Publication Date:
Research Org.:
Oregon State Univ., Corvallis, OR (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER)
OSTI Identifier:
1240607
Grant/Contract Number:  
FG02-04ER63917
Resource Type:
Accepted Manuscript
Journal Name:
Remote Sensing
Additional Journal Information:
Journal Volume: 7; Journal Issue: 12; Journal ID: ISSN 2072-4292
Publisher:
MDPI
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; latent heat flux; grassland ecosystems; revised remote sensing based Penman-Monteith LE algorithm; MOD16; modified satellite-based Priestley-Taylor LE algorithm; semi-empirical Penman LE algorithm

Citation Formats

Feng, Fei, Chen, Jiquan, Li, Xianglan, Yao, Yunjun, Liang, Shunlin, Liu, Meng, Zhang, Nannan, Guo, Yang, Yu, Jian, and Sun, Minmin. Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems. United States: N. p., 2015. Web. doi:10.3390/rs71215853.
Feng, Fei, Chen, Jiquan, Li, Xianglan, Yao, Yunjun, Liang, Shunlin, Liu, Meng, Zhang, Nannan, Guo, Yang, Yu, Jian, & Sun, Minmin. Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems. United States. https://doi.org/10.3390/rs71215853
Feng, Fei, Chen, Jiquan, Li, Xianglan, Yao, Yunjun, Liang, Shunlin, Liu, Meng, Zhang, Nannan, Guo, Yang, Yu, Jian, and Sun, Minmin. Wed . "Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems". United States. https://doi.org/10.3390/rs71215853. https://www.osti.gov/servlets/purl/1240607.
@article{osti_1240607,
title = {Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems},
author = {Feng, Fei and Chen, Jiquan and Li, Xianglan and Yao, Yunjun and Liang, Shunlin and Liu, Meng and Zhang, Nannan and Guo, Yang and Yu, Jian and Sun, Minmin},
abstractNote = {Accurate estimation of latent heat flux (LE) is critical in characterizing semiarid ecosystems. Many LE algorithms have been developed during the past few decades. However, the algorithms have not been directly compared, particularly over global semiarid ecosystems. In this paper, we evaluated the performance of five LE models over semiarid ecosystems such as grassland, shrub, and savanna using the Fluxnet dataset of 68 eddy covariance (EC) sites during the period 2000–2009. We also used a modern-era retrospective analysis for research and applications (MERRA) dataset, the Normalized Difference Vegetation Index (NDVI) and Fractional Photosynthetically Active Radiation (FPAR) from the moderate resolution imaging spectroradiometer (MODIS) products; the leaf area index (LAI) from the global land surface satellite (GLASS) products; and the digital elevation model (DEM) from shuttle radar topography mission (SRTM30) dataset to generate LE at region scale during the period 2003–2006. The models were the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL), the modified satellite-based Priestley–Taylor LE algorithm (MS-PT), and the semi-empirical Penman LE algorithm (UMD). Direct comparison with ground measured LE showed the PT-JPL and MS-PT algorithms had relative high performance over semiarid ecosystems with the coefficient of determination (R2) ranging from 0.6 to 0.8 and root mean squared error (RMSE) of approximately 20 W/m2. Empirical parameters in the structure algorithms of MOD16 and RRS, and calibrated coefficients of the UMD algorithm may be the cause of the reduced performance of these LE algorithms with R2 ranging from 0.5 to 0.7 and RMSE ranging from 20 to 35 W/m2 for MOD16, RRS and UMD. Sensitivity analysis showed that radiation and vegetation terms were the dominating variables affecting LE Fluxes in global semiarid ecosystem.},
doi = {10.3390/rs71215853},
journal = {Remote Sensing},
number = 12,
volume = 7,
place = {United States},
year = {Wed Dec 09 00:00:00 EST 2015},
month = {Wed Dec 09 00:00:00 EST 2015}
}

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