Abstract
Satellite-based vegetation indices (VIs) and Apparent Thermal Inertia (ATI) derived from temperature change provide valuable information for estimating evapotranspiration (LE) and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT) algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. The validation results illustrate that the daily LE can be estimated with the Root Mean Square Error (RMSE) varying from 10.7 W/m2 to 87.6 W/m2, and with the square of correlation coefficient (R2) from 0.41 to 0.89 (p < 0.01). Compared with the Priestley-Taylor-based LE (PT-JPL) algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02). The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.
Highlights
Evapotranspiration (LE) is a major component of the earth’s climate system and global water cycle, and it represents a crucial link between global water, energy and carbon exchanges [1,2,3,4]
Unsaturated soil evaporation can be calculated using an index of soil water deficit and fsm can be acquired from an exponential algorithm of the Apparent Thermal Inertia (ATI), namely, LEs (1 f wet ) f sm f sm (
To evaluate the ability of the modified satellite-based Priestley-Taylor (MS-PT) method to predict the spatial variation in LE, we have validated both MS-PT algorithm and PT-JPL algorithm based on the collected ground-measured data from all flux towers sites
Summary
Evapotranspiration (LE) is a major component of the earth’s climate system and global water cycle, and it represents a crucial link between global water, energy and carbon exchanges [1,2,3,4]. The current Eddy Covariance (ECOR) or Bowen Ratio (BR) systems at flux towers have provided point measurements of terrestrial LE, LE is inherently difficult to measure and predict especially at large spatial scales because sufficient ground observations will never be available [3,4,5]. Satellite-based estimate of temporal and spatial variations of LE is crucial for improving hydrological and agricultural management [6,7,8,9,10]. Advances in satellite-based LE algorithms and remote sensing technology enable estimating terrestrial LE at regional or global scales [7,8,9,10,11,12,13,14,15,16,17,18,19,20,21]. Comprehensive reviews of the historical development and accuracies of in situ and satellite-based LE estimation methods are provided elsewhere [3,5,22]
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