Publications

Sullivan, RC; Cook, DR; Ghate, VP; Kotamarthi, VR; Feng, Y (2019). Improved Spatiotemporal Representativeness and Bias Reduction of Satellite-Based Evapotranspiration Retrievals via Use of In Situ Meteorology and Constrained Canopy Surface Resistance. JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES, 124(2), 342-352.

Abstract
Evapotranspiration (ET) is a key component of the atmospheric and terrestrial water and energy budgets. Satellite-based vegetation index approaches have used remotely sensed vegetation and reanalysis meteorological properties with surface energy balance models to estimate global ET (MOD16 ET). We reconstructed satellite retrievals using in situ meteorology (Argonne-ET) and evaluated them using a dense network of surface turbulent heat flux measurements. Argonne-ET resolves spatial heterogeneity of ET across the U.S. Southern Great Plains that is not well characterized by MOD16; MOD16 ET exhibits spatial autocorrelation (Moran's I significantly >0 in May-Aug.), whereas in situ and Argonne-ET exhibit characteristics of a random spatial process (Moran's I not significantly different from 0). The skill in resolving ET temporal variability is not significantly different between MOD16 and Argonne-ET (correlation coefficient=0.75 and 0.72, respectively). However, the root-mean-square errors were significantly lower for Argonne-ET (36W/m(2)) than MOD16 (43W/m(2)), and MOD16 exhibits substantial bias in annual ET relative to in situ measurements (-38%). This is attributed to overestimation in the dry canopy surface resistance (r(s)) parameterization. Using r(s) constrained to the range of typical measured values, Argonne-ET substantially reduces the bias in the annual ET (+1%). The improved ET estimates are critical for regional water budget analyses. The methodology presented herein also demonstrates the ability to retrieve high temporally resolved (30min; cf. 8-day MOD16) ET that can be used for development of processed-based diagnostics of model biases and to elucidate avenues to improve ET model parameterizations. Plain Language Summary Evapotranspiration (ET), the cumulative quantities of evaporation and plant transpiration, is a leading mechanism, second only to precipitation, for exchange of water between land and the atmosphere, but measurements of ET are limited. Assuming an energy balance between incoming radiation, heat transfer to the ground, heating of the atmosphere, and energy consumed by ET, previous research has estimated global ET distributions using satellite-based remote sensing of vegetation and data-driven simulations (reanalysis) of meteorological conditions. It is shown here that the use of reanalysis meteorology leads to a substantial bias in annual ET over the U.S. Southern Great Plains, but the bias can be greatly reduced by using actual meteorological measurements and constraining vegetation resistance to transpiration to realistic values. Findings presented herein provide an avenue to evaluate and improve modeling of land-atmosphere interactions and provide a methodology for improved estimation of annual ET for analysis of the water budget over land.

DOI:
10.1029/2018JG004744

ISSN:
2169-8953