Microwave based implementation of two source energy balance model to estimate Evaporation

Friday, 18 December 2015: 12:05
3022 (Moscone West)
Thomas R Holmes1, Wade T Crow2, Christopher Hain3, Martha C. Anderson2 and William P Kustas2, (1)USDA Agricultural Research Service New England Plant, Soil and Water Research Laboratory, East Wareham, MA, United States, (2)USDA ARS, Hydrology and Remote Sensing Lab, Beltsville, MD, United States, (3)Earth System Science Interdisciplinary Center, COLLEGE PARK, MD, United States
There is a clear need for observation-based methodologies to estimate evapotranspiration (ET) at diverse spatial domains. The ALEXI methodology (Atmosphere Land Exchange Inverse) is a thermal-based implementation of the two-source energy balance method and provides one of the most direct estimates of actual ET. A unique aspect of ALEXI is that it integrates measurements at multiple spatial scales. It is used to estimate crop water use (field scale), as an early indicator of agricultural drought (regional scale), and at continental to global scales to study hydrological impacts of climate variations and land-use change.

Up to now, the thermal input to ALEXI has always been based on thermal infrared radiometers, which give the most direct measurement of physical land surface temperature (LST). However, because TIR is blocked by clouds, the dependence on TIR has limited ALEXI to clear sky conditions and made the accuracy dependant on the efficacy of cloud masking. Passive microwave (MW) methods to estimate LST could help to overcome this limitation and provide a more cloud tolerant alternative to existing TIR-based techniques. This paper builds on recent progress in characterizing the main structural differences between TIR LST and MW Ka-band observations, the MW frequency that is most suitable for LST sensing. By accounting for differences in diurnal timing (phase lag with solar noon), amplitude, and emissivity we constructed a MW-based LST dataset that matches the diurnal characteristics of the TIR-based LSA SAF LST record. This new global dataset of MW-based LST currently spans the period of 2003-2013 with a 0.25 degree spatial- and 15-minute temporal resolution.

As a first test of the functioning of this MW-based LST within the ALEXI framework we ran two parallel implementations of ALEXI: one with the TIR-LST from geostationary MSG satellite as in previous work, and one with the new MW-LST. The MW-LST is treated exactly as the TIR-based LST to calculate the temperature rate of change in the morning hours – no other changes to the ALEXI framework are made. This paper presents an analysis of the clear sky ET estimates for the years 2003-2013. We will explore the level of agreement between the MW- and TIR-based ET and the utility of the MW-ET to add additional cloud screening capability to TIR observations.