Location: Hydrology and Remote Sensing LaboratoryTitle: Microwave implementation of two-source energy balance approach for estimating evapotranspiration
|HOLMES, T. - Goddard Space Flight Center|
|HAIN, C. - Goddard Space Flight Center|
|Kustas, William - Bill|
Submitted to: Hydrology and Earth System Sciences
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/8/2018
Publication Date: 2/23/2018
Citation: Holmes, T., Hain, C., Crow, W.T., Anderson, M.C., Kustas, W.P. 2018. Microwave implementation of two-source energy balance approach for estimating evapotranspiration. Hydrology and Earth System Sciences. 22:1351-1369. https://doi.org/10.5194/hess-22-1351-2018.
Interpretive Summary: The accurate measurement of evaporation from the land surface is critical for monitoring crop water use over large spatial scales. Within the past two decades, considerable progress has been made in estimating land surface evaporation (often referred to as “evapotranspiration” or “ET”) using thermal remote sensing techniques. Such approaches work well in cloud-free conditions, but are hampered even by low-levels of cloud cover (which obscure the land surface in the thermal band). This paper presents a new approach for measuring ET using microwave-based satellite observations which penetrate through clouds under almost all atmospheric conditions. As a result, it provides much better temporal coverage of daily ET variations than existing approaches. In this paper, the new microwave-based approach is introduced, compared to existing thermal-based ET approaches during clear sky conditions, and validated against high-quality ET ground observations. Results demonstrate that this approach is capable of improving our ability to globally monitor the extent, duration and severity of agricultural drought.
Technical Abstract: A newly developed microwave (MW) land surface temperature (LST) product is used to effectively substitute thermal infrared (TIR) based LST in the two-source energy balance approach (TSEB) for estimating ET from space. This TSEB land surface scheme, used in the Atmosphere Land Exchange Inverse (ALEXI) model framework, is an approach that minimizes sensitivity to absolute biases in input records of LST through the analysis of the rate of change in morning LST. It is therefore an important test of the ability to retrieve diurnal temperature information from a constellation of satellites that provide 6-8 observations of Ka-band brightness temperature per location per day. This represents the first ever attempt at a global implementation of ALEXI with MW-based LST and is intended as the first step towards providing all-weather capability to the ALEXI framework. The leveraging of all sky capability of MW sensors is the main motivation of this work, as TIR-based ALEXI is limited to clear sky conditions. The analysis is based on a 9-year long record of ALEXI ET generated with MW-LST as an input, which is compared to an existing implementation of the same framework with thermal infrared based LST. In this study, the MW-LST sampling is restricted to the same clear sky days as in the IR-based implementation to be able to analyse the impact of LST dataset separately from the impact of sampling all-sky conditions. The results show that long-term bulk ET estimates agree with a spatial correlation of 92% for total ET in the Europe/Africa domain and agreement in seasonal (3-month) averages of and 83-97 % for different times of year. Most importantly, the ALEXI-MW also matches ALEXI-IR very closely in terms of 3-month inter-annual anomalies, demonstrating its ability to capture the development and extent of drought conditions. The weekly output from the two parallel ALEXI implementations is further compared to a common ground measured reference provided by the FLUXNET consortium. Overall, they indicate a surprisingly close match in both performance metrics (correlation and RMSE) for all but the most challenging sites in terms of spatial heterogeneity and level of aridity. It is concluded that merging MW- and IR-based ALEXI may provide estimates of ET with a reduced uncertainty, even during nominally clear sky days.