Abstract

A newly developed microwave (MW) land surface temperature (LST) product is used to substitute thermal infrared (TIR) based LST in the Atmosphere Land Exchange Inverse (ALEXI) modelling framework for estimating ET from space. ALEXI implements a two-source energy balance (TSEB) land surface scheme in a time-differential approach, designed to minimize sensitivity to absolute biases in input records of LST through the analysis of the rate of temperature change in the morning. Thermal infrared (TIR) retrievals of the diurnal LST curve, traditionally from geostationary platforms, are hindered by cloud cover, reducing model coverage on any given day. This study tests the utility of diurnal temperature information retrieved from a constellation of satellites with microwave radiometers that together 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 analysis is based on 9-year long, global records of ALEXI ET generated using both MW and TIR based diurnal LST information as input. 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 changing the LST dataset separately from the impact of sampling all-sky conditions. The results show that long-term bulk ET estimates from both LST sources agree well, with a spatial correlation of 92% for total ET in the Europe/Africa domain and agreement in seasonal (3-month) totals of 83-97 % depending on the time 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. Weekly ET output from the two parallel ALEXI implementations is further compared to a common ground measured reference provided by the FLUXNET consortium. Overall, the two model implementations generate similar 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 a constellation of MW satellites can effectively be used to provide LST for estimating ET through ALEXI, which is an important step towards all-sky satellite-based retrieval of ET using an energy balance framework.

Highlights

  • Estimating terrestrial evapotranspiration (ET) on continental to global scales is central to understanding the partitioning of energy and water at the earth surface and for evaluating modeled feedbacks operating between the atmosphere and biosphere

  • The mean average Trad as calculated from MW-land surface temperature (LST) deviates from that calculated from Moderate Resolution Imaging Spectroradiometer (MODIS) LST by 0–20 %, which leads to a spatial R2 of 0.90 (Fig. 4, top row panels)

  • MW-LST is calibrated to match the Land Surface Analysis Satellite Application Facility (LSA-SAF) LST from Meteosat Second Generation (MSG) (Europe and Africa) with a precision of 2–3 K, and MODIS Trad is trained on Geostationary Operational Environmental Satellite (GOES) (North America) with an estimated precision of 5– 10 %

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Summary

Introduction

Estimating terrestrial evapotranspiration (ET) on continental to global scales is central to understanding the partitioning of energy and water at the earth surface and for evaluating modeled feedbacks operating between the atmosphere and biosphere. Two-thirds of the precipitation over land is returned to the atmosphere by ET (Baumgartner and Reichel, 1975). ET consumes 25–30 % of the net radiation reaching the land surface (Trenberth et al, 2009). ET occurs as a result of atmospheric demand for water vapor and depends on the availability of water and energy.

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