Evaluating European ECOSTRESS Hub Evapotranspiration Products Across a Range of Soil‐Atmospheric Aridity and Biomes Over Europe

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is a scientific mission that collects high spatio‐temporal resolution (∼70 m, 1–5 days average revisit time) thermal images since its launch on 29 June 2018. As a predecessor of future missions, one of the main objectives of ECOSTRESS is to retrieve and understand the spatio‐temporal variations in terrestrial evapotranspiration (ET) and its responses to soil water availability and atmospheric aridity. In the European ECOSTRESS Hub (EEH), by taking advantage of land surface temperature (LST) retrievals, we generated ECOSTRESS ET products over Europe and Africa using three models with different structures and parameterization schemes, namely Surface Energy Balance System (SEBS) and Two Source Energy Balance (TSEB) parametric models, as well as the non‐parametric Surface Temperature Initiated Closure (STIC) model. A comprehensive evaluation of the EEH ET products was conducted with respect to flux measurements from 19 eddy covariance sites in Europe over six different biomes with diverse aridity levels. Results revealed comparable performances of STIC and SEBS (RMSE of ∼70 W m−2). However, the relatively complex TSEB model produced a higher RMSE of ∼90 W m−2. Comparison between STIC ET estimates and the operational ECOSTRESS ET product from NASA PT‐JPL model showed a larger RMSE (around 50 W m−2 higher) for the PT‐JPL ET estimates. Substantial overestimation (>80 W m−2) in PT‐JPL ET estimates was evident over shrublands and savannas, presumably due to weak constraint of LST in the model. Overall, the EEH supports ET retrieval for the future high‐resolution thermal missions.

[1]  José A. Sobrino,et al.  Continental-scale evaluation of three ECOSTRESS land surface temperature products over Europe and Africa: Temperature-based validation and cross-satellite comparison , 2022, Remote Sensing of Environment.

[2]  M. Litvak,et al.  Resolve the Clear‐Sky Continuous Diurnal Cycle of High‐Resolution ECOSTRESS Evapotranspiration and Land Surface Temperature , 2022, Water Resources Research.

[3]  W. Kustas,et al.  Insights Into the Aerodynamic Versus Radiometric Surface Temperature Debate in Thermal‐Based Evaporation Modeling , 2022, Geophysical Research Letters.

[4]  R. Zomer,et al.  Version 3 of the Global Aridity Index and Potential Evapotranspiration Database , 2022, Scientific Data.

[5]  M. Schull,et al.  A global 30-m ET model (HSEB) using harmonized Landsat and Sentinel-2, MODIS and VIIRS: Comparison to ECOSTRESS ET and LST , 2022, Remote Sensing of Environment.

[6]  G. Boulet,et al.  Assessment of an extended SPARSE model for estimating evapotranspiration from directional thermal infrared data , 2022, Agricultural and Forest Meteorology.

[7]  Sha Zhang,et al.  Thermally derived evapotranspiration from the Surface Temperature Initiated Closure (STIC) model improves cropland GPP estimates under dry conditions , 2022, Remote Sensing of Environment.

[8]  D. Baldocchi,et al.  A Coupled Ground Heat Flux-Surface Energy Balance Model of Evaporation Using Thermal Remote Sensing Observations , 2022, Biogeosciences.

[9]  M. Schlerf,et al.  Thermal and Shortwave Infrared Remote Sensing of Ecosystem Processes: Opportunities, Synergies, and Challenges , 2021, 2021 IEEE International India Geoscience and Remote Sensing Symposium (InGARSS).

[10]  P. Bolstad,et al.  An evaluation of ECOSTRESS products of a temperate montane humid forest in a complex terrain environment , 2021, Remote Sensing of Environment.

[11]  Martha C. Anderson,et al.  A decadal (2008–2017) daily evapotranspiration data set of 1 km spatial resolution and spatial completeness across the North China Plain using TSEB and data fusion , 2021 .

[12]  Yaoming Ma,et al.  Remote Sensing of Global Daily Evapotranspiration based on a Surface Energy Balance Method and Reanalysis Data , 2021, Journal of Geophysical Research: Atmospheres.

[13]  H. Hashimoto,et al.  Emerging satellite observations for diurnal cycling of ecosystem processes , 2021, Nature Plants.

[14]  Simon J. Hook,et al.  Validation and Quality Assessment of the ECOSTRESS Level-2 Land Surface Temperature and Emissivity Product , 2021, IEEE Transactions on Geoscience and Remote Sensing.

[15]  Roberta E. Martin,et al.  NASA's surface biology and geology designated observable: A perspective on surface imaging algorithms , 2021 .

[16]  Z. Su,et al.  The role of aerodynamic resistance in thermal remote sensing-based evapotranspiration models , 2021 .

[17]  M. P. González-Dugo,et al.  Long-term water stress and drought assessment of Mediterranean oak savanna vegetation using thermal remote sensing , 2021 .

[18]  Martha C. Anderson,et al.  Interoperability of ECOSTRESS and Landsat for mapping evapotranspiration time series at sub-field scales , 2021, Remote Sensing of Environment.

[19]  William P. Kustas,et al.  Surface Energy Flux Estimation in Two Boreal Settings in Alaska Using a Thermal-Based Remote Sensing Model , 2020, Remote. Sens..

[20]  Glynn C. Hulley,et al.  In-Flight Validation of the ECOSTRESS, Landsats 7 and 8 Thermal Infrared Spectral Channels Using the Lake Tahoe CA/NV and Salton Sea CA Automated Validation Sites , 2020, IEEE Transactions on Geoscience and Remote Sensing.

[21]  J. Chen,et al.  Evolution of evapotranspiration models using thermal and shortwave remote sensing data , 2020 .

[22]  Yaoming Ma,et al.  Optimization of a remote sensing energy balance method over different canopy applied at global scale , 2019, Agricultural and Forest Meteorology.

[23]  Li Fang,et al.  Evapotranspiration Data Product from NESDIS GET-D System Upgraded for GOES-16 ABI Observations , 2019, Remote. Sens..

[24]  Meha Jain,et al.  An automated multi-model evapotranspiration mapping framework using remotely sensed and reanalysis data , 2019, Remote Sensing of Environment.

[25]  Yongming Du,et al.  Directional variation in surface emissivity inferred from the MYD21 product and its influence on estimated surface upwelling longwave radiation , 2019, Remote Sensing of Environment.

[26]  Chunlin Huang,et al.  Evaluating Soil Resistance Formulations in Thermal‐Based Two‐Source Energy Balance (TSEB) Model: Implications for Heterogeneous Semiarid and Arid Regions , 2019, Water Resources Research.

[27]  R. Hostache,et al.  A Critical Evaluation on the Role of Aerodynamic and Canopy–Surface Conductance Parameterization in SEB and SVAT Models for Simulating Evapotranspiration: A Case Study in the Upper Biebrza National Park Wetland in Poland , 2018, Water.

[28]  Gérard Dedieu,et al.  The Indian-French Trishna Mission: Earth Observation in the Thermal Infrared with High Spatio-Temporal Resolution , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[29]  Isabel F. Trigo,et al.  Assessing the potential of parametric models to correct directional effects on local to global remotely sensed LST , 2018 .

[30]  James Cleverly,et al.  Bridging Thermal Infrared Sensing and Physically‐Based Evapotranspiration Modeling: From Theoretical Implementation to Validation Across an Aridity Gradient in Australian Ecosystems , 2018 .

[31]  Christiaan van der Tol,et al.  Integrating satellite optical and thermal infrared observations for improving daily ecosystem functioning estimations during a drought episode. , 2018 .

[32]  Arnaud Carrara,et al.  Modeling Surface Energy Fluxes over a Dehesa (Oak Savanna) Ecosystem Using a Thermal Based Two-Source Energy Balance Model (TSEB) I , 2018, Remote. Sens..

[33]  Nathaniel A. Brunsell,et al.  Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US , 2017 .

[34]  Martha C. Anderson,et al.  The future of evapotranspiration: Global requirements for ecosystem functioning, carbon and climate feedbacks, agricultural management, and water resources , 2017 .

[35]  Massimo Menenti,et al.  Evaluation of Methods for Aerodynamic Roughness Length Retrieval from Very High-Resolution Imaging LIDAR Observations over the Heihe Basin in China , 2017, Remote. Sens..

[36]  S. Wofsy,et al.  Canopy-scale biophysical controls of transpiration and evaporation in the Amazon Basin , 2016 .

[37]  William P. Kustas,et al.  Revisiting the paper “Using radiometric surface temperature for surface energy flux estimation in Mediterranean drylands from a two-source perspective” , 2016 .

[38]  Douglas L. Kane,et al.  Estimation of surface energy fluxes in the Arctic tundra using the remote sensing thermal-based Two-Source Energy Balance model , 2016 .

[39]  Matthew F. McCabe,et al.  ECOSTRESS: NASA's Next Generation Mission to Measure Evapotranspiration From the International Space Station , 2015, Water Resources Research.

[40]  Atul K. Jain,et al.  Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends , 2015, Environmental Research Letters.

[41]  William P. Kustas,et al.  Reintroducing radiometric surface temperature into the Penman‐Monteith formulation , 2015 .

[42]  D. Long,et al.  Comparison of three dual‐source remote sensing evapotranspiration models during the MUSOEXE‐12 campaign: Revisit of model physics , 2015 .

[43]  Richard Crago,et al.  Use of land surface temperature to estimate surface energy fluxes: Contributions of Wilfried Brutsaert and collaborators , 2014 .

[44]  J. Ardö,et al.  A Surface Temperature Initiated Closure (STIC) for surface energy balance fluxes , 2014 .

[45]  Martha C. Anderson,et al.  Examining Rapid Onset Drought Development Using the Thermal Infrared–Based Evaporative Stress Index , 2013 .

[46]  William P. Kustas,et al.  Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations , 2013 .

[47]  Prasanna H. Gowda,et al.  Operational Evapotranspiration Mapping Using Remote Sensing and Weather Datasets: A New Parameterization for the SSEB Approach , 2013 .

[48]  P. Ceccato,et al.  Actual evapotranspiration in drylands derived from in-situ and satellite data: Assessing biophysical constraints , 2013 .

[49]  S. J. Birks,et al.  Terrestrial water fluxes dominated by transpiration , 2013, Nature.

[50]  Yu Zhang,et al.  An Improvement of Roughness Height Parameterization of the Surface Energy Balance System (SEBS) over the Tibetan Plateau , 2013 .

[51]  Albert Olioso,et al.  An empirical expression to relate aerodynamic and surface temperatures for use within single-source energy balance models , 2012 .

[52]  Martha C. Anderson,et al.  Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources , 2012 .

[53]  Hideki Kobayashi,et al.  Integration of MODIS land and atmosphere products with a coupled‐process model to estimate gross primary productivity and evapotranspiration from 1 km to global scales , 2011 .

[54]  Martha C. Anderson,et al.  Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States , 2011 .

[55]  L. S. Pereira,et al.  Evapotranspiration information reporting: I. Factors governing measurement accuracy , 2011 .

[56]  Martha C. Anderson,et al.  Advances in thermal infrared remote sensing for land surface modeling , 2009 .

[57]  Hoshin Vijai Gupta,et al.  Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling , 2009 .

[58]  Martha C. Anderson,et al.  A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales , 2008 .

[59]  D. Baldocchi,et al.  Global estimates of the land–atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites , 2008 .

[60]  J. Wallace,et al.  Evaporation from sparse crops‐an energy combination theory , 2007 .

[61]  Martha C. Anderson,et al.  A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation , 2007 .

[62]  K. Trenberth,et al.  A Global Dataset of Palmer Drought Severity Index for 1870–2002: Relationship with Soil Moisture and Effects of Surface Warming , 2004 .

[63]  Z. Su.  The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes , 2002 .

[64]  E. Boegh,et al.  A Remote Sensing Study of the NDVI–Ts Relationship and the Transpiration from Sparse Vegetation in the Sahel Based on High-Resolution Satellite Data , 1999 .

[65]  W. Massman,et al.  AN ANALYTICAL ONE-DIMENSIONAL MODEL OF MOMENTUM TRANSFER BY VEGETATION OF ARBITRARY STRUCTURE , 1997 .

[66]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature [Agric. For. Meteorol., 77 (1995) 263–293]☆ , 1996 .

[67]  J. Norman,et al.  Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature , 1995 .

[68]  Paul D. Colaizzi,et al.  TWO-SOURCE ENERGY BALANCE MODEL TO CALCULATE E, T, AND ET: COMPARISON OF PRIESTLEY-TAYLOR AND PENMAN-MONTEITH FORMULATIONS AND TWO TIME SCALING METHODS , 2014 .

[69]  Joshua B. Fisher,et al.  ET come home: potential evapotranspiration in geographical ecology , 2011 .