Improving continuous monitoring of evapotranspiration with future thermal infrared missions

&amp;lt;p&amp;gt;Remote Sensing (RS) in the thermal infrared (TIR) provides useful information on evapotranspiration (ET). However, current satellites that are available for monitoring ET at a spatial resolution lower than 100 m have long revisit intervals (16 days for Landsat). Cloud occurrence also reduces the number of available images hindering the accuracy of continuous monitoring of ET (requiring interpolation between available ET estimations from RS data). Future satellite missions providing high spatial resolution data every 1 to 4 days are under study : TRISHNA by CNESand ISRO (France/India) and the Land Surface Temperature Monitoring mission (LSTM) by ESA/COPERNICUS.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;We analyzed the impact of satellite revisit on the uncertainty in monitoring ET over Europe by considering combinations of climate, land use, revisit characteristics and errors in estimating ET from RS data. We analyzed a large range of crop types / soil / climate / revisit combinations by using synthetic data of ET as simulated using the ISBA-A-gs land surface model (while previous studies were based on flux tower measurements and considered only a limited range of situations). Revisit scenarios were defined from the orbital characteristics of TRISHNA and LSTM in comparison to nominal scenarios with revisit between 1 day and 16 days. We also introduced errors in ET estimation from RS data at the time of acquisition (depending on the surface energy balance model used to derive ET and on the accuracy of RS measurements).&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;As expected, the uncertainty in monitoring ET increased significantly with the revisit period when cloud occurrence increased (Figure). However, the impact of cloud regime was lower at higher latitudes because the frequency of image acquisitions increased with the latitude. The impact of the uncertainty in estimating ET at the time of image acquisition was the main driver of the accuracy, in particular in southern Europe.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;img src=&amp;quot;data:image/png;base64, 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