Assessing prospects of sub-daily radar-observations to improve the understanding of soil- and vegetation dynamics.
Authors: Quast Raphael , Wagner Wolfgang , Calvet Jean-Christophe , Albergel Clèment , Bertrand Bonan , Brocca Luca , Filippucci Paolo , Hobbs Stephen 
Published: March 2020

&lt;p&gt;The geosynchronous C-band SAR mission Hydroterra (initially called G-CLASS) is one of three candidate missions for ESA's upcoming Earth Explorer 10 programme (scheduled for launch in 2027-2028). While current available satellite-borne C-band radar instruments have a rather long re-visit time (ASCAT METOP A,B,C: daily, Sentinel-1 A,B: 3-6 days), the fact that the Hydroterra satellite would be in a geosynchronous orbit opens the possibility for a C-band radar dataset with much finer temporal resolution. The image-formation process and operations concept incorporated within the Hydroterra system however requires choices of spatial and temporal resolution of the final product.&lt;/p&gt;&lt;p&gt;The presented experiment is intended to highlight potential benefits associated with high temporal sampling of Hydroterra observations for the understanding of daily and sub-daily soil-moisture and vegetation processes. In order to generate a backscatter dataset that simulates observations at high temporal resolution, a parametric first-order radiative transfer model (RT1) [1] is first calibrated with incidence-angle dependent Sentinel-1 C-band backscatter data as well as auxiliary soil-moisture (SM) and leaf-area-index (LAI) timeseries provided by the SURFEX-ISBA [2] land-surface model over south-western France. Once the model-parameters are obtained, a simulated backscatter timeseries at high temporal resolution is generated by performing a forward-simulation using the retrieved model-parametrizations and auxiliary SM and LAI datasets at hourly intervals.&lt;br&gt;&lt;br&gt;The simulated dataset is then used (in conjunction with the LAI dataset) to simulate a retrieval of SM under a set of possible observation conditions, e.g. varying soil- and vegetation properties (represented via the RT1 model parameters), different temporal resolutions (1,3,6,12 hourly), incidence-angles and noise-levels. In a final step, the obtained SM retrievals from the simulated dataset are used to assess the effects on rainfall estimates obtained via the SM2RAIN [3] algorithm.&lt;/p&gt;&lt;p&gt;The outcome of those simulations is intended to help quantifying the choices of spatial and temporal resolution for the Hydroterra mission concept from a soil properties applications point of view.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;The work has been supported by the FFG-ASAP project &quot;DWC-Radar&quot; and the ESA project &quot;Hydroterra (former G-CLASS) Phase-0 Science and Requirement&quot;.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;References:&lt;/p&gt;&lt;p&gt;[1] Quast, R.; Albergel, C.; Calvet, J.-C.; Wagner, W. A Generic First-Order Radiative Transfer Modelling Approach for the Inversion of Soil and Vegetation Parameters from Scatterometer Observations. &lt;em&gt;Remote Sens.&lt;/em&gt; &lt;strong&gt;2019&lt;/strong&gt;, &lt;em&gt;11&lt;/em&gt;, 285. &lt;/p&gt;&lt;p&gt;[2] Masson, V.; Le Moigne, P.; Martin, E.; Faroux, S.; Alias, A.; Alkama, R.; Belamari, S.; Barbu, A.; Boone, A.; Bouyssel, F.; et al. The SURFEXv7.2 land and ocean surface platform for coupled or offline simulation of earth surface variables and fluxes. &lt;span&gt;Geosci. Model Dev.&lt;/span&gt; &lt;strong&gt;2013&lt;/strong&gt;, &lt;span&gt;6&lt;/span&gt;, 929&amp;#8211;960. &lt;/p&gt;&lt;p&gt;[3] Brocca, L., Massari, C., Ciabatta, L., Moramarco, T., Penna, D., Zucco, G., Pianezzola, L., Borga, M., Matgen, P., Mart&amp;#237;nez-Fern&amp;#225;ndez, J. (2015). Rainfall estimation from in situ soil moisture observations at several sites in Europe: an evaluation of SM2RAIN algorithm. &lt;em&gt;Journal of Hydrology and Hydromechanics&lt;/em&gt;, 63(3), 201-209, doi:10.1515/johh-2015-0016. .&lt;/p&gt;