Sensitivity of the DDM peak to geophysical variables

• Published in: IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium
• Main Authors: Camps Carmona, Adriano José, Hyuk, Park
• Other Authors: Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions, Universitat Politècnica de Catalunya. Departament de Física
• Format: Conference Object
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE) 2022
• Subjects: Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Radar; Radar > Remote sensing; Oceanography > Remote sensing; Synthetic aperture radar; Geophysical variables; GNSS-R; Sensitivity; Oceanografia > Teledetecció; Radar > Teledetecció; Radar d'obertura sintètica; Sea ice
• Online Access: http://hdl.handle.net/2117/381994; https://doi.org/10.1109/IGARSS46834.2022.9883858

GNSS-R (Global Navigation Satellite Systems Reflectometry) can be understood as a multi-static radar with as many transmitters as navigation satellites and in view and can be tracked. GNSS-Reflectometers can process the reflected signals as a scatterometer, as an altimeter, or as an unfocused synthetic aperture radar. GNSS-R has demonstrated its potential to infer numerous geophysical variables over land (soil moisture, vegetation height, detecting freeze-thaw states. ), over the ocean (wind speed and direction, significant wave height, sea surface altimetry. ), over sea ice (extent, depth, type. ). Even a marine plastics litter product has been recently released by NASA, and some have suggested that sea surface salinity could also be inferred. In scatterometric applications the most widely used GNSS-R observable is the peak of the Delay Doppler Map (DDM), and many efforts have been directed towards an accurate instrument calibration. However, many geophysical parameter retrievals have neglected some variations of the DDM linked to the observation geometry, as well as the sensitivity to other geophysical variables. In this study we present analyze some of these effects and present a sensitivity analysis for the ocean case, notably the impact of the wind direction (WD), the 10 m height wind speed (mathrm{U}-{10}), which is routinely obtained today from GNSS-R observables, the sea surface temperature (SST) and sea surface salinity (SSS), and the presence of oil slicks. This quantitative study illustrates the challenges presented to retrieve some of these variables, the required corrections and their accuracy. This work was (partially) sponsored by project SPOT: Sensing with Pioneering Opportunistic Techniques grant RTI2018-099008-B-C21/AEI/10.13039/501100011033. Peer Reviewed Postprint (author's final draft)