Evaluation of Sea State Products from the Sentinel-3A and Sentinel-3B Tandem Phase

Chris Banks1, Christine Gommenginger2, Francisco M Calafat1, Nadim Dayoub2, Helen M Snaith3, Werenfrid Wimmer4, Matthew Hammond5 and Ben Timmermans5, (1)National Oceanography Centre, Liverpool, United Kingdom, (2)National Oceanography Centre, Southampton, United Kingdom, (3)British Oceanographic Data Centre, United Kingdom, (4)University of Southampton, Southampton, SO14, United Kingdom, (5)National Oceangraphy Centre, Southampton, United Kingdom
Abstract:
Sentinel-3A (S3A) was launched in February 2016 and routinely provides data on ocean wind and waves (significant wave height/SWH, Sigma0 and wind speed). In April 2018, S3A was joined in orbit by Sentinel-3B (S3B) and during the first few months the satellites operated in tandem. The operation of S3B in tandem with S3A during the early phase provides a unique opportunity to obtain data close in space and time to quantify instrument-related sources of discrepancies. During the tandem phase, S3B flies as close as 30 seconds ahead of S3A, which for most purposes can essentially be considered to be instantaneous. In the case of the Sentinel-3 Surface Topography Mission (STM) altimeter payload, the operation of the altimeter instruments on the two Sentinel satellites in different operating modes (Low Resolution Mode/LRM and Synthetic Aperture Radar Mode/SARM) brings additional benefits by providing the opportunity to directly compare the performance and dependencies of the retrieved measurements in the two operating modes. Evaluation of the inter-satellite consistency incorporates independent data such as in situ data, model output and other satellite data all of which, like the S3 data, include uncertainties.

In this study, we present work concerned with the calibration and validation of sea state data from the two Sentinel-3 STM instruments. Using independent data, we examine the geographical distribution and uncertainty characteristics of SWH and wind speed from the Sentinel-3 satellites, as well as any global and regional offsets and discrepancies. Statistical methods are explored to formally quantify the errors of the STM sea state measurements, as well as the dependence of errors in SWH and wind speed on various sea state parameters in LRM and SARM operating modes.