CoAuthors

Christine Gommenginger (National Oceanography Centre, UK); Francisco Mir Calafat (National Oceanography Centre, United Kingdom); Helen Snaith (British Oceanographic Date Centre, UK); Nadim Dayoub (National Oceanography Centre, United Kingdom); Matthew Hammond (National Oceanography Centre, United Kingdom)

Sentinel-3A (S3A) has been in orbit since February 2016 and routinely provides data on ocean wind and waves (significant wave height/SWH, Sigma0 and wind speed). S3A was joined in orbit by Sentinel-3B (S3B) in April 2018 with a requirement to establish the consistency of the instruments on the two satellites, through inter-comparisons with each other and also comparisons with independent data. 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 little 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 ongoing 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 S3A and 3B 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.