SMOS Pilot-Mission Exploitation Platform (Pi-MEP)
[06-Nov-2018] Guimbard, S., Reul, N., Herlédan, S., Hanna, Z.E.K., Piollé, J-F., Paul, F., and Sabia, R.
Presented at the
2018 Ocean Salinity Science ConferenceThe Soil Moisture and Ocean Salinity (SMOS) mission was launched on November 2, 2009 as the second Earth Explorer Opportunity mission within ESA's Living Plant Program. It has been providing brightness temperature data in L-Band continuously since January 2010, which are used to retrieve soil moisture and sea surface salinity (SSS) data over land and ocean, respectively. This presentation provides a status of the Pilot Mission Exploitation Platform (Pi-MEP), which focusses on ESA's SMOS mission and supports enhanced validation and scientific process studies over the ocean.
Pi-MEP project objectives are:
- Enhanced validation of satellite SSS and products assessment, complementing and expanding efforts of the SMOS Expert Support Laboratories by exploring satellite performances at different spatial/temporal scales, applying different filtering criteria, or verifying SMOS outputs against various ground-truth data, and
- Oceanographic exploitation and case-studies monitoring, capitalizing on SMOS salinity data in synergy with additional satellite products (e.g., sea surface temperature, wind speed, currents, rain estimates).
The platform will offer a
series of statistical and computational tools in a user-oriented scientific environment to foster an increased uptake of SMOS salinity data in combination with other relevant oceanographic parameters. Pi-MEP datasets currently include:
- 37 Satellite SSS products (13 SMOS, 13 Aquarius, 11 SMAP)
- 120 Different satellite SSS sub-datasets
- 5 In situ datasets (ARGO, TSG, moorings, surface drifters, marine mammals)
- 8 Analysed in situ datasets (ISAS, EN4, JAMSTEC, SCRIPPS, IPRC, WOA09-13)
- 3 Numerical models (HYCOM, MERCATOR (NEMO), ECCO (mitGCM))
- 21 Thematic datasets (mixed layer depth, sea surface temperature, rain rate, surface currents, evaporation)
- 8 Process study dedicated datasets