Over past years, substantial progress has been made developing new products and novel applications using L-band observations from SMOS. So far, L-band radiometry has been the only technique allowing the estimation of thin sea ice thickness. Consequently, this data set has received a lot of attention and matured into a product that is now being produced and disseminated operationally by the University of Hamburg, under contract from ESA.
Substantial synergies and improvements for the exploitation of brightness temperatures and the retrieval of sea ice parameters from space can be achieved when passive microwave observations covering the spectral range from 1 GHz to 90 GHz are combined. A comprehensive set of long-term observations covering the full spectral range is available through radiometers on the SSMIS, AMSR2, SMAP and SMOS missions.
Additional observational data sets, e.g. from CryoSat2, Sentinel-1&3, or IceSat2, can be used as well, either as independent verification data or in advanced data assimilation systems. For this activity it is proposed to focus on passive microwave observations and exploit the respective observations in the context of a “virtual mission” focussing on a thematic topic rather than an individual satellite mission.
We suggest three main working areas for the “virtual mission”:
- Across instrument quality control including RFI detection and mitigation at brightness temperature level;
- Design, definition and generation of a community microwave emission model for ice covered ocean surfaces (following the CMEM approach over land) covering the spectral range from 1 to 90 GHz;
- First model verification using actual satellite observations and drafting of an experimental plan for a thorough model validation in a controlled (laboratory) environment.
The definition and generation of the community model is the key task of the group requiring a broad range of expertise and the involvement of internationally renowned experts. Starting from a gap analysis of existing models and parameterisations and the requirements from different (science) application groups (including the generation of ECVs, ocean and ice services, weather forecasting) the community model will be built and tested.
Last update: November 30, 2016