RSLand - Assimilation of satellite-based measurements of the hydrosphere - towards a combined meteorological-hydrological forecasting system

The objective is to improve meteorological and hydrological model forecasts on the km-scale by assimilating satellite radiance and backscatter data regarding the Earth's surface and near-surface properties using modern ensemble Kalman filter (EnKF) techniques.

This project will capitalise on the considerable investment Sweden makes in ESA and EUMETSAT (and they in turn by collaborations with NASA and JAXA). Progress in the utilization of satellite data carrying important information about the surface soil moisture and snow characteristics will come from novel use of satellite radiances from the AMSR2 (GCOM-W1), the MIRAS (SMOS), and backscatter data from the SAR (Sentinel-1). Independent products and retrievals for the hydrosphere from the EUMETSAT satellite application facilities (SAF) and ESA will be used for validation purposes. Existing observation operators in terms of radiation transfer models (RTMs) will be adapted to mesoscale land surface and NWP models. These RTMs will be evaluated in and if necessary adapted to Nordic conditions. On the longer term the aim is an integrated meteorological-hydrological forecasting system. Cross fertilization of meteorological and hydrological competences will result in synergy effects on the development of data assimilation methods as well as the use of remote sensing satellite data in the respective modelling systems.

Role of SMHI

The work is carried out by SMHI and is funded by the Swedish National Space Board during 2015-2018. There is a close collaboration between SMHI, MET Norway, NILU and Météo-France regarding EnKF developments for land data assimilation systems. Contact person at SMHI is Tomas Landelius.