HR: 14:15h
AN: H23D-02 INVITED     [Abstracts]
TI: Soil Moisture Remote Sensing in the Canadian Land Data Assimilation System (CaLDAS)
AU: * Belair, S
EM: stephane.belair@ec.gc.ca
AF: Environment Canada, 2121 Trans-Canada, room 500, Dorval, Que H9P1J3, Canada
AU: Carrera, M
EM: marco.carrera@ec.gc.ca
AF: Environment Canada, 2121 Trans-Canada, room 500, Dorval, Que H9P1J3, Canada
AU: Bilodeau, B
EM: bernard.bilodeau@ec.gc.ca
AF: Environment Canada, 2121 Trans-Canada, room 500, Dorval, Que H9P1J3, Canada
AB: For several years now, a major project has been underway at Environment Canada (EC) to improve the representation of land surface processes in operational environmental prediction systems. A foremost component of this effort is related to improving soil moisture analysis produced by the Canadian Land Data Assimilation System (CaLDAS). In its current operational state, CaLDAS assimilates observations from surface stations to specify terrestrial snow, soil moisture, and surface temperature, using simple techniques based on optimal interpolation. Our present focus is to include space-based remote sensing observations in CaLDAS with more sophisticated methods like variational data assimilation or ensemble Kalman filtering. We are currently examining and testing these approaches for the assimilation of passive L-band microwave data that will be available from the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active and Passive (SMAP) missions. Progress on this effort will be reported at the conference, with emphasis on the soil moisture first guess, on the integrated data assimilation framework that is becoming CaLDAS, and on specific aspects of the assimilation of SMOS and SMAP soil moisture data that require particular attention.
DE: 1840 Hydrometeorology
DE: 1847 Modeling
DE: 1855 Remote sensing (1640)
DE: 1866 Soil moisture
DE: 1876 Water budgets
SC: Hydrology [H]
MN: 2009 Joint Assembly