Cryospheric data assimilation, an integrated approach for generating consistent cryosphere data sets

Xin Li
Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, China

Establishing an integrated data and information service is one of the major objectives of the International Polar Year (IPY). The land data assimilation technology, which was booming in the last few years, provide an integrated approach to generated spatial and temporal consistent datasets of snow, frozen soil and other cryospheric states. We have developed a land data assimilation system with can assimilate remote sensing observations into land surface models and then produce reanalyzed cryospheric datasets with high spatial and temporal resolutions.

The model operator used in the system is the JMA (Japan Meteorological Administration) new SiB, which originates from the Simple Biosphere (SiB) model but is reformulated with explicit snow and soil freeze/thaw processes. The observation operators are passive microwave radiative transfer models of land surface states such as snow and (frozen/thaw) soil. The data assimilation methods employed is the ensemble Kalman filter, which is a Monte Carlo based sequential filter method.

The system was tested using many observations collected during CEOP (Coordinated Enhanced Observation Period), particularly at cold region sites such as Tibet-east reference and Siberia reference. The results showed that: (1) The system can estimate land surface variables, i.e., soil moisture, soil temperature and snow much more accurate than uncontrolled modeling. (2) Spatiotemporal and physical consistent data sets of cryospheric variables can be obtained from the system. (3) The system is very effective in terms of computation cost.


Keywords: cryosphere, data assimilation, IPY