Assimilation of Freeze–Thaw Observations into the NASA Catchment Land Surface Model

The land surface freeze-thaw (F/T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, an F/T assimilation algorithm was developed for the NA SA G oddard E arth Observing System, version 5 (GEOS-5), modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F/T state in the GEOS-5 Catchment land surface model. The F/T analysis is a rulebased approach that adjusts Catchment m odel state variables in response to binary F/T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F/T observations. The assimilation of perfect (error free) F/T ob­ servations reduced the root-mean-square errors (RMSEs) of surface tem perature and soil tem perature by 0.206° and 0.061°C, respectively, when compared to m odel estimates (equivalent to a relative RM SE re­ duction of 6.7% and 3.1%, respectively). For a maximum classification error CE^jaxOf 10% in the synthetic F/T observations, the F/T assimilation reduced the RM SE of surface tem perature and soil tem perature by 0.178° and 0.036°C, respectively. For CEmax = 20%, the F/T assimilation still reduces the RM SE of m odel surface tem perature estimates by 0.149°C but yields no improvement over the m odel soil tem perature estimates. The F/T assimilation scheme is being developed to exploit planned F/T products from the NA SA Soil Moisture Active Passive (SM AP) mission.