Assimilation of Freeze-Thaw observations into the NASA catchment land surface model

Leila Farhadi, Rolf H. Reichle, Gabriëlle J.M. De Lannoy, John S. Kimball

Research output: Contribution to journalArticlepeer-review

Abstract

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 NASA Goddard Earth 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 model 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 observations reduced the root-mean-square errors (RMSEs) of surface temperature and soil temperature by 0.2068 and 0.061°C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7%and 3.1%, respectively). For a maximum classification error CEmax of 10%in the synthetic F/T observations, the F/T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178° and 0.036°C, respectively. For CEmax = 20%, the F/T assimilation still reduces the RMSE of model surface temperature estimates by 0.149°C but yields no improvement over the model soil temperature estimates. The F/T assimilation scheme is being developed to exploit planned F/T products from the NASA Soil Moisture Active Passive (SMAP) mission.

Original languageEnglish
Pages (from-to)730-743
Number of pages14
JournalJournal of Hydrometeorology
Volume16
Issue number2
DOIs
StatePublished - 2015

Keywords

  • Data assimilation
  • Land surface model

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