An OSSE Platform for Terrestrial Hydrology using the NASA Land Information System (LIS): Initial Results from SMAP-relevant OSSEs

Simulation is a key tool for the cost effective planning and execution of NASA missions. Observing system simulation experiments (OSSEs) can help to demonstrate and quantify the impact of remotely sensed observations on terrestrial hydrologic science and societal objectives (e.g., minimizing impacts of droughts and floods). Importantly, they are also critical for understanding and mitigating mission risk. Here, the science and technology underlying a new mission simulation and evaluation platform under development are presented. The platform will be built upon the NASA Land Information System (LIS), an advanced multi-scale land surface modeling system, and the Land surface Verification Toolkit (LVT), which provides tools for evaluating LIS outputs using a wide range of metrics. The platform integrates components of LIS' advanced data processing subsystems (e.g., data assimilation, optimization, and uncertainty estimation) and coupled model systems (e.g., land surface -atmospheric radiative transfer, land surface-weather forecasting, and land surface-application models). The design advances the state-of-the-art in OSSE development by incorporating "value-of-information" and other concepts from decision and information theory that have long dealt with similar questions, and by anticipating a more robust set of questions than the "classic" OSSE that focuses on data assimilation. In addition, the platform is being designed to conduct OSSEs useful at each stage of mission planning, from the time of mission concept formulation to after launch, and therefore targets current (e.g., TRMM, EOS-Aqua, GRACE, Aquarius) and future (e.g., SMAP, GPM, GRACE Follow-on, GRACE-II) missions. In the talk, results from soil moisture observation system simulation experiments designed for SMAP mission will be presented.