Science and applications-driven OSSE platform for terrestrial hydrology using NASA Land Information System

Abstract:

Observing System Simulation Experiments (OSSEs) are often conducted to evaluate the worth of existing data and data yet to be collected from proposed new missions. As missions increasingly require a broader ``Earth systems'' focus, it is important that the OSSEs capture the potential benefits of the observations on end-use applications. Towards this end, the results from the OSSEs must also be evaluated with a suite of metrics that capture the value, uncertainty, and information content of the observations while factoring in both science and societal impacts. In this presentation, we present the development of an end-to-end and end-use application oriented OSSE platform using the capabilities of the NASA Land Information System (LIS) developed for terrestrial hydrology. Four case studies that demonstrate the capabilities of the system will be presented: (1) A soil moisture OSSE that employs simulated L-band measurements and examines their impacts towards applications such as floods and droughts. The experiment also uses a decision-theory based analysis to assess the economic utility of observations towards improving drought and flood risk estimates, (2) A GPM-relevant study quantifies the impact of improved precipitation retrievals from GPM towards improving landslide forecasts, (3) A case study that examines the utility of passive microwave soil moisture observations towards weather prediction, and (4) OSSEs used for developing science requirements for the GRACE-2 mission. These experiments also demonstrate the value of a comprehensive modeling environment such as LIS for conducting end-to-end OSSEs by linking satellite observations, physical models, data assimilation algorithms and end-use application models in a single integrated framework.