The Self-adaptive Earth Predictive System (SEPS) concept combines Earth System Models (ESM) and Earth Observations (EO) into one system. EO measures the Earth system state while ESM predicts the evolution of the state. A feedback mechanism processes EO measurements and feeds them into ESM during model runs or as initial conditions. A feed-forward mechanism analyzes the ESM predictions against science goals for scheduling optimized/targeted observations. The SEPS framework automates the Feedback and Feed-forward mechanisms (the FF-loop). Scientists from GMU, GSFC, and UBMC will collaborate to 1) develop a general SEPS framework for dynamic, interoperable coupling between ESMs and EO, based on open, consensus-based standards; 2) implement and deploy the framework and plug in diverse sensors and data systems to demonstrate the plug-in-EO-and-play capability; and 3) prototype a Bird- Migration-Model-to-aid-avian-influenza-prediction SEPS and an atmospheric chemistry composition SEPS using this framework, to demonstrate the framework's plug-in-ESM-and-play capability and its applicability as a common infrastructure for supporting the focus areas of NASA research. This project will significantly advance 1) dynamic, interoperable and live coupling of ESM with the sensor web; 2) the sensor web from concept to operation with existing sensors and data sources; and 3) the use of service-oriented architecture in modeling and integration. The project will improve the accuracy and timeliness of monitoring and predicting rapidly changing Earth phenomena, such as severe weather and air pollution.
The 3-year project will start in October 2006. The entry TRL is 4 and the exit TRL is 7. |