As part of NASA's mission to understand and protect our home planet, we are developing applications to assist resource managers, scientists, and policy makers in evaluating the effects of climate variability and change on ecocsystems. Each of these applications utilizes TOPS and the Ecocast architecture to rapdily convert gigabytes per day of NASA satellite data into usable nowcasts and forecasts. The applications listed below demonstrate the range of capabilities provided by the Ecocast architecture. New applications are always in development and will posted here as they become available.
Researchers at CMU and UWF IHMC are applying algorithms for autonomous causal discovery to a dataset which includes TOPS 8km data products for the U.S., in addition to NASA's MODIS data products, and meteorological data from NCDC and gridded using TOPS. Parameters analyzed include TOPS daily inputs including temperature, humidity, rainfall, solar radiation and outputs including soil moisture, evapotranspiration, snow cover and gross primary production. Novel and promising fire risk models discovered by these algorithms are currently being integrated into the Ecocast architecture for use in the generation of weekly and seasonal fire risk forecasts. (more)
Net Primary Productivity (NPP) is a measure of plant growth, and is important to monitoring and understanding global change. As an extension of past work on the historical trends in global NPP, we are producing annual and 10 day maps of anomalies in net primary production. Since 2000, production of these anomaly maps has utilized a variety of MODIS products. In addition, the anomaly maps are produced using weather data from the National Center for Environmental Prediction (NCEP). TOPS is currently being used to produce the global and continental forecasts at weekly and seasonal time scales. (more)
The Regional Hydro-Ecological Simulation System (RHESSys) model has been implemented in the Ecocast architecture and is currently being used to ingest MODIS satellite data to forecast snowpack behavior and regional watershed dynamics. Applications based on this system are currently in development and include flood risk forecasting and water resource management. (more)
In collaboration with Robert Mondavi wineries and California State University Monterey Bay, we developed and implemented a biogeochemical model in TOPS to estimate and map canopy conditions, soil moisture stress, and irrigation requirements in vineyards. The Mondavi winery is currently testing the utility of these nowcasts in their operational management. Vineyard forecasts are produced using IKONOS 2m imagery to map canopy conditions, among other data. (more)
