Abstract: The Terrestrial Observation and Prediction System (TOPS) modeling software system that brings together technologies in information technology, weather/climate forecasting, ecosystem modeling, and satellite remote sensing to enhance management decisions related to floods, droughts, forest fires, human health, and crop, range, and forest production. TOPS is designed to provide a suite of ecosystem ... nowcasts and forecasts known as the TOPS-30.
TOPS uses the Java Distributed Applications Framework (JDAF) framework and is the core modeling layer in the Ecocast architecture. TOPS is comprised of multiple biogeochemical (BGC) models which can be used together or independently. The JDAF framework along with the applications programming interface (API) to the IMAGEbot Planner also support rapid integration of new models.
TOPS automatically integrates and preprocesses EOS data fields so that land surface models can be run in near real time with minimal intervention. Currently we use a modified version of BIOME-BGC to estimate various water (evaporation, transpiration, stream flows, and soil water), carbon (net photosynthesis, plant growth) and nutrient flux (uptake and mineralization) processes. BIOME-BGC is adapted for all major biomes exploiting their unique ecophysiological principles such as drought resistance, cold tolerance, etc. The model is initialized with soil physical properties and satellite based vegetation information (type and density of plants). Then daily weather conditions (maximum/minimum temperatures, solar radiation, humidity and rainfall) are used to drive various ecosystem processes (e.g. soil moisture, transpiration, evaporation, photosynthesis and snowmelt etc., that can be translated to drought, crop yields, and streamflow estimates. We have implemented TOPS at a variety of spatial scales to forecast parameters from monthly NPP anomalies globally at 0.5x0.5 resolution down to local estimates of irrigation requirements for vineyards. At each spatial resolution, TOPS uses different sources of satellite data (MODIS to IKONOS) and meteorology data (single weather station to global atmosperic model outputs).
TOPS provides functionality to ensure that inputs are spatially and temporally consistent. It provides algorithms to fill in gaps, identify, and correct problems in various data sources, with the aim of producing operationally reliable land surface fluxes and states. The technology behind TOPS allows us to rapidly adapt the system to address a variety research questions related to ecological forecasting.