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Creating first guess forecast products NASA Johnson Space Center: Applying LAPS and AWIPS Forecast Preparation System algorithms in McIDAS
Timothy D. Oram, NASA, Spaceflight Meteorology Group, Johnson Space Center, TX
The National Weather Service Spaceflight Meteorology Group (NWS SMG) at NASA Johnson Space Center is responsible for issuing forecasts for all potential Space Shuttle landings. These landings include both planned End-of-Mission landings at US landing sites and contingency landings at locations throughout the world. Forecasters also produce daily experimental forecasts of clouds and precipitation for NASA's Deep Space Network (DSN) location in California. The experimental forecasts are used to determine if weather forecasts used to predict radio propagation can improve the utilization of DSN communications bands. In addition, daily forecasts for emergency landing sites throughout the world will be required when the Crew Recovery Vehicle is deployed to the International Space Station in the near future.
Forecasters have various global and regional numerical model data available for developing forecasts. This data includes model-generated soundings for specific locations that have higher vertical and temporal resolution than the resolution available in the grid data. However, SMG customers often require forecast parameters that are not explicitly predicted by the model. The creation of the final forecast product is also largely a manual process. These factors and the relatively short time line for producing the forecasts in an operational environment have created a need for automated processes to create first guess forecast products. These first guess products can serve as a starting point for revision by the forecaster or, in some limited instances, these products can be sent directly to the customer without modification by the forecaster.
The primary forecast parameters needed to meet all customer needs are: surface wind, surface visibility, weather, cloud heights, cloud thickness, cloud amount, cloud liquid water content, upper atmospheric winds at specific levels, upper level water vapor, and turbulence. Algorithms exist in the Local Analysis and Prediction System (LAPS) and the Automated Weather Information Processing System (AWIPS) Forecast Preparation System (FPS) that produce the desired forecast parameters when the variables are not explicitly predicted by the available models. These algorithms are being integrated into the Johnson Space Center Meteorological Interactive Data Display System (MIDDS) with the processes that create the first guess forecast product. The first guess product is based on numerical model grid data and is readily imported into Microsoft Word and Excel as well as other formats used by SMG's NASA customers.
In the near future, the model-generated soundings will be incorporated into the first guess. A graphical user interface can be added that allows the forecaster to interact with the database to manipulate the first guess. The graphical user interface could also be used to incorporate forecaster decision aids -- currently under development -- into the forecast process.
Poster Session 1, Poster Session
Wednesday, 12 January 2000, 5:00 PM-6:30 PM
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