6.2 Weather support to the NASA Deep Space Network

Thursday, 14 September 2000: 8:20 AM
G. Wayne Baggett, NOAA/NWS/Spaceflight Meteorology Group, Houston, TX; and S. D. Slobin

Since February 1999, the NWS Spaceflight Meteorology Group (SMG) at the Johnson Space Center has been furnishing weather support on an experimental basis to NASA/JPL (Jet Propulsion Laboratory) for the Deep Space Network (DSN) antenna site at Goldstone, CA. Goldstone is located in the Mojave Desert 45 miles north of Barstow, elev. 3,153 ft. This support is in the form of daily forecasts of cloud conditions, temperature, pressure, rainfall, and humidity out to 48 hours.

The newly built worldwide network of 34 meter diameter beamwaveguide antennas is being implemented for operation at a microwave frequency of 32 GHz (Ka-band). Microwave propagation at this frequency is adversely affected to a significant degree by water vapor and liquid water particles (clouds and rain). It is felt that with accurate forecasts of weather conditions at the DSN receiving sites, microwave propagation conditions can also be forecast, and appropriate modifications to the telecommunication link (e.g., changing spacecraft data rate) can be made to maintain an adequate signal-to-noise ratio and to optimize data return.

This paper outlines the evolution and development of SMG weather support and describes in detail the Goldstone forecast product that is now being disseminated daily. In addition, an objective technique has been developed that generates a first guess cloud forecast using NCEP model data. This automated product computes cloud liquid water content and absolute humidity in each cloud layer.

During the forecast development process, users at JPL will convert SMG forecast parameters to corresponding values of atmospheric attenuation and noise temperature. The noise temperature values will then be verified against actual microwave noise temperature measurements made by a water vapor radiometer at the Goldstone antenna site. The results of this verification study can then be used to determine to what extent DSN operations at Ka-band can be improved by utilizing realtime operational weather forecasts.

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