2002 Annual

Thursday, 17 January 2002: 10:30 AM
Evaluation of balloon trajectory forecast routines for GAINS
Randall S. Collander, NOAA/FSL, Boulder, CO; and C. M. I. R. Girz
Poster PDF (188.9 kB)
GAINS, the Global Air-ocean IN-situ System, is a global observing system designed to augment current environmental observing and monitoring networks. GAINS is a network of long-duration, stratospheric platforms that carry onboard sensors and dozens to hundreds of dropsondes to acquire meteorological, air chemistry, and climate data over oceans and in remote land regions of the globe. Although GAINS platforms will include balloons and Remotely Operated Aircraft (ROA), the scope of this paper is limited to balloon-based platforms.

The ideal method for evaluating system operation is the launch and recovery of short (<48-h) flights at altitude, and successful test flights require proper placement of chase and recovery crews. Software has been developed for the prediction of the balloon trajectory and landing site to aid in these flight operations, with separate software versions written to generate predictions based upon radiosonde data and model output. Balloon positions are calculated in 1-min increments based on wind data from the closest raob site or model grid point, given a known launch point, ascent and descent rate and flight duration. For flights less than 6 h, radiosonde winds interpolated to 10-mb levels are used for trajectory calculations. Predictions for flight durations of 6 to 48 h are based upon the initialization and 3-h forecast wind fields from the global AVN and RUC models.

Given a limited number of actual balloon launches, trajectories computed from a chronological series of hourly RUC initializations are assumed to be the true balloon trajectories for comparison purposes. These "true" trajectories are compared to predicted trajectories from the raob and model-based versions over a 30-day period ( 1-30 May 2001) for flight durations of 3 h and 12 h, respectively. We expect that predicted trajectories will diverge from the true path, and that this divergence will increase proportionally with time. The directional and distance deviations are examined to determine biases in the predictions. This paper gives an overview of the software, including methods employed, physical considerations and limitations, and discusses results of this preliminary evaluation.

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