Accession Number:

ADA361368

Title:

Predicting Launch Pad Winds at the Kennedy Space Center With a Neural Network Model.

Descriptive Note:

Master's thesis,

Corporate Author:

AIR FORCE INST OF TECH WRIGHT-PATTERSONAFB OH SCHOOL OF ENGINEERING

Personal Author(s):

Report Date:

1999-03-01

Pagination or Media Count:

72.0

Abstract:

This thesis uses neural networks to forecast winds at the Kennedy Space Center and the Cape Canaveral Air Station launch pads. Variables are developed from WINDS tower observations, surface and buoy observations, and an upper-air sounding. From these variables, a smaller set of predictive inputs is chosen using a signal-to-noise variable screening method. A neural network is then trained to forecast launch pad winds from the inputs. The network forecasts are compared to persistence, and peak wind predictions are found skillful compared to persistence. An ensemble modeling technique using Toths and Kalnays breeding of growing modes method is explored with neural networks. The inputs are perturbed an amount representative of measurement error. Ensemble member forecasts are found to diverge, but the ensemble spread does not often encompass the resulting weather. This is due to a disproportionate amount of error originating from the model compared to error originating from measurements.

Subject Categories:

  • Meteorology

Distribution Statement:

APPROVED FOR PUBLIC RELEASE