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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Predicting Launch Pad Winds at the Kennedy Space Center With a Neural Network Model

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

Storch, Steven J.

Paperback

Technology & EngineeringAstronomy & SpaceGeneral Education

ISBN10: 1249601363
ISBN13: 9781249601364
Publisher: Biblioscholar
Published: Oct 10 2012
Pages: 74
Weight: 0.26
Height: 0.15 Width: 6.14 Depth: 9.21
Language: English

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 Toth's and Kalnay's 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.

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