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Proceedings Paper

Genetically optimizing weather predictions
Author(s): S. B. Potter; Kai Staats; Encarni Romero-Colmenero
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Paper Abstract

humidity, air pressure, wind speed and wind direction) into a database. Built upon this database, we have developed a remarkably simple approach to derive a functional weather predictor. The aim is provide up to the minute local weather predictions in order to e.g. prepare dome environment conditions ready for night time operations or plan, prioritize and update weather dependent observing queues.

In order to predict the weather for the next 24 hours, we take the current live weather readings and search the entire archive for similar conditions. Predictions are made against an averaged, subsequent 24 hours of the closest matches for the current readings. We use an Evolutionary Algorithm to optimize our formula through weighted parameters.

The accuracy of the predictor is routinely tested and tuned against the full, updated archive to account for seasonal trends and total, climate shifts. The live (updated every 5 minutes) SALT weather predictor can be viewed here: http://www.saao.ac.za/~sbp/suthweather_predict.html

Paper Details

Date Published: 15 July 2016
PDF: 11 pages
Proc. SPIE 9910, Observatory Operations: Strategies, Processes, and Systems VI, 99102H (15 July 2016); doi: 10.1117/12.2232306
Show Author Affiliations
S. B. Potter, South African Astronomical Observatory (South Africa)
Kai Staats, Univ. of Cape Town (South Africa)
Encarni Romero-Colmenero, South African Astronomical Observatory (South Africa)
Southern African Large Telescope (South Africa)


Published in SPIE Proceedings Vol. 9910:
Observatory Operations: Strategies, Processes, and Systems VI
Alison B. Peck; Robert L. Seaman; Chris R. Benn, Editor(s)

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