Forecasting Algorithm Based on Temperature Error Prediction Using Kalman Filter for Management System Development

The study offers a new method of collection and processing of meteorological data from the meteorological service based on observations and correction of numerical weather forecast errors using a new prediction algorithm. This algorithm vastly increases the accuracy of the short-term forecast of out...

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Veröffentlicht in:Latvian journal of physics and technical sciences Jg. 58; H. 5; S. 38 - 49
Hauptverfasser: Bogdanovs, N, Belinskis, R, Bistrovs, V, Petersons, E, Ipatovs, A
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Riga De Gruyter Brill Sp. z o.o., Paradigm Publishing Services 01.10.2021
Schlagworte:
Air temperature
Algorithms
Kalman filters
Meteorological data
Meteorological services
Weather forecasting
ISSN:0868-8257, 2199-6156
Online-Zugang:Volltext
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Zusammenfassung:The study offers a new method of collection and processing of meteorological data from the meteorological service based on observations and correction of numerical weather forecast errors using a new prediction algorithm. This algorithm vastly increases the accuracy of the short-term forecast of outdoor air temperature, which is subject to uncertainty due to the stochastic nature of atmospheric processes. Processing of temperature data using Kalman filter provides the decrease in predicted temperature errors. The main setup methods of Kalman filter have been examined. The article also describes the implementation of accuracy improving algorithm of predicted temperature using Python.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 14
ISSN:0868-8257
2199-6156
DOI:10.2478/lpts-2021-0038