S. Karali, Improve short-term local meteorological forecast using local observation data, Diploma thesis, 274 pages, Department of Water Resources and Environmental Engineering – National Technical University of Athens, Athens, November 2017.
The accuracy of the short-term prediction of ambient conditions is particularly import for the development of predictive control strategies in various operations. Although the short-term prediction methods for outside air temperature have been extensively studied, reliable prediction methods for the other variables that describe the state of the atmosphere, such as atmospheric pressure, wind speed, total precipitation and humidity are yet to be established. Current diploma thesis discusses the possibility of using meteorological forecasting data with local observed data to improve short-term prediction of meteorological variables. Based on the analysis of the collected data, new methods have been developed for all forecasting variables. It is found that a linear combination of observed data including or not meteorological forecasting data can effectively improve the accuracy of short-term prediction (less than 24 hours). In addition, short-term local weather forecast is investigated by searching for comparable situations, but also combining this with meteorological forecasting data. Finally, we are studying the change of the results of forecasting methods on different climatic characteristics. In particular, same methods are applied for stations located in areas of different or similar climates and their results are compared.