Statistical Analysis for Long-Term Weather Forecast
Dimitrios Kampolis · 2023
A weather forecast is a result of applying science and technology to predict the conditions of the atmosphere in a selected location and time in the future. The main input is a collection of data (atmospheric, land, and ocean), and the resulting output is meteorology (how atmospheric conditions will change). People have been trying to predict the weather by observing nature for thousands of years, but in a scientific way only since the 19th century. First manually and based mostly on changes in barometric pressure, and later in modern times with the contribution of computer-based models (numerical weather prediction). Despite the high inaccuracy of numerical weather prediction beyond 10 days, the interest in long-term weather forecasts is very high due to social reasons—energy sector, civil protection, etc.—and the scientific effort is constant. Here, we propose a statistical weather model for long-term weather forecasts based on weather/climate data time series. We will analyze atmospheric data in 850 hPa for a period of 35 years, resulting in temperature ensembles and temperature deviations for specific periods. Finally, we will contrast the results of the statistical weather model (prediction) with the real data to check the accuracy of the model.