Shchehlov O. Physical-statistical method of forecasting air temperature and precipitation with monthly time-lead based on ensemble of analogues of atmospheric processes.

The thesis is devoted to the development of a method of forecasting air temperature and atmospheric precipitation for a month, taking into account the ensemble of analogues of atmospheric circulation on the basis of two month quasi - periodicity of atmospheric processes. The physical-statistical method of regional forecast of monthly air temperature and precipitation anomaly for the winter months over the territory of Ukraine is based on principles of the ensemble of analogues of atmospheric processes and the two-month quasi-periodicity of atmospheric processes. The predictors for predicting future circulation processes are integral characteristics of the geopotential fields on the 500 hPa height. Integral characteristics are obtained via latitudinal averaging between 40N and 70N. When selecting similar processes, the principle of "floating" analogue is applied. That mean when searching for analogues from the archive, some longitudinal and time shift are assumed relative to the territory and calendar dates of the current synoptical processes. The evolution of large-scale circulation processes lasting up to two weeks is used as a predictor. The similarity of atmospheric processes is determined by the calculation of similarity coefficients such as the criterion of geometric similarity and the average absolute error. The ensemble of the most similar processes is selected based on comparison of calculated and critical values of the similarity coefficients.