Seasonal forecasting of air temperature anomalies using the time analog method

Proposed is a method of forecasting the monthly mean air temperature anomalies for three months of the moving season based on the statistical analysis of the array of analogous processes of temperature variations specially selected for the initial season using the operational forecast for the first ten-day period of prognostic period being available by the beginning of the forecast. The array of analogous processes is used for revealing the most frequently observed values of temperature anomalies in the future. The overall station-by-station analysis gives a field of anomaly forecast for the CIS territory for three forthcoming months and for a season. Presented is the assessment of forecasts issued from January 2007 to December 2010 using the real ten-day period forecasts. The estimates of forecasts based on the model using the normals for 1979?C2007 are also considered.