Application of statistical correction to deterministic air temperature and precipitation forecasts for the Arctic region produced by SL-AV model
The method of statistical correction of ensemble seasonal forecasts from hydrodynamical model SL-AV for the Arctic region has been tested. The method is based on the use of multiple linear regression and the normalized forecast data previously decomposed by empirical orthogonal functions. The best predictors combinations were identified using the cross-validation mode. These estimates of corrected retrospective forecasts using SL-AV model showed a significant improvement in the quality of forecasts based on historical base period, and they can be used for operational long-range deterministic forecasting. The skill scores of corrected air temperature and precipitation forecasts over the Arctic region are higher than those for "raw" forecasts for the whole 1981-2010 period.