Incorporating Natural Changes in Global Climate in Very-Long-Range Forecasting of River Runoff

A method is proposed for incorporating possible global changes in the state of the atmosphere, basing on K. Hasselmann’s theory of stochastic climate models, for assessing the significance of forecasts of variations of annual river runoff depth in the XXI century. The data used includes the results of river runoff simulation at warming, obtained using 21 IPCC climate models along with six IPCC scenarios of greenhouse gas emission, and MEI scenario. The significance index of forecasted runoff variations, i.e., the values of runoff depth increments divided by the standard error of forecasts was mapped. To demonstrate the role of the maps of significance index, which have been constructed taking into account forecast uncertainty because of the natural changes in global climate, those maps were compared with the maps of significance index calculated basing on other sources of errors. At large time scales, the uncertainty of runoff forecasts owing to natural changes in global climate plays the main role in assessing the reliability of forecasts in areas where greenhouse effect is strongest. Estimates of the significance index show that statistically significant changes in the annual runoff depth in the extreme northeast of Eurasia can be expected to occur not earlier than the late XXI century. In other RF regions, as well as in the majority of world areas, the forecasted changes in the annual runoff depth are comparable with the standard errors of the respective estimates or are less than they are.