Effects of observational data shortage on accuracy of global solar activity forecast

Building a reliable forecast of solar activity is long-standing problem that requires to accurately describe past and current global dynamics. However, synoptic observations magnetic fields subsurface flows became available relatively recently. In this paper, we present an investigation effects short observational data series on accuracy cycle prediction. This analysis performed using the annual sunspot number time-series applied Parker-Kleeorin-Ruzmaikin dynamo model employing Ensemble Kalman Filter (EnKF) assimilation method. The testing prediction for last six cycles (from Solar Cycle 19 24) by sequentially shortening are used target cycle, evaluating according specified criteria. According analysis, predictions can be made number. It demonstrated even two allow us obtain reasonable forecasts.