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The modeling of coronal mass ejections (CMEs) arrival to Earth was carried out using a one-dimensional drag-based model (DBM) over the period from 2010 to 2018. The CME propagation model includes a simulation of the interaction of the CME with background solar wind via the quasi-stationary solar wind (QSW) model. An analysis of the results of forecasting CME speed and time of arrival to Earth was performed. Input data were obtained from the CACTus database. To ensure real-time operation, a new algorithm was established to select events that can reach Earth more likely. Coronal dimming data were used to obtain coordinates of the CME source location. Forecasting results have been compared with interplanetary CME (ICME) catalogs. The system has predicted 189 of 280 events (68%), with a tolerance of 48 h for the period of maximum solar activity (from 2010 to 2015). The average absolute error of predicted CME arrival speed is about 90 km/s. Our system has predicted 80% of ICMEs associated with extreme geomagnetic storms (Dstmin ≤ −100 nT) within a tolerance of 24 h.

Solar wind (SW) disturbances associated with coronal mass ejections (CMEs) cause significant geomagnetic storms, which may lead to the malfunction or damage of sensitive on-ground and space-based critical infrastructure. CMEs are formed in the solar corona, and then propagate to the Earth through the heliosphere as Interplanetary CME (ICME) structures. We describe the main principles in development with the online, semi-empirical system known as the Space Monitoring Data Center (SMDC) of the Moscow State University, which forecasts arrival of ICMEs to Earth. The initial parameters of CMEs (speeds, startup times, location of the source) are determined using data from publicly available catalogs based on solar images from space telescopes and coronagraphs. After selecting the events directed to Earth, the expected arrival time and speed of ICMEs at the L1 point are defined using the Drag-Based model (DBM), which describes propagation of CMEs through the heliosphere under interaction with the modeled quasi-stationary SW. We present the test results of the ICME forecast in the falling phase of Cycle 24 obtained with the basic version of SMDC in comparison with results of other models, its optimization and estimations of the confidence intervals, and probabilities of a successful forecast.