The aim of this study was to do attribution of climate change to the extreme snow fall of Mazandaran province in the northern part of Iran and southern shores of the Caspian Sea in the vicinity of Alborz mountains. The area is not prone to extreme snow fall or even snow fall then this phenomenon has had great damages to the infrastructures of the region. The study is performed on the time interval of 1987-2017in winter time (DJF). Corresponding calculation is done for two parallel worlds of counterfactual i.e. without external forcing and factual with external forcing in the context of stochastic climate modeling. This is done by the chaotic dynamical 3-D model Lorenz-63. Then the two worlds of study are defined on the basis of LM-63 and SLM-63 as deterministic and stochastic climate models. Fakher- Planck equation had the role of implementing time evolution of the PDF into the modal. The conditional probability and Bayesian framework is the preliminaries of the method of this study. The model is belonging to the space state models and Bayesian recursive estimation. These all is the basis of the EnKF as nonlinear filtering approach to the nonlinear dynamical model of this study. It is tried to bring down all the related situation associated with the issue on the basis of sound mathematical, epistemological and physical foundations. All the computations are done on the environment of GIS, Matlab, Mathematica and Maple. Then causal theory of pearl (2000) is used as the evidence of verification for the whole process. The final results showed that the extreme snow of Mazandaran province is attributable to the climate forcing defined for the study 0.8978 in its PN causation, 0.1942 in its PS causation and 0.4519 in its PNS causation.
