The paper presents a technology for predictive estimation of meteorological indicators based on the global climate model CFSv2. This technology provides continuous monitoring of current and prognostic indicators of the state of the atmosphere (temperature, pressure, humidity, precipitation, etc.) in the catchment basin of Lake Baikal. The monitoring and data analysis tasks are briefly described as well as the operation algorithms for the main software components intended to obtain predictive distributions of weather indicators for the average values of a given time period, predictive scenarios of the dynamics of their changes for a selected point or a separate basin. The technology involves adjusting the weights of individual ensembles of predictive data of the global CFSv2 system, which provides more reliable predictive estimates.