Monitoring and Predictive Estimations of Atmospheric Parameters in the Catchment Area of Lake Baikal

Abstract

The paper is concerned with a methodological approach to monitoring the state of atmospheric parameters in the catchment area of Lake Baikal, including real-time analysis of actual distributed data with the determination of analog years according to the preset proximity of comparative indicators and the most probable long-term predictive distributions of surface temperatures, precipitation, pressure, and geopotential with a lead time of up to 9–12 months. We have developed the information-analytical system GeoGIPSAR to conduct the real-time analysis of spatial and point data by various processing methods and obtain long-term prognostic estimates of water inflow into the lake.

Keywords

• monitoring
• atmospheric parameters
• analog years
• neural network
• global predictive model
• predictive inflow estimates