Seasonal climate forecasting: from scientific foundations to practical solutions

Abstract

This article provides a review of methods of seasonal climate
forecasting. The evolution of forecasting techniques is traced  from early
empirical-statistical approaches, based on identifying stable relationships within
the climate system, to modern complex dynamic and hybrid models, including
artificial intelligence methods. Special emphasis is placed on the role of key
climate processes, such as El Niño–Southern Oscillation (ENSO), the Madden–
Julian Oscillation, the state of the soil moisture, and Arctic sea ice, as primary
sources of predictability on seasonal timescales. The concept of "windows of
opportunity"  periods when the influence of these factors on regional circulation
is maximized, thereby enhancing forecast accuracy  is considered. The
components of a modern seasonal forecasting system are described, including the
generation of ensembles of operational and retrospective (hindcast) forecasts, the
use of multi-model approaches to assess and reduce uncertainty, and methods for
objective verification. The infrastructure of the World Meteorological Organization
is outlined, particularly the role of Global Producing Centres and Regional Climate
Centres, such as the North Eurasian Climate Centre, in adapting global forecast
products to regional and national conditions. The development of specialized
forecast products for key economic sectors is discussed separately. Promising
development directions, including impact-based forecasting, are also examined.
Keywords. Seasonal forecasting, climate models, ENSO, sources of
predictability, windows of opportunity, multi-model forecasts, North Eurasian
Climate Centre, forecast verification, impact-based forecasting.