Spatial and Temporal Analysis of Climatic Zones in Kazakhstan Using Google Earth Engine

Kazakhstan, located in Central Asia, is experiencing faster warming than the global trend, making it an important region regarding the study of how climate change is affecting climatic zones. This research aims to identify projected shifts in Köppen–Geiger climate zones under high-emission Shared Socioeconomic Pathway (SSP) 5-8.5 climate scenarios. The Köppen–Geiger climate classification system is a practical tool that effectively captures climate types based on just two variables: temperature and precipitation. Monthly temperature and precipitation data from Climatic Research Unit (CRU,) ERA5-Land, and Coupled Model Intercomparison Project Phase 6 (CMIP6) ensembles from 1951 to 2100 were used to generate climatic zone maps. CMIP6 models were evaluated against meteorological station data and ERA5-Land, with bias metrics used to identify the best-performing models for temperature and precipitation in Kazakhstan. Based on these results, two inter-model datasets were developed and used to generate Köppen–Geiger climate maps for high-emission scenarios for the 2061–2100 time period. This research resulted in two key outcomes. First, to facilitate this analysis, a Google Earth Engine (GEE) application was developed as an open accessible tool for dynamic visualization of Köppen–Geiger climate maps. Second, projected maps based on CMIP6 SSP5-8.5 scenario projections indicate that southern Kazakhstan may shift to BSh (Hot Semi-Arid) and Csa (Mediterranean) climates, and the southwest region of the country is projected to shift to a BWh (Hot Desert) climate. These projected Köppen–Geiger climate maps contributed to climate adaptation efforts by identifying regions at risk of desertification and aridification. This study provides a comprehensive analysis of climate zone transformations in Kazakhstan and offers a practical scalable geovisualization tool for monitoring climate change impacts. This allows users easy access to climate-related information and insights into data processing procedures.