Selection of the Gridded Temperature Dataset for Assessment of Thermal Bioclimatic Environment Changes in Amu Darya River Basin

Abstract

Assessment of the thermal bioclimatic environmental changes is important to understand ongoing climate change implications on agriculture, ecology, and human health. This is particularly important for the climatologically diverse transboundary Amy Darya River basin, a major source of water and livelihood for millions in Central Asia. However, the absence of longer period observed temperature data is a major obstacle for such analysis. This study employed a novel approach by integrating compromise programming (CP) and multicriteria group decision–making methods (MCGDM) to evaluate the efficiency of four global gridded temperature datasets based on observation data at 44 stations. The most reliable gridded data was used to assess the spatial distribution of global warming-induced unidirectional trends in thermal bioclimatic indicators (TBI) using a modified Mann-Kendall (MMK) test. Ranking of the products revealed Climate Prediction Center (CPC) temperature as most efficient in reconstruction observed temperature, followed by TerraClimate and Climate Research Unit (CRU). Assessment of TBI trends using CPC data revealed an increase in the minimum temperature in the coldest month over the whole basin at a rate of 0.03 to 0.08\(℃\) per decade, except in the east. Besides, an increase in diurnal temperature range and isothermally increased in the east up to 0.2\(℃\) and 0.6% per decade, respectively. The results revealed negative implications of thermal bioclimatic change on water, ecology, and public health in the eastern mountainous region and positive impacts on vegetation in the west and northwest.