Assessing the Potential Impacts of Climate Change on Drought in Uzbekistan: Findings from RCP and SSP Scenarios

1. Introduction

The profound and multifaceted challenges posed by global warming and climate change have increasingly captured the attention of the scientific community [1,2,3]. The Intergovernmental Panel on Climate Change (IPCC)’s Sixth Assessment Report paints a stark picture, documenting a remarkable increase in global surface temperature. According to the report, from 1850–1900 to 2001–2020, the global surface temperature increased by 0.99 °C, accelerating to 1.09 °C when comparing 1850–1900 to 2011–2020 [4]. This increase, as described by various climate models [5], is expected to amplify the hydrological cycle and cause an uneven global distribution of precipitation. Evaporation rates are expected to increase with temperature, potentially outpacing precipitation increases and escalating drought risks, especially in water-scarce regions. Since the mid-20th century, the frequency and severity of droughts have increased in many regions of Africa, East Asia, and South Asia, affecting agriculture and wild ecosystems [6]. Understanding future dry–wet climate trends is critical to addressing the challenges posed by global warming.

Scenarios describing future human-induced climate change trends are a key focus of climate research. The Coupled Model Intercomparison Project (CMIP), operational since 1995, coordinates international climate model experiments to improve the understanding of historical and future climate dynamics [7]. CMIP5 (initiated in 2008) [8] and CMIP6 (initiated in 2016) [9,10] have conducted extensive simulations using updated models and scenarios to project future climate change. These efforts contribute significantly to the IPCC assessments by providing insights into temperature patterns, precipitation trends, sea level variations, and climate mechanisms that are essential for the development of mitigation and adaptation strategies [7,9,10,11,12,13]. Despite the inherent uncertainties in model simulations, the multi-model ensemble mean (MME) is quite robust. Bias correction methods adjust model outputs, resulting in more accurate climate predictions and enabling policy makers to make informed decisions [14,15].

Central Asia (CA) has become a region of significant concern in the face of global warming, primarily because of its low precipitation and consequent constraints on water availability [16]. Therefore, understanding the changes in natural water resources induced by climate change is of paramount importance. Research shows a remarkable trend in global dryland temperatures, with a significant increase since the late 1940s, exceeding both global and Northern Hemisphere averages [17]. CA exhibits a worrisome divergence in water dynamics, with potential evapotranspiration increasing...