Abstract

The arid and semiarid regions of Uzbekistan are sensitive and vulnerable to climate change. However, the sparse and very unevenly distributed meteorological stations within the region provide limited data for studying the region’s climate variation. The aim of this work was to evaluate the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA)-Interim and ERA5 products for the fields of near-surface temperature, humidity, and precipitation over Uzbekistan from 1981 to 2018 using observations from 74 meteorological stations. Major results suggested that the reanalysis datasets match well with most of the observed climate records, especially in the plain areas. While ERA5, with a high spatial resolution of 0.1°, is able more accurately reproduce mountain ranges and valleys. Compared to ERA-Interim, the climatological biases in temperature, humidity, and total precipitation from ERA5 are clearly reduced, and the representation of inter-annual variability is improved over most regions of Uzbekistan. Both reanalyses show a high level of agreement with observations on the standardized precipitation evaporation index (SPEI) with a correlation coefficient of 0.7–0.8.Although both of these ECMWF products can be successfully implemented for the calculation of atmospheric drought indicators for Uzbekistan and adjacent regions of Central Asia, the newer and advanced ERA5 is preferred.

Highlights

  • Drought is a dangerous natural hazard characterized by a lower-than-normal water supply insufficient to meet the demands of human activities and the environment [1]

  • Logical parameters at 74 meteorological stations in Uzbekistan according to observations and reanalyses (ERA‐I, ERA‐5) for the period 1981–2018

  • We must emphasize the humidity in the reanalysis compared to observations, as a fat tail of high SH is not reproduced by reanalysis (Figure 2g)

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Summary

Introduction

Drought is a dangerous natural hazard characterized by a lower-than-normal water supply insufficient to meet the demands of human activities and the environment [1]. According to the report of the Intergovernmental Panel on Climate Change (IPCC), future climate change will lead to an increase in climate variability and in frequency and intensity of extreme events in the world [8]. In order to mitigate the consequences of drought, it is necessary to develop a monitoring system and forecasting methods that are based on various indicators of drought, which have usually complex characteristics. In this regard, reliable climate information is the basis for developing a climate-resilient system to minimize the region’s vulnerability to various climatic risks. Detailed observations are not always available for all required locations and variables

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