Future temperature and precipitation climate indices changes over the Transcarpathia region on EURO-CORDEX multimodel ensemble
Authors:   Ukrainian Hydrometeorological Institute, Sidenko Vladyslav , Oshurok Dmytro 
Published: December 2023

This study aims to assess potential climate changes in the Transcarpathia Region in the period 2021-2050 relative to the 1991-2020 base period based on the calculation of temperature and precipitation climate indices: annual average air temperature, number of frost days (FD), number of summer days (SU), number of tropical days (TD), amount of winter precipitation, amount of summer precipitation, annual count of days with more than 20 mm precipitation (R20mm) and maximum amount of precipitation for two consecutive days (AMP2). The domain under study includes the Transcarpathia Region of Ukraine and its neighbouring territories and has extremely complicated topography, with an altitude range between 101 m and 2061 m ASL. Such complexity significantly influences an interpolation/downscaling procedure applied to climatological variables (e.g., air temperature, atmospheric precipitation, etc.). In this study, daily data collected at 11 meteorological stations located in the domain was used. Data of four essential climate variables, namely minimum air temperature (tn), mean air temperature (tm), maximum air temperature (tx), and atmospheric precipitation (rr), were used in the calculations. The period covered by the data time series is 1961-2020. Data of climate model simulations (historical and future projections) were obtained from the Coordinated Regional Climate Downscaling Experiment project for the European domain (Euro-CORDEX). In our calculations, the Euro-CORDEX daily data of tn, tm, tx, and rr (converted previously from precipitation flux) was used. We only selected Euro-CORDEX simulations which (1) were performed based on RPC4.5, (2) provide output data in the Gregorian (or similar) calendar, and (3) provide output for all four variables. Thus, a multimodel ensemble of climate simulations utilised in our calculations consists of eleven members (combinations of 5 GCMs and 8 RCMs). Quality control of the station time series was performed by means of the INQC software (https://CRAN.R-project.org/package=INQC). Homogenization was performed using the Climatol package (https://CRAN.R-project.org/package=climatol) (Guijarro, 2018). We used the MISH software (Szentimrey and Bihari, 2014) to perform gridding/downscaling of the station data on the grid with the spatial resolution of 0.05° in both horizontal directions (~5 km). Bias-correction of the climate model data was performed by means of linear/variance scaling (for the air temperature data) and quantile matching (for the atmospheric precipitation data) methods. After bias correction of the climate projection data, they were statistically downscaled by means of the MISH software to the 0.05° grid, the same as for the observation data. The downscaling was performed for the period of 2006-2050 for each climate variable and each climate model (GCM-RCM combination). Spatial fields of air temperature (minimum, average and maximum) and amounts of precipitation for each day of the historical period (1961-2020) and the period of climate projections (2006-2050) were obtained. Based on the MISH downscaled climate model data, 8 climate indices were calculated for each year of the projection period (2021-2050) and each grid point of the interpolation grid (with the 0.05° spatial resolution). Finally, differences (anomalies) in the climate indices averaged over 1991-2020 and 2021-2050, i.e. calculated base observations and projections, respectively, were computed. Our calculations showed a moderate increase in air temperature (and other related indices, such as SU and TD) in 2021-2050 compared to 1991-2020. The increase is more intensive on valleys of the domain, while mountain tops and ridges will experience less intensive changes. Atmospheric precipitation will not change significantly.