Convection-permitting climate simulations for the 21st century based on SSP3-7.0 scenario over the Black Sea basin

Abstract

The human influence on global climate change has been at an unprecedented rate since the pre-industrial era. The general circulation models (GCMs) are the primary tools for climate change studies. Moreover, the regional climate models (RCMs) provide more detailed and physically more reliable climate information at higher resolutions. Recently RCMs are run at a horizontal resolution of higher or equal to 4 km, so-called convection-permitting models (CPMs). In this study, we performed CMIP6-based historical and future convection-permitting climate simulations at 3 km horizontal resolution for 2005-2014 and 2061-2070 periods based on the SSP3-7.0 greenhouse gas emission scenario by using the Weather Research and Forecasting (WRF) model. We downscaled the last generation high-resolution Max Planck Institute for Meteorology Earth System Model (MPI-ESM-HR) outputs over the Black Sea Basin. We evaluated the historical simulation outputs using high-resolution gridded observational and reanalysis datasets and station observations. Following that, we examined the future changes in the climate of the Black Sea Basin. In terms of maximum temperature, the WRF model has a negative bias in winter and spring, especially in mountainous regions, and a positive bias of about 3°C compared to gridded datasets in summer and autumn over the study area. Compared with the monthly station observations, the WRF model significantly improves MPI-ESM-HR outputs and reduces the bias. Similarly, for the minimum temperatures, although the WRF model has a positive bias of about 4°C compared to the gridded datasets in all seasons, comparisons with station observations show that it significantly improves MPI-ESM-HR outputs by reducing the bias. In terms of precipitation, compared to gridded datasets, the WRF model has a positive bias of about 6 mm/day in winter over mountainous areas due to the positive bias of MPI-ESM-HR. However, compared with the station observations, the WRF model better estimates the daily precipitation probabilities than one of the MPI-ESM-HR outputs. In particular, it outperforms MPI-ESM-HR for high amounts of daily precipitation exceeding 50 mm at high-elevation stations. Also, the WRF model provides better estimations of 3-hourly precipitation probabilities than MPI-ESM-HR, especially over the northeast of Turkey and the Eastern Black Sea region.