Assesment of drought in a future climate over Turkey with COSMO-CLM

Abstract

Many physical processes interact to create a region's climatic conditions. Climate parameters may change over time as a result of human-caused or natural factors. Changes in climate parameters have occurred as a result of the greenhouse gases and geographical changes caused by climate change. However, the sources of human-caused climate change are becoming more numerous. Climate models are used to forecast the future effects of climate change. Drought is also affected by expected changes in climate parameters. Drought indices can be used to examine dry and humid periods that occur on a regular basis. These indices, which can be calculated using a variety of periods and variables, provide information on the frequency, severity, and duration of drought. Information about future dry and humid periods can be obtained by calculating the drought index using future simulations obtained from climate models. In this study, drought analysis was carried out with the help of COSMO-CLM climate simulations and data projected according to the RCP8.5 scenario and drought indices. This study aims to examine how the current temperature and precipitation in the reference period will be in the future and the expected changes in the dry period and values with the effect of climate change on temperature and precipitation. In the study, NEWA-WRF and ERA5-Land were used for bias correction. Since the SPI and SPEI values calculated with ERA5-Land are more accurate after the bias and correlation calculations, the COSMO reference period and future corrections were made with ERA5-Land. The method used in bias correction is Quantile Mapping (QM), which is used in many studies. The transformation method, which is a variant of this method, and which uses non-parametric and empirical variables, which gives more accurate results, especially for variables that are nonlinear such as precipitation, was used. Afterward, SPI and SPEI indices were selected as drought indices. These indices have been chosen because they are two methods that are used quite frequently and they are easy to calculate. SPI and SPEI have the same index values, with positive values meaning "moist" and negative values meaning "dry". First, calculations were made between 1989 and 2018 with ERA5-Land, WRF, and station observation data. Similar results were obtained in each data set. Subsequently, each data set was studied temporally. Similar distributions and values were obtained for SPI and SPEI. However, longer dry periods were investigated in the SPEI. Furthermore, the ERA5-Land and COSMO data between 1989 and 2005 were adjusted to apply bias correction to the future simulations, and the future simulations were made more accurate with this correction. Different methods were tried, but the most efficient result was obtained by performing non-parametric transformations. Additionally, corrected with precipitation and temperature future drought index values were calculated. Since SPI only uses precipitation data, the effect of temperature with SPEI is also considered. The indices were examined and evaluated spatially and temporally. In the results obtained, a decrease in precipitation and an increase in temperatures are expected in the general framework. While the expected increases may cause meteorological, agricultural, and hydrological problems in the short term, they may cause significant damage to the socio-economics as a result of all of them in the long term.