جستجوی مقالات مرتبط با کلیدواژه « نگاشت چندک » در نشریات گروه « جغرافیا »

In the current research, to investigate the future climate of the Urmia Lake catchment, the maximum and minimum temperature, rainfall and drought in the basin were projected for the period of 2015-2099 using NorESM2-MM climate model under the scenarios of SSP. The downscaling output of the model was done using the quantile mapping method and their accuracy was evaluated in the simulation of the base period (1990-2014) using the monthly diagram and RMSE and NRMSE indicators. The evaluation of the results showed that: the minimum and maximum temperature of the basin under the pessimistic scenario (SSP5-8.5) until the end of the century and under the optimistic scenario (SSP1-2.6) until 2075 have an ascending trend and then a descending trend. Average maximum and minimum temperature of the basin in the near future (1.0 to 1.8) and (1.1 to 1.8) ℃ and in the far future (1.5 to 4.8) and (1.3 to 4.3) ℃ will increase. The annual rainfall in the future period does not have a significant trend, but the average rainfall of the basin in the optimistic scenario will increase by 16.5% in the near future and 8.9% in the far future and in the pessimistic scenario will increase by 1.8% in the near future and 7.2% in the far future. According to the SPEI index, in the future period, under the optimistic scenario, moderate drought will have an ascending trend, severe drought will have a descending trend, and under the pessimistic scenario, the drought will have a descending trend.

The characteristics of drought, as one of the environmental events, may change under the effect of climate change in future periods. The current study was conducted with the aim of predicting meteorological drought in Gorganroud watershed. For this purpose, the output of temperature and precipitation of 8 General Circulation Models (GCMs), were investigated under two scenarios (SSP2-4.5) and (SSP5-8.5) during two periods of 2025-2054 and 2071-2100. To downscale the GCMs, quintile mapping bias correction method was used. After projecting the future precipitation and temperature, the SPEI index was calculated at the annual scale for the baseline and future periods. Thereafter, the drought characteristics (duration, intensity and Severity) were computed using the median results of SPEI bands based on the Run theory method. With the aim of improving the process of evaluating and quantifying the effects of climate change on future droughts in the region and showing the uncertainties caused by climate models, the prediction bands of climate variables have been used to quantify the SPEI index. According to the simulated results of performance of multi model ensemble, that in the future climate conditions, the average values of mean temperature and precipitation will increase in both scenarios; So that the temperature increases from 1.2 to 4.4 Celsius and precipitation increases by 2 to 11.9 percent. The results of this study show that the conditions of the region in the coming decades likely the normal or wet climate conditions in the near decades, but these conditions would change in the far future as the more we move towards the last decades of the century, the more occurrences of droughts would happen. The results obtained from of the Run theory indicate that the duration and magnitude intensity profiles will decrease in the SSP2-4.5 scenario and the near future period in the SSP5-8.5 scenario.

This study evaluates the ability of different quantitative mapping (QM) methods as a bias correction technique for ERA5 reanalysis precipitation data. Climate type and geographical location can affect the performance of the bias correction method due to differences in precipitation characteristics. For this purpose, ERA5 reanalysis precipitation data for the years 1989-2019 for 10 selected synoptic stations in climates with different topographic characteristics were received daily from the European Centre for Medium-Range Weather Forecasts (ECMWF) website. Bias correction of these data was performed using 5 quantitative mapping methods based on observational data in R software environment. Two-part evaluation and Taylor diagram were used to compare the performance of different methods. The results showed that the performance of the quantification mapping method depends on the performance functions, set of parameters and climatic conditions. In general, non-parametric methods of multiple mapping have better performance than parametric methods, so that the best performance is related to QUANT and RQUANT methods, among which DIST method has the weakest performance.