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Showing 2 results for Aogcm Model

M. Zareian,
Volume 26, Issue 2 (9-2022)
Abstract

This study was conducted to investigate the effects of climate change on temperature and precipitation changes in important synoptic weather stations in Yazd province (including Yazd, Bafgh, Marvast, and Robat-e-Poshtebadam). Accordingly, a combination of the outputs of the latest AOGCM models presented in the IPCC sixth assessment report (CMIP6) were used to increase the accuracy of temperature and precipitation forecasts. A weighting method was used based on the Kling-Gupta combined index (KGE) to combine these models. After weighting the models, the monthly temperature and precipitation changes were calculated based on SSP126, SSP245, and SSP585 emission scenarios. Then, daily temperature and precipitation time series were extracted for different weather stations using the LARS-WG downscaling model. The results showed that in all the weather stations, CanESM5 and BCC-CSM2-MR models have the best ability to simulate the temperature and precipitation of the historical period, respectively. Results also showed that in all emission scenarios, the annual temperature will increase and the annual precipitation will decrease. The annual temperature of this region will increase between 0.2 to 0.6 °C, and the annual precipitation will decrease between 2.9 and 13.7% in different weather stations. Also, the maximum temperature increase and precipitation decrease in this region, will occur in spring and autumn, respectively.

M.j. Zareian, R. Seraj Ebrahimi, H. Dehban,
Volume 28, Issue 3 (10-2024)
Abstract

In the present study, the impact of climate change on maximum temperature and daily precipitation in 16 weather stations was investigated in the Sefidrood Basin from 2023 to 2052. 10 AOGCM models related to the sixth IPCC Assessment Report (CMIP6) were ranked based on their ability to simulate temperature and precipitation in the historical period (1980 to 2014). Then, the maximum temperature and daily precipitation outputs of the best model at each weather station were extracted using the LARS-WG downscaling model under three emission scenarios SSP126, SSP245, and SSP585 from 2023 to 2052. The Mann-Kendall test (95% confidence level) was also used to investigate the trend of changes in the average maximum temperature and maximum daily precipitation. The results showed that different AOGCMs have different accuracies in simulating temperature and precipitation in different regions of the basin, and their accuracies in simulating temperature were better than simulating precipitation. In general, the IPSL-CM6A-LR and HadGEM3-GC31-LL models had the best performance in simulating maximum temperature and precipitation, respectively. Results also indicated that the mean maximum temperature will increase between 0.9 and 2.8 °C in different emission scenarios. Also, the mean maximum daily precipitation will change between -8.6 and 7.17 mm in different emission scenarios.


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