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Evaluation and Comparison of CMIP5 and CMIP6 Models in Estimating Precipitation in Iran
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Nima Nemati Shishehgaran   , Fariba Babaeian , Hojjat Mianabadi * |
| Tarbiat Modares University |
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Abstract: (25 Views) |
Global warming can significantly alter the water cycle and precipitation patterns on Earth. Climate models are primary tools for projecting precipitation changes and assessing the impacts of climate change in various fields. The objective of this study is to assess the simulation performance of the CMIP6 and CMIP5 models and to detail the efficacy of each climate model in estimating precipitation patterns in Iran. Accordingly, the precipitation simulation performance of 30 climate models from CMIP6 and CMIP5, as well as their multi-model ensemble for Iran, was evaluated against observational data. After bias correction of the simulated precipitation values using the quantile mapping method, the performance of each General Circulation Model (GCM) will be assessed using the Taylor skill score (TSS) and Taylor diagram, which includes correlation, standard deviation, root mean square deviation. In the following, the spatial and temporal patterns of simulated precipitation in Iran by the CMIP6 and CMIP5 models were compared using the relative bias criterion. The findings from the Taylor diagram and the TSS metric reveal that while most CMIP5 models display a standard deviation closer to observational data than CMIP6 models, overall, the majority of CMIP6 models exhibit superior performance in simulating precipitation in Iran. Moreover, the multi-model ensemble (MME) of both generations of CMIP models outperformed the individual models, with CMIP6-MME demonstrating superior performance compared to CMIP5-MME. In terms of spatial and temporal variations, there exist relative bias between the observed and simulated precipitation values by the CMIP5 and CMIP6 models, with the CMIP6-MME exhibiting a lower relative bias compared to the CMIP5-MME. The results of this study can provide a scientific foundation for future research on hydrological cycle predictions in Iran and for evaluating the vulnerable water security and climate conditions in the West Asia region.
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Article number: 6 |
| Keywords: Climate Models, Quantile Mapping, Relative Bias, Spatial and Temporal Precipitation Patterns, Taylor Diagram |
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Type of Study: Research |
Subject:
Special
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