A comparison of CMIP6 and CMIP5 projections for precipitation to observational data: the case of Northeastern Iran

The present study aimed to assess the performance of CMIP6 and CMIP5 projects in projecting mean precipitation at annual, summer, autumn, winter, and spring timescales in the north and northeast of Iran over the period 1987-2005 using relative bias, correlation coefficient, root mean square error, relative error, and the Taylor diagram. This is the first attempt to compare CMIP6 and CMIP5 data in an arid region at a seasonal and annual scale. The results showed that the precipitations simulated by the ensembles of CMIP6 and CMIP5 models were different. The relative bias for winter was lower at all stations in CMIP6 than in CMIP5, so CMIP6 performed better in this respect. CMIP6 outperformed CMIP5 in projecting annual and spring precipitation in 60 and 69% of the stations, respectively. Whereas CMIP6 overestimated precipitation in 70% of the stations, CMIP5 underestimated it in 77% of the stations. CMIP5 models exhibited better performance in 70% of the stations only in autumn. In most seasons and stations, CMIP6 CGMs' ensemble outperformed CMIP5. The results of HadGEM2-ES from CMIP5 and CESM2 from CMIP6 were more accurate than the models' ensembles in both projects. Overall, CMIP6 models exhibited better performance than CMIP5 models.