A novel selection method of CMIP6 GCMs for robust climate projection

The selection of global climate models (GCMs) is a major challenge for reliable projection of climate. A novel method is introduced in this study to select couple model intercomparison project phase 6 (CMIP6) GCMs. Climatology maps of GCM simulated precipitation, maximum temperature and minimum temperature data were rasterized to form 8-bit grey scale images, which were subsequently merged to form a colour image. The GCMs' climatology images were compared with the climatology image prepared using gridded climate data for their performance assessment. This allowed an unbiased comparison of GCMs according to their ability to reconstruct three major climate variables' climatology. The proposed method was employed for CMIP6 GCMs selections and projection of climate of Egypt for different shared socioeconomic pathway (SSP) scenarios. The study recognized four GCMs suitable for climate projections of Egypt, ACCESS-CM2, AWI-CM-1-1-MR, BCC-CSM2-MR and MRI-ESM2-0. The selected models' biases in simulating precipitation and temperature showed consistent results, underestimating the north and overestimating in the south for rainfall. However, the projections of different GCMs showed a considerable inconsistency. Overall, the results indicated a possible decrease in annual and winter precipitation in the range of 0 to -50% in the high rainfall regions in the north and a large increase in the low rainfall (similar to 5 mm) region in the south. The low rainfall zone in the south showed a gradual expansion with the increase of SSPs and time. The maximum and minimum temperature showed a higher increase in the south, particularly southeast (>6 degrees C in the far future) and least in the northern coastal zone.

Automated summary

This study introduces a novel method to select CMIP6 GCMs for climate projection, assessing their ability in reconstructing climate variables. Four suitable GCMs for climate projections in Egypt were identified, with consistent biases in simulating precipitation and temperature.