A novel selection method of CMIP6 GCMs for robust climate projection

Abstract

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 (~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°C in the far future) and least in the northern coastal zone.

Nonlinear ABAQUS Simulations for Notched Concrete Beams

“…All models were developed using CIT, VCCT, and XFEM. Based on the results deduced from the T6 simulations, the most suitable technique was determined by using five different statistical indicators that are used by researchers in different fields [ 37 , 38 , 39 ]. These statistical indicators are: 1. root mean square error (RMSE); 2.…”

High‐resolution reference evapotranspiration for arid Egypt: Comparative analysis and evaluation of empirical and artificial intelligence models

“…It has mild cold winters and hot summers, and rainfall is rare. The annual rainfall is about 200 mmÁyear −1 in the northern parts and less than 5 mmÁyear −1 in the far south (Nashwan et al, 2020;Yassen et al, 2020;Hamed et al, 2021a;2021b). Due to the shortage of water, most Egyptians live along the Nile in nearly 4% of Egypt's total land.…”

Projecting spatiotemporal changes of precipitation and temperature in Iraq for different shared socioeconomic pathways with selected Coupled Model Intercomparison Project Phase 6

“…GCMs are commonly used for projecting temperature and precipitation change (Her et al ., 2019). Thus a number of studies reported using ensemble of more appropriate GCMs by excluding those considered unrealistic; doing so can reduce uncertainties in mean changes in projected precipitation and temperature (Khan et al ., 2020; Nashwan and Shahid, 2020; Hamed et al ., 2022b). Besides, GCM subsetting can address the issue of resource limitations by handling many GCMs for climate change assessment (Salman et al ., 2018; Salehie et al ., 2021).…”