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.

The global climate models (GCMs) performances of the recently released Coupled Model Intercomparison Project phase 6 (CMIP6) compared to its predecessor, CMIP5, are evaluated to anticipate the expected changes in climate over Egypt. Thirteen GCMs and their multi‐model ensemble (MME) of both CMIPs were used for this purpose. The future projections were compared for two radiative concentration pathways (RCP 4.5 and 8.5) and two shared socio‐economic pathways (SSP 2–4.5 and 5–8.5). The results revealed improvement in most CMIP6 models in replicating historical rainfall, maximum temperature (Tmax), and minimum temperature (Tmin) climatology over Egypt. The MME of the CMIPs revealed that both could reproduce Egypt's spatial distribution and seasonal climate variability. However, the bias in CMIP5 was higher than that for CMIP6. The uncertainties in simulating seasonal variability of rainfall and temperatures were lower for CMIP6 compared to CMIP5. The future projection of rainfall using CMIP6 MME revealed a higher reduction of precipitation (10–26 mm) in the economically crucial northern region than that estimated using CMIP5 (0–17 mm), compared to 133.5 mm rainfall in the base period. CMIP6 also projected a 0.74–1.63°C more rise in Tmax and Tmin compared to CMIP5 by the end of the century. The study indicates more aggravated scenarios of climate changes in Egypt than anticipated earlier, using the CMIP5 models. Therefore, Egypt needs to streamline the existing adaptation and mitigation measures to account for climate projections.

The study evaluated the ability of 11 global climate models of the latest two versions of the Coupled Model Intercomparison Project (CMIP5 and CMIP6) to simulate observed (1965–2005) rainfall, maximum (T_max) and minimum (T_min) temperatures, mean eastward (uas) and northward (vas) wind speed, and mean surface pressure. It also evaluated relative uncertainty in projections of climate variables using those two CMIPs. The European reanalysis (ERA5) data were used as the reference to evaluate the performance of the GCMs and their mean and median multimodel ensembles (MME). The study revealed less bias in CMIP6 GCMs than CMIP5 GCMs in simulating most climate variables. The biases in rainfall, T_max, T_min, uas, vas, and surface pressure were −55 mm, 0.28 °C, −0.11 °C, −0.25 m/s, −0.06 m/s, and −0.038 Kpa for CMIP6 compared to −65 mm, 0.07 °C, −0.87 °C, −0.41 m/s, −0.05 m/s, and 0.063 Kpa for CMIP5. The uncertainty in CMIP6 projections of rainfall, T_max, T_min, uas, vas, and wind speed was relative more narrow than those for CMIP5. The projections showed a higher increase in T_min than T_max by 0.64 °C, especially in the central region. Besides, rainfall in most parts of MENA would increase; however, it might decrease by 50 mm in the coastal regions. The study revealed the better ability of CMIP6 GCMs for a wide range of climatic studies.

Successful concepts are adopted throughout the phases of the building lifecycle to provide maximum comfort and benefits to occupiers without compromising the function of such a project. Although there is limited information on building information modeling (BIM) execution in developing countries, BIM drivers have received significant attention from different researchers, but with a limited investigation into the influence of BIM barriers on such building projects. Our goal with this research is to identify and remove any challenges that may stand in the way of using BIM in developing country construction projects. To this end, a comprehensive literature search uncovered impediments to BIM implementation. To assess the relative importance of the numerous challenges to BIM mentioned in the literature, a survey questionnaire was distributed to a sample of specialists in the construction industry. Exploratory factor analysis (EFA) was used to classify these challenges, and partial least square structural equation modeling (PLS-SEM) was created to bring attention to the most pressing ones in the context of BIM adoption. The results of this research will inform policymakers in underdeveloped nations interested in adopting BIM on the pitfalls they should avoid.

Selection of suitable gridded precipitation data is deemed for hydroclimatic assessment and climate change impact analysis, especially in regions where long‐term reliable precipitation data is unavailable. A novel approach based on fuzzy entropy similarity analysis (FESA) is proposed to evaluate the performance of four reanalysis gridded precipitation datasets (GPDs) for Egypt, namely European Reanalysis v.5. (ERA5), TerraClimate, Global Land Data Assimilation System (GLDAS)—Noah Land Surface Model L4 v.2 and Climatologies at high resolution for the Earth's land surface areas (CHELSA), against gauge records. The proposed method was verified using conventional statistics. Besides, the relative performance of different GPDs was verified according to their response to the influence of North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO) on winter precipitation. The performance of the best reanalysis GPD was also compared with the gauge‐based global precipitation climatology centre (GPCC) dataset to show its reliability. The FESA revealed CHELSA as the best reanalysis GPD for Egypt. The performance assessment of GDPs based on conventional statistical metrics and visual presentation confirms the results obtained using FESA. CHELSA showed significant correlations with NAO (r = 0.3627) and MO (r = 0.624) like that obtained for gauge records. CHELSA also showed a better representation of precipitation in Egypt than GPCC at nearly half of the gauge locations. As CHELSA has a much higher spatial resolution than GPCC, it can be recommended as the proxy of gauge records in Egypt. The FESA can be used for performance analysis of gridded climate data by avoiding the complexities of using multiple statistical metrics.