Comparison between CMIP5 and CMIP6 Models over MENA Region Using Historical Simulations and Future Projections

Hamed, Mohammed Magdy; Nashwan, Mohamed Salem; Shiru, Mohammed Sanusi; Shahid, Shamsuddin

doi:10.3390/su141610375

Cited by 41 publications

(15 citation statements)

References 74 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Importantly, this result highlights the potential value of careful management of water resources and demand-side measures in alleviating the water scarcity problem. Also, while the results are based on the AR5 climate data rather than on the most recent AR6 climate data, which have been shown to be less bias in the MENA region (Hamed et al, 2022), the finding that human systems dominate the scarcity signal in the MENA region is still robust given that the difference in renewable water supply due to climate change is much smaller than the delta in water demand (Table 1).…”

Section: Physical Assessment Of Climate Impacts On Water Scarcity In ...mentioning

confidence: 95%

Impacts of water scarcity on agricultural production and electricity generation in the Middle East and North Africa

Hejazi

Silva

Miralles‐Wilhelm

et al. 2023

Front. Environ. Sci.

View full text Add to dashboard Cite

Incorporating the interdependencies between water, energy and food (WEF) within an integrated approach of planning and management could help nations worldwide to address sustainability concerns. This is a topic of great importance for the Middle East and North Africa (MENA) region, where water is a very limited resource. In this study, we develop an analytical framework to analyze the water-energy-food nexus in the MENA region to inform the formulation of integrated strategies for water, energy and food activities. Our approach is based on an integrated assessment model for the MENA region, which explicitly represents WEF sectors within an economic framework, in tandem with a set of relevant scenarios addressing three key dimensions (socioeconomics, climate and water-management). Using this framework, our study analyzes the current and projected status of water resources in the region, and the potential implications for the agriculture and electricity sectors. Our scenarios demonstrate that water scarcity worsens by the end of the 21st century in most MENA countries, mostly due to growing demands. The impacts of growing scarcity on agriculture are significant, with production projected to drop by 60 percent by 2050 in some countries. On the other hand, and to a lesser extent, water-saving technologies and fuel-switching in the power sector play a key role in mitigating the effects of water scarcity on electricity generation in some parts of the MENA region. Our analysis then underscores the need to reduce the dependence of MENA’s agricultural and energy sectors on water, and transition to renewable energies to reduce water scarcity.

show abstract

Section: Physical Assessment Of Climate Impacts On Water Scarcity In ...mentioning

confidence: 95%

Impacts of water scarcity on agricultural production and electricity generation in the Middle East and North Africa

Hejazi

Silva

Miralles‐Wilhelm

et al. 2023

Front. Environ. Sci.

View full text Add to dashboard Cite

show abstract

“…Where r is the Pearson correlation, γ is the fraction of the coefficient of variance, and β is the normalized bias with standard deviation [16], [24].…”

Section: Kling-gupta Efficiency (Kge)mentioning

confidence: 99%

Uncertainty of Coupled Model Intercomparison Projects 6 (CMIP6) in Indonesia’s maritime continental region for the historical period

Agiel,

Pratama,

Mareta

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

Climate Model is a tool for studying climate and climate change, In climate models there is uncertainty that occurs due to the inability of the model to simulate climate in an area. This study aims to find the best CMIP6 model in the IMC and look at the uncertainty of the model. The data used in this study are precipitation data on the CMIP6 model, as well as the use of CRU data as reference data and observation data. Uncertainty is calculated for historical periods using CDF to see random values from the model. Validation of historical CRU and CMIP6 data is performed by performing statistical calculations that include Pearson correlation, standard deviation, RMSE, KGE, TSS, and relative bias. CRU model testing in Indonesia shows quite good performance at all points, the CRU model has a pattern that follows observational data based on correlation values. the uncertainty of CMIP6 is large in high precipitation and low in moderate precipitation, and there is moderate uncertainty in low precipitation, The analysis of historical data indicates that the EC-Earth3-Veg-LR model has greater performance in simulating precipitation within the IMC region, closely aligning with the values and patterns observed in the CRU model. Furthermore, the EC-Earth3-Veg-LR model displays a strong correlation, as well as good values for the KGE and relative Bias, measuring at 0.33, 0.175, and 1.101% respectively.

show abstract

“…However, the inadequacy of the CMIP5 and the regional dependence of MHWs require further study with improved numerical models. Hamed et al (2022) pointed out that most climate variables simulated in CMIP6 are less biased than in CMIP5. Preliminary studies show that the WNPCC region is one of the regions most affected by MHWs (Li et al, 2019).…”

Section: Local Oceanic Current Anomaliesmentioning

confidence: 99%

Analysis and prediction of marine heatwaves in the Western North Pacific and Chinese coastal region

et al. 2022

View full text Add to dashboard Cite

Over the past decade, marine heatwaves (MHWs) research has been conducted in almost all of the world’s oceans, and their catastrophic effects on the marine environment have gradually been recognized. Using the second version of the Optimal Interpolated Sea Surface Temperature analysis data (OISSTV2) from 1982 to 2014, this study analyzes six MHWs characteristics in the Western North Pacific and Chinese Coastal region (WNPCC, 100°E ∼ 180°E, 0° ∼ 65°N). MHWs occur in most WNPCC areas, with an average frequency, duration, days, cumulative intensity, maximum intensity, and mean intensity of 1.95 ± 0.21 times/year, 11.38 ± 1.97 days, 22.06 ± 3.84 days, 18.06 ± 7.67 °Cdays, 1.84 ± 0.50°C, and 1.49 ± 0.42 °C, respectively, in the historical period (1982 ~ 2014). Comparing the historical simulation results of 19 models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) with the OISSTV2 observations, five best-performing models (GFDL-CM4, GFDL-ESM4, AWI-CM-1-1-MR, EC-Earth3-Veg, and EC-Earth3) are selected for MHWs projection (2015 ~ 2100). The MHWs characteristics projections from these five models are analyzed in detail under the Shared Socio-economic Pathway (SSP) 1-2.6, 2-4.5 and 5-8.5 scenarios. The projected MHWs characteristics under SSP5-8.5 are more considerable than those under SSP1-2.6 and 2-4.5, except for the MHWs frequency. The MHWs cumulative intensity is 96.36 ± 56.30, 175.44 ± 92.62, and 385.22 ± 168.00 °Cdays under SSP1-2.6, 2-4.5 and 5-8.5 scenarios, respectively. This suggests that different emission scenarios have a crucial impact on MHW variations. Each MHWs characteristic has an obvious increasing trend except for the annual occurrences. The increase rate of MHWs cumulative intensity for these three scenarios is 1.02 ± 0.83, 3.83 ± 1.43, and 6.70 ± 2.61 °Cdays/year, respectively. The MHWs occurrence area in summer is slightly smaller than in winter, but the MHWs average intensity is stronger in summer than in winter.

show abstract

Comparison between CMIP5 and CMIP6 Models over MENA Region Using Historical Simulations and Future Projections

Cited by 41 publications

References 74 publications

Impacts of water scarcity on agricultural production and electricity generation in the Middle East and North Africa

Impacts of water scarcity on agricultural production and electricity generation in the Middle East and North Africa

Uncertainty of Coupled Model Intercomparison Projects 6 (CMIP6) in Indonesia’s maritime continental region for the historical period

Analysis and prediction of marine heatwaves in the Western North Pacific and Chinese coastal region

Contact Info

Product

Resources

About