Performance of CMIP6 HighResMIP Simulations on West African Drought

Ajibola, Felix Olabamiji; Zhou, Botao; Shahid, Shamsuddin; Ali, Arfan

doi:10.3389/feart.2022.925358

Cited by 11 publications

(3 citation statements)

References 35 publications

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“…By selecting three CMIP6 models, we have aimed to assess the role of ECS in the prediction of aridity by using low, medium and high ECSs. Various studies have evaluated CMIP6's performance in modelling precipitation and temperature on continental or regional scales (Ajibola et al, 2020; Fan et al, 2020; Ajibola et al, 2022; Dong & Dong, 2021), and it has been shown that multi‐model ensembles perform better overall than individual models (Vogel et al, 2020; Zhao et al, 2021). Therefore, we have calculated the multi‐model means of the GFDL‐ESM4, MRI‐ESM2‐0 and IPSL‐CM6A‐LR models and assessed the results based on the multi‐model mean results.…”

Section: Methodsmentioning

confidence: 99%

Climate model projections of aridity patterns in Türkiye: A comprehensive analysis using CMIP6 models and three aridity indices

Yavaşlı,

Erlat

2023

Intl Journal of Climatology

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Climate change can alter the spatial and temporal distribution of aridity around the world through a combination of factors such as reduced precipitation, rising temperatures and decreased evapotranspiration. Especially the Mediterranean region has been identified as vulnerable to anthropogenic climate change due to a significant reduction in precipitation compared to other land regions in all climate models operated under different scenarios. Despite numerous studies on aridity trends, few have focused specifically on Türkiye and considered a comprehensive range of aridity indices and scenarios. This study aims to fill this research gap by providing a more detailed understanding of future aridity trends in Türkiye under various climate change scenarios and using multiple aridity indices. A novelty of this study lies in the simultaneous examination of three aridity indices (PCI, EAI and UNEP AI) for Türkiye, allowing for a more comprehensive assessment of future aridity trends. Furthermore, this study considers three future time periods (2011–2040, 2041–2070 and 2071–2100) and three shared socioeconomic pathways (SSPs) to evaluate the potential range of climate change impacts on aridity in Türkiye. Therefore, in this study, we aimed to determine the changes in aridity conditions in Türkiye until the end of the 21st century. We used three aridity indices: the Pinna combinative index, the Erinç aridity index and the UNEP aridity index. These indices were calculated for the baseline period of 1981–2010 using gridded data (CHELSA) and for the periods of 2011–2040, 2041–2070 and 2071–2100 using three climate models (GFDL‐ESM4, MRI‐ESM2‐0 and IPSL‐CM6A‐LR) and multi‐model means with three SSPs to represent different future scenarios. The results showed that all three indices indicate an increase in dry climate conditions in Türkiye after 2041, with particularly notable increases expected in Central Anatolia, Southeastern Anatolia and parts of the Eastern Mediterranean, as well as eastern parts of Eastern Anatolia and the inner Aegean region. Under the SSP3‐7.0 scenario, the expansion of semi‐arid and arid areas is predicted to cover more than 30% of the country by the end of the century (2071–2100). This increase in aridity could increase the region's vulnerability to climate change and the risk of desertification, which should be taken into consideration in national water management and planning.

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Section: Methodsmentioning

confidence: 99%

Climate model projections of aridity patterns in Türkiye: A comprehensive analysis using CMIP6 models and three aridity indices

Yavaşlı,

Erlat

2023

Intl Journal of Climatology

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“…Precise precipitation simulation in West Africa is crucial for understanding the region's climate variability and change vulnerability. Previous studies have highlighted the importance of accurate precipitation simulation in the region, particularly in light of its susceptibility to climate extremes such as droughts and oods (Sarr, 2017;Almazroui et al, 2020;Ajibola et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Impacts of improved horizontal resolutions in the simulations of mean and extreme precipitation using CMIP6 HighResMIP models over West Africa

Ajibola,

Afolayan

2024

Environ Monit Assess

Self Cite

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We analyzed 16 historical simulations from High-Resolution Model Intercomparison Project (HighResMIP) within the framework of Coupled Model Intercomparison Project (CMIP) Phase 6 (CMIP6). The simulations comprise high and low-resolution simulations. The aim is to examine the effect of improved horizontal resolution models on mean and extreme precipitation over West Africa from 1985 -2014. Observation shows southeast and southwest regions are the most active in precipitation, consistent with simulations of HighResMIP. The impact of improved horizontal resolutions is felt in the simulation of orographic-induced rainfall over the high grounds and the intensi cation of precipitation in most of the metrics employed. The observed highest 1-day precipitation shows most of the Guinea coast region had 1-day rainfall greater than 100 mm, which was over-estimated (under-estimated) by high (low) resolution simulations. Also, improvement in horizontal resolution seems to improve the capacity of highresolution models to reproduce the observed pattern of heavy precipitation (R10mm) days and very heavy rainfall (R20mm) days. The spatio-temporal analysis showed the presence of uncertainty in the simulation of both the high and low resolutions simulations in reproducing the extreme precipitation over West Africa. Due to this, a bias correction approach was employed.Recently, several studies have been done. For instance, Molteni et al. (2020) discovered the HighResMIP simulations' ability to capture the tropical Indo-Paci c rainfall and its modulations. Xin et al. (2021)

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“…Earth System (iHESP) (Small et al 2014;Chang et al 2020). These HR GCMs improve the simulation of rainfall characteristics and its associated governing mechanisms compared to their low resolution (LR) counterparts in tropical climates such as southern China (Xin et al, 2021), Malaysia (Liang et al, 2021), Indonesia (Hariadi et al, 2022;Kurniadi et al, 2022), tropical South America (Monerie et al 2020) and West Africa (Ajibola et al 2020;Ajibola et al 2022, Nkrumah et al 2022. We also use the M19 subregional classification (Fig.…”

Section: Introductionmentioning

confidence: 99%

An Evaluation of the Seasonal Caribbean Hydroclimate in Low and High-Resolution CESM and other CMIP6 Models

Martinez¹,

Simpson²,

Fasullo³

et al. 2023

Preprint

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The Caribbean and Central American hydroclimate is understudied and complex in part due to its data sparsity, varied topographies, and multi-faceted interactions with the tropics and mid-latitudes. Recent work developed a refined and comprehensive understanding of the observed hydroclimate that has yet to be explored in global circulation models. This study investigates the simulation of the Caribbean hydroclimate using a suite of station and gridded observational datasets, the Community Earth System Model version 1 (CESM1) at high (0.25x0.25°) and low (0.9x1.25°) resolution, CESM2 at low (0.9x1.25°) resolution, the Coupled Model Intercomparison Project phase 6 (CMIP6) High-Resolution Model Intercomparison Project (HighResMIP), and the Geophysical Fluid Dynamics Laboratory Seamless System for Prediction and Earth System Research (GFDL-SPEAR). The simulated climatologies (1983-2014) of the annual rainfall cycle and total moisture fluxes, and climatological correlation coefficients of sea surface temperatures (SST), sea-level pressure (SLP), and zonal/meridional low-level winds onto indices of seasonal Caribbean rainfall totals are calculated to investigate inter-model differences. Generally, fully coupled CESM, GFDL-SPEAR-MED, and CMIP6 simulations underestimate precipitation across the Caribbean, with some improvements using high-resolution (<0.5°) simulations. The underestimations are largest during the Early-Rainy Season (ERS; mid-April to mid-June). Coupled models also show a moisture divergence bias associated with a stronger/west-displaced North Atlantic Subtropical High (NASH), a weaker / southward displaced Intertropical Convergence Zone (ITCZ), and stronger Caribbean Low-Level Jet (CLLJ). Precipitation and large-scale dynamic biases in experiments with observation-based SSTs are smaller, regardless of their spatial resolution, suggesting SST biases in coupled models may contribute to precipitation and dynamic biases. The findings emphasize the importance of both high-resolution and accurate simulation of coupled dynamical interactions in global circulation models to accurately simulate the Caribbean’s hydroclimate, and, therefore, provide reliable future climate projections for the region.

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Performance of CMIP6 HighResMIP Simulations on West African Drought

Cited by 11 publications

References 35 publications

Climate model projections of aridity patterns in Türkiye: A comprehensive analysis using CMIP6 models and three aridity indices

Climate model projections of aridity patterns in Türkiye: A comprehensive analysis using CMIP6 models and three aridity indices

Impacts of improved horizontal resolutions in the simulations of mean and extreme precipitation using CMIP6 HighResMIP models over West Africa

An Evaluation of the Seasonal Caribbean Hydroclimate in Low and High-Resolution CESM and other CMIP6 Models

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