The trend and spatial spread of multisectoral climate extremes in CMIP6 models

Adeyeri, Oluwafemi E.; Zhou, Wen; Wang, Xuan; Zhang, Ruhua; Laux, Patrick; Ishola, Kazeem A; Usman, Muhammad

doi:10.1038/s41598-022-25265-4

Cited by 27 publications

(13 citation statements)

References 67 publications

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“…All models except IPSL recorded high SPI RMSE (>1.8) in the area. These inconsistencies could be caused by the models' inability to resolve the solar radiation accurately (Adeyeri et al., 2022), vegetation, cloud properties (Wild et al., 2005), or other synoptic‐scale system interactions (Grose et al., 2019) of such locations.…”

Section: Resultsmentioning

confidence: 99%

“…Future climate projections have been made using climate models. However, climate models and reference data do not always agree because of the differences in land surface schemes and the modeling of components (Adeyeri et al., 2022; Dieng et al., 2022). Consequently, climate change impact projections require correcting these biases (Dieng et al., 2022; Laux et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

“…However, because specific heatwaves have a short lifespan, they may not immediately impact drought. Therefore, the HTWL considers the aggregate number of heatwaves during a specific time frame (Adeyeri et al., 2022) to account for the propagation time. Additionally, multivariate copula functions (Hao et al., 2017; Laux et al., 2011; Ma et al., 2022) were employed for combined drought modelling based on the MSDI.…”

Section: Introductionmentioning

confidence: 99%

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Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

et al. 2023

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Understanding how droughts are characterized, propagated, and projected, particularly multivariate droughts, is necessary to explain the variability and changes in drought characteristics. This study aims to understand multimodel global drought monitoring, propagation, and projection by utilizing a multivariate standardized drought index (MSDI) during the historical (1959–2014) and future (2045–2100) periods under two socioeconomic pathways SSPs (370 and 585), derived from the bias‐corrected Coupled Model Intercomparison Project Phase 6 (CMIP6). Based on the energy metrics, the multivariate bias correction method outperformed other techniques in correcting the biases in the CMIP6 drought representation. The drought indicators demonstrate distinct categories for meteorological, hydrological, and multivariate droughts. There were significant high cross correlations between Heatwave Total Length (HWTL) and MSDI in Africa and South America for all lagged times. Europe and North America generally saw the maximum MSDI drought duration (228 months) during the historical period. For future projections, Africa recorded the maximum drought duration (197 months), while Europe witnessed the minimum drought duration for SSP 370 (171 months), and North America (149 months) for SSP 585. Furthermore, during the historical period in tropical Africa, the propagation of meteorological to hydrological drought was slower during the wet months than during the dry months. Under the SSP 370 future projection, there was a shift in the long period of meteorological‐hydrological propagation from the middle and late wet months to the beginning of the wet months in tropical Africa. Therefore, tracking and projecting drought characteristics is vital for understanding the risk of drought‐related consequences.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

et al. 2023

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“…Our results, as suggested by most models and drought metrics, suggest that in a high emissions scenario drought would increase in southern North America, Central America, the Amazon region, the Mediterranean, southern Africa, and southern Australia, which agrees with earlier studies (e.g., Cook et al., 2020; Seneviratne et al., 2021; Ukkola et al., 2020; Wang et al., 2021; Zhao & Dai, 2022). These projections must be considered carefully since the models are affected by substantial biases (Adeyeri et al., 2022, 2023), strong differences with the trends in observations during the historical period (Vicente‐Serrano, Miralles, et al., 2022b) and limitations to consider key ecohydrological processes (e.g., the interactions between plant root systems, soil moisture and runoff generation with groundwater) (Miguez‐Macho & Fan, 2021; Ndehedehe et al., 2023).…”

Section: Discussionmentioning

confidence: 99%

Assessment of the Global Relationship of Different Types of Droughts in Model Simulations Under High Anthropogenic Emissions

Gimeno‐Sotelo,

El Kenawy,

Franquesa

et al. 2024

Earth's Future

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This study provides a global analysis of the relationship between drought metrics obtained from several climatic, hydrologic and ecological variables in a climate change framework using CMIP6 model data. A comprehensive analysis of the evolution of drought severity on a global scale is carried out for the historical experiment (1850–2014) and for future simulations under a high emissions scenario (SSP5‐8.5). This study focuses on comparing trends in the magnitude and duration of drought events according to different standardized indices over the world land‐surface area. The spatial and temporal relationship between the different drought indices on a global scale was also evaluated. Overall, there is a fairly large consensus among models and drought metrics in pointing to drought increase in southern North America, Central America, the Amazon region, the Mediterranean, southern Africa and southern Australia. Our results show important spatial differences in drought projections, which are highly dependent on the drought metric employed. While a strong relationship between climatic indices was evident, climatic and ecological drought metrics showed less dependency over both space and time. Importantly, our study demonstrates uncertainties in future projections of drought trends and their interannual variability related to the relationship among indices, stressing the importance of coherent climatic, hydrological and plant physiological patterns when analyzing CMIP6 model simulations of droughts under a warming climate scenario.

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“…The CMIP6 dataset combines observations with other exogenous forcings like volcanic aerosols, solar variability, and changes in the atmospheric composition of greenhouse gases and atmospheric aerosols [47,48]. While SSP585 is the only SSP with emissions adequate to provide the 8.5 W/m 2 level of forcing in 2100, SSP370 represents the medium-to-high end of projected future emissions and temperature scenarios [45,48]. In SSP585, technical advancement, notably agricultural production, is strong while characterized by fast and resource-intensive development and material-intensive consumption habits.…”

Section: 0mentioning

confidence: 99%

Land use and land cover dynamics influence the thermal stress spread and energy demands

Adeyeri,

Zhou,

Laux

et al. 2023

Preprint

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This study examined the interaction between land use land cover (LULC) dynamics and thermal stress distribution using the universal thermal comfort index (UTCI) and different LULC classifications under two Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathways (i.e., SSP 370 and 585) climate and land use scenarios for the historical (1959–2014) and future period (2045–2100). The moderate to strong cold stress in the annual and winter climatology in the midlatitudes was replaced by no thermal stress in the summer, while the summertime ranged from moderate to strong heat stress. A negative correlation was observed between thermal stress and southern hemispheric primary forests. Perennial croplands had the most dynamic active change intensities during the historical period. Primary nonforest and secondary forests actively influenced global thermal stress. Areas in the tropics recording moderate heat stress coincided with secondary nonforest, pastureland and annual cropland expansions. The conversion of forest to range land and croplands and the subsequent negative forest trends increased the severity of thermal stress. The future projection showed more intense thermal stress; however, the SSP 585 signals were more potent. As a result, cooling demands will rise, and heating demands will decline; yet, improved thermal comfort necessitates a higher cooling capacity, especially in the summer. Thermal stress may make it difficult for many cooling systems to meet people’s energy demands. These could be a driving factor in shaping better land use policies, improved energy demand preparedness and elucidating the potentially severe impacts of thermal stress.

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The trend and spatial spread of multisectoral climate extremes in CMIP6 models

Cited by 27 publications

References 67 publications

Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

Multivariate Drought Monitoring, Propagation, and Projection Using Bias‐Corrected General Circulation Models

Assessment of the Global Relationship of Different Types of Droughts in Model Simulations Under High Anthropogenic Emissions

Land use and land cover dynamics influence the thermal stress spread and energy demands

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