Projected wind changes in the Caribbean Sea based on CMIP6 models

Usta, David Francisco Bustos; Parra, Rafael Ricardo Torres

doi:10.1007/s00382-022-06535-3

Cited by 7 publications

(3 citation statements)

References 69 publications

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“…Compared to the case under SSP2‐4.5, the area where the difference between W ref and W 50 decreases is larger under SSP5‐8.5, with the magnitude of change more pronounced in the Tibetan Plateau. The difference between W ref and W 50 shows a negative relationship with the increase in the intensity of anthropogenic emissions, which could be related to the enhanced atmospheric flow velocity under climate change (Bustos Usta & Torres Parra, 2022; Wu et al., 2020).…”

Section: Resultsmentioning

confidence: 99%

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Zhao,

Huang,

et al. 2024

JGR Atmospheres

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Wind energy has grown rapidly in recent years as a measure to control carbon emissions and mitigate climate change. Extreme wind can damage wind turbines, cause losses to wind power plants, limit economic benefits of wind energy facilities, and disrupt regional grid balance. Therefore, an accurate assessment of extreme wind speeds at wind turbine hub height and their spatiotemporal variation under climate change is critical for the planning of wind energy and for guaranteeing regional energy security. In this study, the 100‐m extreme wind speeds in China are estimated using an empirical downscaling and Bayesian model averaging ensemble method with the latest ERA5 reanalysis and 20 global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). Two shared socioeconomic pathways (SSP), that is, SSP2‐4.5 and SSP5‐8.5, are considered to account for the uncertainty in anthropogenic emissions. According to the results, the highest extreme wind speeds are primarily found in Inner Mongolia, northeast China, western Tibet, and the eastern coastal region. Extreme wind speeds in central and southeastern China are projected to increase by approximately 2% in the middle (2031–2060) and the end (2071–2100) of the 21st century relative to the baseline period (1985–2014). Summer extreme wind speeds in northwestern Tibet are expected to increase by more than 9% at the end of the century. The findings of this study indicate that it is important to take the present and projected changes in local wind extremes into account when choosing locations for wind power plants and wind energy installations.

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Section: Resultsmentioning

confidence: 99%

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Zhao,

Huang,

et al. 2024

JGR Atmospheres

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“…ERA5 incorporates several data from various kinds of observations such as buoys, satellites, and radiosondes into the model to produce long-record data [23] using the assimilation method. Thus, it has been widely used in climate studies to assess the accuracy of model outputs [24,25].…”

Section: Model Institutionmentioning

confidence: 99%

“…The affix "R" (rank) denotes the individual position in each metric. The final rank is determined by performance order from the smallest to the largest "R_tot" (sum of individual ranks assigned to each CMIP6 model based on the statistical metrics SS, MS, NSE, and IA, following [25]). To better understand the CMIP6 skill over the study area, Figure 2 presents the spatial MMM correlation and bias error (deviation between ERA5 and MMM).…”

Section: Perfomance Of Cmip6 Models In Historical Period (1985-2014)mentioning

confidence: 99%

Near-Future Projection of Sea Surface Winds in Northwest Pacific Ocean Based on a CMIP6 Multi-Model Ensemble

Bayhaqi,

Yoo,

Jang

et al. 2024

Atmosphere

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Information about wind variations and future wind conditions is essential for a monsoon domain such as the Northwest Pacific (NWP) region. This study utilizes 10 Generalized Circulation Models (GCM) from CMIP6 to evaluate near-future wind changes in the NWP under various climate warming scenarios. Evaluation against the ERA5 reanalysis dataset for the historical period 1985–2014 reveals a relatively small error with an average of no more than 1 m/s, particularly in the East Asian Marginal Seas (EAMS). Future projections (2026–2050) indicate intensified winds, with a 5–8% increase in the summer season in the EAMS, such as the Yellow Sea, East Sea, and East China Sea, while slight decreases are observed in the winter period. Climate mode influences show that winter El Niño tends to decrease wind speeds in the southern study domain, while intensifying winds are observed in the northern part, particularly under SSP5-8.5. Conversely, summer El Niño induces higher positive anomalous wind speeds in the EAMS, observed in SSP2-4.5. These conditions are likely linked to El Niño-induced SST anomalies. For the application of CMIP6 surface winds, the findings are essential for further investigations focusing on the oceanic consequences of anticipated wind changes such as the ocean wave climate, which can be studied through model simulations.

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CMIP6 Ocean and Atmospheric Climate Change Projections in the Seaflower Biosphere Reserve—Caribbean Sea—by the End of the Twenty-First Century

Usta,

Parra

2024

Disaster Risk Reduction

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Seventeen climate models from CMIP6 were examined to assess the expected behavior of seven atmospheric/ocean variables in the Caribbean Basin and the Seaflower Biosphere Reserve (SBR) during the twenty-first century, under two socioeconomic scenarios (SSP2-4.5 and SSP5-8.5). Additionally, an ensemble is made with the five models with the best oceanic resolution in the Caribbean Sea. Precipitation shows significant negative trends in most of the projected periods, while air and sea surface temperature, surface salinity and mean sterodynamic sea level (SDSL) have significant positive trends. Air temperature in SBR will probably increase by 2 °C compared to the preindustrial period after 2050 (SSP5-8.5) or 2060 (SSP2-4.5). The warming trend in the region could extend the hurricane season and/or increase hurricane frequency, affect ecosystems like coral reefs and mangroves, and intensify ocean stratification. For the same period, SDSL is expected to rise in SBR between ~24.2 and 39.9 cm. If all contributing factors are included, an increase of up to ~95 cm (SSP5-8.5) could be expected by the end of the twenty-first century. This sea level rise would modify the ecological balance and enhance flooding, affecting tourism and risking the disappearance of the low-elevation islands.

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Projected wind changes in the Caribbean Sea based on CMIP6 models

Cited by 7 publications

References 69 publications

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Ensemble Bayesian Model Averaging Projections of Wind‐Speed Extremes for Wind Energy Applications Over China Under Climate Change

Near-Future Projection of Sea Surface Winds in Northwest Pacific Ocean Based on a CMIP6 Multi-Model Ensemble

CMIP6 Ocean and Atmospheric Climate Change Projections in the Seaflower Biosphere Reserve—Caribbean Sea—by the End of the Twenty-First Century

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