2023
DOI: 10.1175/jcli-d-21-0929.1
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140 Years of Global Ocean Wind-Wave Climate Derived from CMIP6 ACCESS-CM2 and EC-Earth3 GCMs: Global Trends, Regional Changes, and Future Projections

Abstract: We present four 140-year wind-wave climate simulations (1961-2100) forced with surface wind speed and sea ice concentration from two CMIP6 GCMs under two different climate scenarios: SSP1-2.6 and SSP5-8.5. A global three-grid system is implemented in WAVEWATCH III® to simulate the wave-ice interactions in the Arctic and Antarctic regions. The models perform well in comparison with global satellite altimeter and in-situ buoys climatology. The comparison with traditional trend analyses demonstrates the present G… Show more

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Cited by 25 publications
(50 citation statements)
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“…Watterson (2015) has proposed skill scores of four wind‐related variables to evaluate the performance of GCMs. The evaluations of 42 CMIP6 GCMs (Meucci et al., 2022) indicate that the EC3G (ranked 2nd) is clearly a high performing GCM in simulating global wind‐related variables in comparison to ERA5 reanalysis. AC2G (ranked 15th) does not perform as highly on this global basis, but as it is an Australian GCM, it was developed to perform well for the Australia region.…”
Section: Methodsmentioning
confidence: 99%
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“…Watterson (2015) has proposed skill scores of four wind‐related variables to evaluate the performance of GCMs. The evaluations of 42 CMIP6 GCMs (Meucci et al., 2022) indicate that the EC3G (ranked 2nd) is clearly a high performing GCM in simulating global wind‐related variables in comparison to ERA5 reanalysis. AC2G (ranked 15th) does not perform as highly on this global basis, but as it is an Australian GCM, it was developed to perform well for the Australia region.…”
Section: Methodsmentioning
confidence: 99%
“…Therefore, as undertaken in this study, it is useful to evaluate the potential impacts of different GCMs on the regional future projected wave climate, by comparing two RWCMs. In this study, the EC3R and AC2R were nested within a global WW3 model forced with the EC3G and AC2G, respectively (Meucci et al., 2022). Watterson (2015) has proposed skill scores of four wind‐related variables to evaluate the performance of GCMs.…”
Section: Methodsmentioning
confidence: 99%
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“…In this study, a 40‐year (1981–2020) global wave hindcast was used to investigate the wave climate trends and the modulation of climate variability (ENSO, AAO, AO, PDO, AMO, and IOD) on ocean waves in the DJF and JJA seasons. The advantage of using a hindcast is that it removes the impact of the ERA5 wave height assimilation on the wave climate trends (Meucci et al., 2023).…”
Section: Discussionmentioning
confidence: 99%