Olawale James Ikuyajolu, Luke Van Roekel, Steven R Brus, Erin E Thomas, Yi Deng, James J Benedict
{"title":"表面湍流通量参数化对 MJO 的影响:海洋表面波的作用","authors":"Olawale James Ikuyajolu, Luke Van Roekel, Steven R Brus, Erin E Thomas, Yi Deng, James J Benedict","doi":"10.1175/jcli-d-23-0490.1","DOIUrl":null,"url":null,"abstract":"Abstract This study investigates the sensitivity of the Madden-Julian Oscillation (MJO) to changes to the bulk flux parameterization and the role of ocean surface waves in air-sea coupling using a fully-coupled ocean-atmosphere-wave model. The atmospheric and ocean model components of the Energy Exascale Earth System Model (E3SM) are coupled to a spectral wave model, WAVEWATCH III (WW3). Two experiments with wind speed dependent bulk algorithms, NCAR (Large and Yeager 2004, 2009) & COARE3.0a (Fairall et al. 2003), and one experiment with wave-state dependent flux (COR3.0a-WAV) were conducted. We modify COARE3.0a to include surface roughness calculated within WW3 and also account for the buffering effect of waves on the relative difference between air-side and ocean-side momentum flux. Differences in surface fluxes, primarily caused by discrepancies in drag coefficients, result in significant differences in MJO’s properties. While COARE3.0a has better convection-circulation coupling than NCAR, it exhibits anomalous MJO convection east of the dateline. The wave-state dependent flux (COR3.0-WAV) improves the MJO representation over the default COARE3.0 algorithm. Strong easterlies over the Pacific Ocean in COARE3.0a enhance the latent heat flux (LHFLX). This is responsible for the anomalous MJO propagation after the dateline. In COR3.0a-WAV, waves reduce the anomalous easterlies, leading to a decrease in LHFLX and MJO dissipation after the dateline. These findings highlight the role of surface fluxes in MJO simulation fidelity. Most importantly, we show that the proper treatment of wave-induced effects in bulk flux parameterization improves the simulation of coupled climate variability.","PeriodicalId":15472,"journal":{"name":"Journal of Climate","volume":"22 1","pages":""},"PeriodicalIF":4.8000,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Effects of Surface Turbulence Flux Parameterizations on the MJO: The Role of Ocean Surface Waves\",\"authors\":\"Olawale James Ikuyajolu, Luke Van Roekel, Steven R Brus, Erin E Thomas, Yi Deng, James J Benedict\",\"doi\":\"10.1175/jcli-d-23-0490.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract This study investigates the sensitivity of the Madden-Julian Oscillation (MJO) to changes to the bulk flux parameterization and the role of ocean surface waves in air-sea coupling using a fully-coupled ocean-atmosphere-wave model. The atmospheric and ocean model components of the Energy Exascale Earth System Model (E3SM) are coupled to a spectral wave model, WAVEWATCH III (WW3). Two experiments with wind speed dependent bulk algorithms, NCAR (Large and Yeager 2004, 2009) & COARE3.0a (Fairall et al. 2003), and one experiment with wave-state dependent flux (COR3.0a-WAV) were conducted. We modify COARE3.0a to include surface roughness calculated within WW3 and also account for the buffering effect of waves on the relative difference between air-side and ocean-side momentum flux. Differences in surface fluxes, primarily caused by discrepancies in drag coefficients, result in significant differences in MJO’s properties. While COARE3.0a has better convection-circulation coupling than NCAR, it exhibits anomalous MJO convection east of the dateline. The wave-state dependent flux (COR3.0-WAV) improves the MJO representation over the default COARE3.0 algorithm. Strong easterlies over the Pacific Ocean in COARE3.0a enhance the latent heat flux (LHFLX). This is responsible for the anomalous MJO propagation after the dateline. In COR3.0a-WAV, waves reduce the anomalous easterlies, leading to a decrease in LHFLX and MJO dissipation after the dateline. These findings highlight the role of surface fluxes in MJO simulation fidelity. 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Effects of Surface Turbulence Flux Parameterizations on the MJO: The Role of Ocean Surface Waves
Abstract This study investigates the sensitivity of the Madden-Julian Oscillation (MJO) to changes to the bulk flux parameterization and the role of ocean surface waves in air-sea coupling using a fully-coupled ocean-atmosphere-wave model. The atmospheric and ocean model components of the Energy Exascale Earth System Model (E3SM) are coupled to a spectral wave model, WAVEWATCH III (WW3). Two experiments with wind speed dependent bulk algorithms, NCAR (Large and Yeager 2004, 2009) & COARE3.0a (Fairall et al. 2003), and one experiment with wave-state dependent flux (COR3.0a-WAV) were conducted. We modify COARE3.0a to include surface roughness calculated within WW3 and also account for the buffering effect of waves on the relative difference between air-side and ocean-side momentum flux. Differences in surface fluxes, primarily caused by discrepancies in drag coefficients, result in significant differences in MJO’s properties. While COARE3.0a has better convection-circulation coupling than NCAR, it exhibits anomalous MJO convection east of the dateline. The wave-state dependent flux (COR3.0-WAV) improves the MJO representation over the default COARE3.0 algorithm. Strong easterlies over the Pacific Ocean in COARE3.0a enhance the latent heat flux (LHFLX). This is responsible for the anomalous MJO propagation after the dateline. In COR3.0a-WAV, waves reduce the anomalous easterlies, leading to a decrease in LHFLX and MJO dissipation after the dateline. These findings highlight the role of surface fluxes in MJO simulation fidelity. Most importantly, we show that the proper treatment of wave-induced effects in bulk flux parameterization improves the simulation of coupled climate variability.
期刊介绍:
The Journal of Climate (JCLI) (ISSN: 0894-8755; eISSN: 1520-0442) publishes research that advances basic understanding of the dynamics and physics of the climate system on large spatial scales, including variability of the atmosphere, oceans, land surface, and cryosphere; past, present, and projected future changes in the climate system; and climate simulation and prediction.