Impact of a New Wave Mixing Scheme on Ocean Dynamics in Typhoon Conditions: A Case Study of Typhoon In-Fa (2021)
Abstract
:1. Introduction
2. Materials and Methods
2.1. Experimental Programs
2.2. Introduction and Setup of the Coupling Model
2.3. Study Area and Datasets
3. Results
3.1. Wave-Simulation Results
3.2. Simulated Currents
3.3. Simulated SST
3.4. The Simulated Results of Mixed-Layer Temperature
3.5. Effect on Surface Current Field
4. Conclusions
- (1)
- Using HYCOM data as the background field, GFS reanalysis wind fields and ERA5 reanalysis heat flux data as driving fields, the simulated significant wave heights, SST and other variables from the COAWST sea–wave–air coupled model closely match actual measurements. This accuracy suggests that the selection of background fields, initial conditions and physical parameters is appropriate, indicating that the model performs well in simulating sea–wave–air interactions and can serve as a reference for future simulations.
- (2)
- The inclusion of wave-induced mixing effects in the COAWST model reduces SST biases, particularly in areas affected by the typhoon. The spatial distribution of SST differences aligns with the distribution of significant wave heights, showing larger differences near the typhoon and smaller differences in calmer waters. Analysis reveals that wave-induced vertical mixing enhances current velocities during the typhoon, with a more pronounced effect on the right side of the typhoon path. This enhancement increases upper-layer water dispersion and upwelling, resulting in reduced SST. Furthermore, the MLD metrics in EXP3 demonstrate significant improvements, with the percentage error (PE) decreasing from 26.54 in EXP1 to 18.54, the mean absolute error (MAE) from 8.85 to 5.25 and the root mean square error (RMSE) from 11.05 to 6.13, while the correlation coefficient (COR) increased from 0.84 to 0.92, indicating a notable reduction in errors and enhanced predictive accuracy. For MLT, EXP3 achieves a PE reduction to 1.02, with MAE and RMSE values dropping to 0.41 and 0.46, respectively. Incorporating wave-induced mixing effects thus significantly improves the accuracy of upper-layer SST simulations.
- (3)
- The original COAWST model’s MY2.5 scheme (EXP1) tends to overestimate upper-ocean temperatures, while the previously proposed parameterization scheme (EXP2) underestimates turbulent mixing during typhoons. This paper proposes a new parameterization scheme (EXP3) that accounts for turbulence enhancement during typhoons. Compared to EXP1 and EXP2, EXP3 significantly improves simulations of temperature changes in both the sea surface layer and deep sea column, demonstrating more efficient vertical momentum and heat transfer. Due to strong wind stress and wave breaking caused by intense winds, the upper ocean experiences rapid mixing, leading to a sharp increase in turbulent kinetic energy (TKE), which peaks near the typhoon’s eye. Simulation results indicate that wave-induced mixing significantly enhances the generation and vertical transport of TKE. Specifically, the EXP3 scheme shows that with the inclusion of wave-induced mixing effects, TKE distribution becomes more widespread and intense, leading to an increase in mixed layer depth. This underscores the critical role of wave-induced mixing in enhancing vertical mixing and energy transfer, particularly near the typhoon path. Comparisons of the simulation results from EXP1, EXP2 and EXP3 reveal that the increase in TKE contributes to a more uniform energy distribution within the mixed layer, facilitating vertical heat and momentum exchange. As a result, sea surface temperatures decrease, and the temperature within the mixed layer becomes more uniform. Comparisons with Argo and Drifter buoy data show that EXP3 results are closer to observed measurements, highlighting the importance of incorporating wave-induced mixing and turbulence enhancement. The enhanced model offers better simulations of ocean temperature and current velocity changes during typhoons, improving forecasting accuracy and reliability. This method of improving wave–current interaction modeling is effective and recommended for forecasting sea states in the East China Sea and South China Sea, especially under typhoon conditions. In future research, we will explore the impact of multiple wave effects on the ocean during typhoons using the COAWST model, while also considering the extension of the new wave-induced mixing scheme to global climate models. This extension aims to verify its applicability across different ocean areas and assess its potential impact on the global climate system.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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WRF | SWAN | ROMS | |
---|---|---|---|
Domain | DO1: 140 × 116 (30 km) | DO1: 591 × 438 (10 km) | DO1: 590 × 437 (10 km) |
DO2: 591 × 438 (10 km) | |||
50 eta levels | 40 sigma levels | ||
Dynamics | DO1: dt = 48 s, DO2: dt = 16 s | dt = 60 s | dt = 60 s |
Physics | Mp_physcis: WSM 6-class graupel | Whitecapping physics: KOMEN | Momentum equation physics: TS_U3HADVECTION |
Ra_lw_physics: RRTMG | Whitecap crushed Physics: Hasselman | Vertical mixing physics: MY2.5 mixing | |
Ra_sw_physics: RRTMG | Bottom Friction Physics: Collins | Tidal physics: UV_TIDES | |
Sf_sfclay_physics: Monin-Obukhov | |||
Sf_surface_physics: Noah | |||
Bl_pbl_physics: TS_U | |||
Cu_physics:Kain-Fritsch |
Data | Data Sources |
---|---|
Topographic data | ETOPO1 (http://www.ngdc.noaa.gov/mgg/global/, accessed on 3 March 2024) |
Wind data | GFS (https:/nomads.ncep.noaa.gov/, accessed on 3 March 2024) |
Heat flux data | ERA5 (https://www.ecmwf.int/, accessed on 3 March 2024) |
Initial field data | HYCOM (https://www.hycom.org/, accessed on 3 March 2024) |
Validation data | JASON-3 (https://www.aviso.altimetry.fr/en/home.html, accessed on 3 March 2024) |
OISST (https://www.hycom.org/, accessed on 3 March 2024) | |
Argo (http://www.argo.org.cn/, accessed on 3 March 2024) Drifter (https://www.aoml.noaa.gov/global-drifter-program/, accessed on 3 March 2024) |
Track | Satellite Peak (m) | Simulated Peak (m) | PE (m) | MAE (m) | RMSE (m) | COR |
---|---|---|---|---|---|---|
C1 | 5.152 | 4.767 | 0.385 | 0.342 | 0.366 | 0.871 |
C2 | 6.463 | 6.146 | 0.317 | 0.392 | 0.389 | 0.836 |
C3 | 4.177 | 3.918 | 0.259 | 0.296 | 0.314 | 0.943 |
C4 | 6.291 | 6.025 | 0.266 | 0.287 | 0.294 | 0.951 |
EXP1 | EXP2 | EXP3 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
PE (m) | MAE (m) | RMSE (m) | COR | PE (m) | MAE (m) | RMSE (m) | COR | PE (m) | MAE (m) | RMSE (m) | COR | |
MLD (m) | 26.54 | 8.85 | 11.05 | 0.84 | 21.94 | 6.58 | 8.55 | 0.88 | 18.54 | 5.25 | 6.13 | 0.92 |
MLT (°C) | 1.55 | 0.55 | 0.65 | 0.52 | 1.14 | 0.46 | 0.53 | 0.74 | 1.02 | 0.41 | 0.46 | 0.64 |
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Chen, W.; Chen, J.; Shi, J.; Zhang, S.; Zhang, W.; Xia, J.; Wang, H.; Yi, Z.; Wu, Z.; Zhang, Z. Impact of a New Wave Mixing Scheme on Ocean Dynamics in Typhoon Conditions: A Case Study of Typhoon In-Fa (2021). Remote Sens. 2024, 16, 3298. https://doi.org/10.3390/rs16173298
Chen W, Chen J, Shi J, Zhang S, Zhang W, Xia J, Wang H, Yi Z, Wu Z, Zhang Z. Impact of a New Wave Mixing Scheme on Ocean Dynamics in Typhoon Conditions: A Case Study of Typhoon In-Fa (2021). Remote Sensing. 2024; 16(17):3298. https://doi.org/10.3390/rs16173298
Chicago/Turabian StyleChen, Wei, Jie Chen, Jian Shi, Suyun Zhang, Wenjing Zhang, Jingmin Xia, Hanshi Wang, Zhenhui Yi, Zhiyuan Wu, and Zhicheng Zhang. 2024. "Impact of a New Wave Mixing Scheme on Ocean Dynamics in Typhoon Conditions: A Case Study of Typhoon In-Fa (2021)" Remote Sensing 16, no. 17: 3298. https://doi.org/10.3390/rs16173298