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- Author or Editor: Jia Hu x
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Abstract
We used a mesoscale atmospheric model to simulate Typhoon Hagupit (2008) in the South China Sea (SCS). First, we chose optimized parameterization schemes based on a series of sensitivity tests. The results suggested that a combination of the Kain–Fritsch cumulus scheme and the Goddard microphysics scheme was the best choice for reproducing both the track and intensity of Typhoon Hagupit. Next, the simulated rainfall was compared with microwave remote sensing products. This comparison validated the model results for both the magnitude of rainfall and the location of heavy rain relative to the typhoon’s center. Furthermore, the potential vorticity and vertical wind speed displayed the asymmetric horizontal and tilted vertical structures of Typhoon Hagupit. Finally, we compared the simulation of air–sea turbulent fluxes with estimations from an in situ buoy. The time series of momentum fluxes were roughly consistent, while the model still overestimated heat fluxes, especially right before the typhoon’s arrival at the buoy.
Abstract
We used a mesoscale atmospheric model to simulate Typhoon Hagupit (2008) in the South China Sea (SCS). First, we chose optimized parameterization schemes based on a series of sensitivity tests. The results suggested that a combination of the Kain–Fritsch cumulus scheme and the Goddard microphysics scheme was the best choice for reproducing both the track and intensity of Typhoon Hagupit. Next, the simulated rainfall was compared with microwave remote sensing products. This comparison validated the model results for both the magnitude of rainfall and the location of heavy rain relative to the typhoon’s center. Furthermore, the potential vorticity and vertical wind speed displayed the asymmetric horizontal and tilted vertical structures of Typhoon Hagupit. Finally, we compared the simulation of air–sea turbulent fluxes with estimations from an in situ buoy. The time series of momentum fluxes were roughly consistent, while the model still overestimated heat fluxes, especially right before the typhoon’s arrival at the buoy.
Abstract
In Alaska’s coastal environment, accurate information of sea ice conditions is desired by operational forecasters, emergency managers, and responders. Complicated interactions among atmosphere, waves, ocean circulation, and sea ice collectively impact the ice conditions, intensity of storm surges, and flooding, making accurate predictions challenging. A collaborative work to build the Alaska Coastal Ocean Forecast System established an integrated storm surge, wave, and sea ice model system for the coasts of Alaska, where the verified model components are linked using the Earth System Modeling Framework and the National Unified Operational Prediction Capability. We present the verification of the sea ice model component based on the Los Alamos Sea Ice Model, version 6. The regional, high-resolution (3 km) configuration of the model was forced by operational atmospheric and ocean model outputs. Extensive numerical experiments were conducted from December 2018 to August 2020 to verify the model’s capability to represent detailed nearshore and offshore sea ice behavior, including landfast ice, ice thickness, and evolution of air–ice drag coefficient. Comparisons of the hindcast simulations with the observations of ice extent presented the model’s comparable performance with the Global Ocean Forecast System 3.1 (GOFS3.1). The model’s skill in reproducing landfast ice area significantly outperformed GOFS3.1. Comparison of the modeled sea ice freeboard with the Ice, Cloud, and Land Elevation Satellite-2 product showed a mean bias of −4.6 cm. Daily 5-day forecast simulations for October 2020–August 2021 presented the model’s promising performance for future implementation in the coupled model system.
Significance Statement
Accurate sea ice information along Alaska’s coasts is desired by the communities for preparedness of hazardous events, such as storm surges and flooding. However, such information, in particular predicted conditions, remains to be a gap. This study presents the verification of the state-of-art sea ice model for Alaska’s coasts for future use in the more comprehensive coupled model system where ocean circulation, wave, and sea ice models are integrated. The model demonstrates comparable performance with the existing operational ocean–ice coupled model product in reproducing overall sea ice extent and significantly outperformed it in reproducing landfast ice cover. Comparison with the novel satellite product presented the model’s ability to capture sea ice freeboard in the stable ice season.
Abstract
In Alaska’s coastal environment, accurate information of sea ice conditions is desired by operational forecasters, emergency managers, and responders. Complicated interactions among atmosphere, waves, ocean circulation, and sea ice collectively impact the ice conditions, intensity of storm surges, and flooding, making accurate predictions challenging. A collaborative work to build the Alaska Coastal Ocean Forecast System established an integrated storm surge, wave, and sea ice model system for the coasts of Alaska, where the verified model components are linked using the Earth System Modeling Framework and the National Unified Operational Prediction Capability. We present the verification of the sea ice model component based on the Los Alamos Sea Ice Model, version 6. The regional, high-resolution (3 km) configuration of the model was forced by operational atmospheric and ocean model outputs. Extensive numerical experiments were conducted from December 2018 to August 2020 to verify the model’s capability to represent detailed nearshore and offshore sea ice behavior, including landfast ice, ice thickness, and evolution of air–ice drag coefficient. Comparisons of the hindcast simulations with the observations of ice extent presented the model’s comparable performance with the Global Ocean Forecast System 3.1 (GOFS3.1). The model’s skill in reproducing landfast ice area significantly outperformed GOFS3.1. Comparison of the modeled sea ice freeboard with the Ice, Cloud, and Land Elevation Satellite-2 product showed a mean bias of −4.6 cm. Daily 5-day forecast simulations for October 2020–August 2021 presented the model’s promising performance for future implementation in the coupled model system.
Significance Statement
Accurate sea ice information along Alaska’s coasts is desired by the communities for preparedness of hazardous events, such as storm surges and flooding. However, such information, in particular predicted conditions, remains to be a gap. This study presents the verification of the state-of-art sea ice model for Alaska’s coasts for future use in the more comprehensive coupled model system where ocean circulation, wave, and sea ice models are integrated. The model demonstrates comparable performance with the existing operational ocean–ice coupled model product in reproducing overall sea ice extent and significantly outperformed it in reproducing landfast ice cover. Comparison with the novel satellite product presented the model’s ability to capture sea ice freeboard in the stable ice season.
