IMPROVEMENT OF STORM SURGE SIMULATION UPON PARAMETERIZATIONS OF COUPLED AIR-SEA INTERACTIONS

Coupled atmosphere-ocean model has been developed in various organizations. Warner et al. developed fully coupled model, so-called COAWST, using the atmosphere model WRF, the ocean model ROMS and the wave model SWAN. Though there are several studies with coupled model, there is few research on tropical cyclone event analyzing the changes in ocean current and water temperature in detail. In this study, a series of numerical simulations was carried out targeting Typhoon Melor (2009), and it is analyzed against to the meteorologic and oceanic field data at Tanabe bay, Wakayama Prefecture in Japan. The results show that the wave energy dissipation by the wave model is effective in the change of ocean current and the thermal feedback by the atmospheric model is effective in the change of water temperature due to the typhoon passage.

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A Coupled OpenFOAM-WRF Study on Atmosphere-Wake-Ocean Interaction

Fluids ◽

10.3390/fluids6010012 ◽

2020 ◽

Vol 6 (1) ◽

pp. 12

Author(s):

John Gilbert ◽

Jonathan Pitt

Keyword(s):

Field Data ◽

Wrf Model ◽

Coupled Model ◽

Atmospheric Model ◽

Ocean Model ◽

Sea Surface ◽

Small Scale ◽

Surface Currents ◽

Atmospheric Component ◽

Surface Disturbances

This work aims to better understand how small scale disturbances that are generated at the air-sea interface propagate into the surrounding atmosphere under realistic environmental conditions. To that end, a one-way coupled atmosphere-ocean model is presented, in which predictions of sea surface currents and sea surface temperatures from a microscale ocean model are used as constant boundary conditions in a larger atmospheric model. The coupled model consists of an ocean component implemented while using the open source CFD software OpenFOAM, an atmospheric component solved using the Weather Research and Forecast (WRF) model, and a Python-based utility foamToWRF, which is responsible for mapping field data between the ocean and atmospheric domains. The results are presented for two demonstration cases, which indicate that the proposed coupled model is able to capture the propagation of small scale sea surface disturbances in the atmosphere, although a more thorough study is required in order to properly validate the model.

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Building a coupled data assimilation system for the atmosphere, land-surface and subsurface on the catchment scale

10.5194/egusphere-egu21-7439 ◽

2021 ◽

Author(s):

Bernd Schalge ◽

Barbara Haese ◽

Bastian Waldowski ◽

Natascha Brandhorst ◽

Emilio Sanchez ◽

...

Keyword(s):

Soil Moisture ◽

Data Assimilation ◽

Land Surface ◽

Coupled Model ◽

Cosmic Ray ◽

Atmospheric Model ◽

Surface Model ◽

Catchment Scale ◽

Near Surface ◽

Fully Coupled

We present a data assimilation (DA) system for the atmosphere-land-surface-subsurface system on the catchment scale. The Neckar catchment in SW-Germany served as the specific case where the DA in combination with the coupled atmosphere-land surface-subsurface model TSMP was used. TSMP couples the atmospheric model COSMO, the land-surface model CLM and the hydrological model ParFlow to the DA framework PDAF. We will discuss how the ensemble system is set up in order to work properly and what issues we faced during our initial testing. For the atmosphere we found that it is important to have a good ensemble of lateral forcings as changing internal parameters for various parametrizations does not introduce sufficient variability on its own due to the rather small size of our domain. For the sub-surface the choice of parameters becomes most important and as such parameter estimation will be a valuable tool for improving DA results significantly. Finally, we are showing some first DA results with our system concerning soil moisture with two different assimilation methods with a fully coupled model setup. In the first assimilation scenario in-situ soil moisture data measured by cosmic ray probes are assimilated, while in the second assimilation scenario remotely sensed near surface soil moisture is assimilated. The first results are encouraging and we discuss additional planned simulation scenarios with the fully coupled atmosphere-land surface-subsurface modelling system as well as plans to test strongly coupled DA, where measurements are used to update states across compartments, possibly resulting in additional accuracy gain compared to traditional uncoupled DA.&#160;

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LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project

Advances in Atmospheric Sciences ◽

10.1007/s00376-019-9208-5 ◽

2020 ◽

Vol 37 (3) ◽

pp. 239-249 ◽

Cited By ~ 11

Author(s):

Pengfei Lin ◽

Zhipeng Yu ◽

Hailong Liu ◽

Yongqiang Yu ◽

Yiwen Li ◽

...

Keyword(s):

Coupled Model ◽

Reanalysis Data ◽

Ocean Model ◽

Model Intercomparison ◽

Surface Data ◽

Intercomparison Project ◽

System Bias ◽

The Mean ◽

Fully Coupled

Abstract The datasets of two Ocean Model Intercomparison Project (OMIP) simulation experiments from the LASG/IAP Climate Ocean Model, version 3 (LICOM3), forced by two different sets of atmospheric surface data, are described in this paper. The experiment forced by CORE-II (Co-ordinated Ocean–Ice Reference Experiments, Phase II) data (1948–2009) is called OMIP1, and that forced by JRA55-do (surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis) data (1958–2018) is called OMIP2. First, the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described. Second, the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation. We find that the mean states, interannual variabilities, and long-term linear trends can be reproduced well by the two experiments. The differences between the two datasets are also discussed. Finally, the usage of these data is described. These datasets are helpful toward understanding the origin system bias of the fully coupled model.

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Directional Wind–Wave Coupling in Fully Coupled Atmosphere–Wave–Ocean Models: Results from CBLAST-Hurricane

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-12-0157.1 ◽

2013 ◽

Vol 70 (10) ◽

pp. 3198-3215 ◽

Cited By ~ 87

Author(s):

Shuyi S. Chen ◽

Wei Zhao ◽

Mark A. Donelan ◽

Hendrik L. Tolman

Keyword(s):

Surface Waves ◽

Surface Stress ◽

Prediction Models ◽

Wind Wave ◽

Coupled Model ◽

Ocean Waves ◽

Ocean Model ◽

Wave Coupling ◽

Surface Exchange ◽

Fully Coupled

Abstract The extreme high winds, intense rainfall, large ocean waves, and copious sea spray in hurricanes push the surface-exchange parameters for temperature, water vapor, and momentum into untested regimes. The Coupled Boundary Layer Air–Sea Transfer (CBLAST)-Hurricane program is aimed at developing improved coupling parameterizations (using the observations collected during the CBLAST-Hurricane field program) for the next-generation hurricane research prediction models. Hurricane-induced surface waves that determine the surface stress are highly asymmetric, which can affect storm structure and intensity significantly. Much of the stress is supported by waves in the wavelength range of 0.1–10 m, which is the unresolved “spectral tail” in present wave models. A directional wind–wave coupling method is developed to include effects of directionality of the wind and waves in hurricanes. The surface stress vector is calculated using the two-dimensional wave spectra from a wave model with an added short-wave spectral tail. The wind and waves are coupled in a vector form rather than through the traditional roughness scalar. This new wind–wave coupling parameterization has been implemented in a fully coupled atmosphere–wave–ocean model with 1.67-km grid resolution in the atmospheric model, which can resolve finescale features in the extreme high-wind region of the hurricane eyewall. It has been tested in a number of storms including Hurricane Frances (2004), which is one of the best-observed storms during the CBLAST-Hurricane 2004 field program. This paper describes the new wind–wave coupling parameterization and examines the characteristics of the coupled model simulations of Hurricane Frances (2004). Observations of surface waves and winds are used to evaluate the coupled model results.

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Weakly and strongly coupled data assimilation with the coupled ocean-atmosphere model AWI-CM

10.5194/egusphere-egu2020-5023 ◽

2020 ◽

Author(s):

Qi Tang ◽

Longjiang Mu ◽

Dmitry Sidorenko ◽

Lars Nerger

Keyword(s):

Data Assimilation ◽

Climate Model ◽

Current System ◽

Coupled Model ◽

Atmospheric Model ◽

Ocean Model ◽

Strongly Coupled ◽

Weakly Coupled ◽

Coupled Data Assimilation ◽

Ocean Observations

In this study we compare the results of strongly coupled data assimilation (SCDA) and weakly coupled data assimilation (WCDA), and among the different WCDAs by analyzing the assimilation effect on the prediction of the ocean as well as the atmosphere variables. We have implemented the parallel data assimilation framework (PDAF, http://pdaf.awi.de) with the AWI climate model (AWI-CM), which couples the ocean model FESOM and the atmospheric model ECHAM. In the WCDA, the assimilation acts separately on each component in the coupled model and observations of one component only directly influence its own component. The other components can benefit from the DA through the model dynamics. The alternative to WCDA is SCDA, in which the atmosphere as well as the ocean variables are updated jointly using cross-covariances between the two components. Our current system allows both the SCDA and the WCDA. For the SCDA configuration, either the ocean observations (e.g., satellite sea surface temperature, profiles of temperature and salinity) or the atmosphere observations (e.g., air temperature, surface pressure) or both of them can be assimilated to update the ocean as well as the atmosphere variables. For the WCDA, it allows 1) assimilating only the ocean observations into the ocean state; 2) assimilating only the atmosphere observations into the atmosphere state; 3) assimilating both types of observations into the corresponding component models. The results are evaluated by comparing the estimated ocean and atmosphere variables with the observational data.

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Impact of SST and Surface Waves on Hurricane Florence (2018): A Coupled Modeling Investigation

Weather and Forecasting ◽

10.1175/waf-d-20-0171.1 ◽

2021 ◽

Author(s):

Joseph B. Zambon ◽

Ruoying He ◽

John C. Warner ◽

Christie A. Hegermiller

Keyword(s):

Surface Roughness ◽

Wave Model ◽

Ocean Waves ◽

Atmospheric Model ◽

Surface Fluxes ◽

Heat Fluxes ◽

Coupled Modeling ◽

Storm Characteristics ◽

The Impact ◽

Fully Coupled

AbstractHurricane Florence (2018) devastated the coastal communities of the Carolinas through heavy rainfall that resulted in massive flooding. Florence was characterized by an abrupt reduction in intensity (Saffir-Simpson Category 4 to Category 1) just prior to landfall and synoptic-scale interactions that stalled the storm over the Carolinas for several days. We conducted a series of numerical modeling experiments in coupled and uncoupled configurations to examine the impact of sea surface temperature (SST) and ocean waves on storm characteristics. In addition to experiments using a fully coupled atmosphere-ocean-wave model, we introduced the capability of the atmospheric model to modulate wind stress and surface fluxes by oceanwaves through data from an uncoupled wave model. We examined these experiments by comparing track, intensity, strength, SST, storm structure, wave height, surface roughness, heat fluxes, and precipitation in order to determine the impacts of resolving ocean conditions with varying degrees of coupling. We found differences in the storm’s intensity and strength, with the best correlation coefficient of intensity (r=0.89) and strength (r=0.95) coming from the fully-coupled simulations. Further analysis into surface roughness parameterizations added to the atmospheric model revealed differences in the spatial distribution and magnitude of the largest roughness lengths. Adding ocean andwave features to the model further modified the fluxes due to more realistic cooling beneath the stormwhich in turn modified the precipitation field. Our experiments highlight significant differences in how air-sea processes impact hurricane modeling. The storm characteristics of track, intensity, strength, and precipitation at landfall are crucial to predictability and forecasting of future landfalling hurricanes.

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FIELD CALCULATIONS OF WAVE ENERGY DISSIPATION AND RELATED BEACH PROFILE

Coastal Engineering Proceedings ◽

10.9753/icce.v21.135 ◽

1988 ◽

Vol 1 (21) ◽

pp. 135

Author(s):

James R. Tallent ◽

Takao Yamashita ◽

Yoshito Tsuchiya

Keyword(s):

Energy Dissipation ◽

Wave Energy ◽

Field Data ◽

Surf Zone ◽

Wave Theory ◽

Nonlinearity Parameter ◽

Engineering Project ◽

Wave Energy Dissipation ◽

Dissipation Model ◽

Zone Field

The process by which wave energy dissipates across the surf zone and its affect on the bed profile is, of course, a topic of immediate concern and debate. Various concepts of the wave energy dissipation process have been modeled, however, additional research is needed before confidence can be placed in a particular calculation scheme. In addition to the problems associated with proper model derivation a method of application and result interpretation of actual surf zone field data must be devised and understood. This is, of course, prerequisite to any realistic use of a wave energy dissipation model in an engineering project. The following study was therefore conducted in order to examine the applicability of surf zone field data to wave energy dissipation models and to investigate the bed profile relationship. Two wave energy dissipation models were selected for comparison in this study, the 'Undertow Model'(UM) which is based on the conservation of wave energy flux across the surf zone (3), and the 'Turbulent Bore Model'(TBM) which is based on hydraulic jump theory (2). Individual waves were identified in the wave record by employing the zero up-crossing method, and wave energy calculations were based on small amplitude wave theory, Svendsen's nonlinearity parameter Bo (4), and the 1/3 Significant Wave classification.

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Three-Dimensional Temperature Field Change in the South China Sea during Typhoon Kai-Tak (1213) Based on a Fully Coupled Atmosphere–Wave–Ocean Model

Water ◽

10.3390/w11010140 ◽

2019 ◽

Vol 11 (1) ◽

pp. 140 ◽

Cited By ~ 11

Author(s):

Zhiyuan Wu ◽

Changbo Jiang ◽

Jie Chen ◽

Yuannan Long ◽

Bin Deng ◽

...

Keyword(s):

Temperature Field ◽

Heat Exchange ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Coupled Model ◽

Ocean Model ◽

Sea Surface ◽

Sea Temperature ◽

Simulation Results ◽

Fully Coupled

Studying the sea–air interaction between the upper ocean and typhoons is crucial to improve our understanding of heat and momentum exchange between the atmosphere and the ocean. There is a strong heat flux exchange between the atmosphere and the ocean during the impact of a typhoon, and the physical fields, such as the wind field, wave field, flow field, and SST field, also interact with each other. A fully coupled Atmosphere–Wave–Ocean model in the South China Sea was established by the mesoscale atmospheric model WRF, wave model SWAN, and the regional ocean model ROMS based on the COAWST model system. Typhoon Kai-tak was simulated using this fully coupled model and some other coupled schemes. In this paper, the variation of sea surface temperature (SST) and ocean subsurface temperature caused by Typhoon Kai-tak is analyzed by the fully coupled model, and the basic characteristics of the response of the upper ocean to the typhoon are given. The simulation results demonstrate that the fully coupled WRF-SWAN-ROMS model shows that the typhoon passes through the sea with obvious cooling. In the cold eddy region, the sea surface temperature cools 4 to 5 °C, and the cooling zone is concentrated on the right side of the track. The change of sea surface temperature lags more than 12 h behind the change of sea surface height. The decrease of SST on the left side of the track was relatively small: ranging from 1.5 to 2.5 °C. The disturbance of typhoon causes the subsurface water to surge to the surface, changes the temperature distribution of the surface, and causes the mixing layer to deepen about 40 m to 60 m. The simulation results reveal the temporal and spatial distribution of sea temperature and mixed layer depth. The sea surface temperature field has an asymmetrical distribution in space and has a lag in time. The heat exchange at the air–sea interface is very strong under the influence of the typhoon. The heat exchange between the air and sea is divided into latent heat and sensible heat, and the latent heat generated by water vapor evaporation plays a dominant role in the heat exchange at the air–sea interface, which shows that the heat carried by the vaporization of the sea surface is one of the important factors for the decrease of sea temperature under the influence of the typhoon.

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