Modification of the Charnock Wind Stress Formula to Include the Effects of Free Convection and Swell

Huang, C. H.

doi:10.5772/27003

Cited by 5 publications

(4 citation statements)

References 41 publications

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“…For rough flow, α is estimated to be 0.011 in open sea conditions and 0.03 in coastal areas [ Sempreviva et al , ; Smith , ; Huang , ]. As most of these studies focused on the sea‐atmosphere interaction, we performed a numerical simulation with the B model in which we used observations to optimize the most appropriate α for the small Nam Co Lake.…”

Section: Resultsmentioning

confidence: 99%

Observation and simulation of lake‐air heat and water transfer processes in a high‐altitude shallow lake on the Tibetan Plateau

Wang

Chen

et al. 2015

JGR Atmospheres

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Lakes are an important part of the landscape on the Tibetan Plateau. Most of the Plateau lakes' area has been expanding in recent years, but lake‐atmosphere energy and water interaction is poorly understood because of a lack of observational data and adequate modeling systems. Based on the eddy covariance observation over a high‐altitude shallow and small lake (the small Nam Co Lake) during an ice‐free period from 10 April to 30 August 2012, this study analyzes the lake‐air heat and water vapor turbulent transfer processes and evaluates two popular lake‐air exchange models: a bulk aerodynamic transfer model (B model) and a multilayer model (M model). Our main results are as follows: (1) observations show that the bulk transfer coefficient (CE) and roughness length (zoq) for water are higher than those for heat (CH and z0h), especially under low wind speed; (2) both models underestimate turbulent fluxes due to inaccurate values of the Charnock coefficient (α) and the roughness Reynolds number (Rr) which are both important parameters for calculating the roughness length for momentum (z0m) over water; (3) α within a reasonable range of 0.013–0.035 for rough flow and Rr for smooth flow (Rr = 0.11) are 0.031 and 0.54, respectively, by our observation. The wave pattern of shorter wavelength gives a larger z0m in the small and shallow lake; and (4) the B model and the M model gave consistent results, and both models are more suitable for simulation of turbulent flux exchange after z0m optimization.

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Section: Resultsmentioning

confidence: 99%

Observation and simulation of lake‐air heat and water transfer processes in a high‐altitude shallow lake on the Tibetan Plateau

Wang

Chen

et al. 2015

JGR Atmospheres

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“…В модели SWAN зависимость 𝐶 𝑑 (𝑉, α 1 , … , α 𝑛 ) задана квадратичной функцией с фиксированными коэффициентами, изменение которой, в отличие от параметров в источниках, описывающих генерацию и диссипацию волновой энергии, не предусмотрено. Но на самом деле коэффициент 𝐶 𝑑 известен почти с той же степенью неопределенности [18][19][20][21][22], что и параметры математических моделей, описывающих диссипацию и генерацию морских волн. Неопределенность значения 𝐶 𝑑 особенно характерна для прибрежных районов, находящихся на удалении до 100-200 км от побережья.…”

Section: особенности предлагаемой процедуры настройки модели Swanunclassified

Updated System for the Sea Wave Operational Forecast of the Black Sea Marine Forecasting Center

Ratner¹,

Фомін²,

Kholod³

et al. 2021

MGZh

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Purpose. The work is aimed at updating the sea wave forecasting system developed in the Black Sea Marine Forecasting Center by including the block of wind wave forecast in the Sevastopol region and by improving the wave forecast accuracy using the proposed procedure for the SWAN model tuning. Methods and Results. In the updated forecasting system, the possibility of performing the joint operational sea wave forecasts for the Black Sea and the Sevastopol region (with the 5 and 1 km spatial resolutions, respectively) became possible due to the nested grid method applied. To improve accuracy of the wave forecasts, the procedure for the SWAN model tuning was proposed. It is based on changing the parameterization of the surface friction coefficient 𝐶𝑑(𝑉), where V is the surface wind speed. This permits to reduce the deviations of the forecasted wave heights from those obtained from the satellite altimetry measurements. Efficiency of the proposed procedure was assessed through comparison of the forecasting results with the remote sensing data. It is shown that in the forecasts supplied with an optimal choice of functional dependence 𝐶𝑑(𝑉), the scattering index between the forecasted and measured values can be reduced by 20 %. Conclusions. Represented is the updated system of the Black Sea Marine Forecasting Center intended for the joint operational sea wave forecasts in the Black Sea and in the Sevastopol region. The results of model validation have shown that the procedure proposed for tuning the SWAN model makes it possible to reduce the deviations of the forecasted wave heights from those measured by the sensors installed at the altimetry satellites.

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“…In SWAN model, the dependence 𝐶𝐶 𝑑𝑑 (𝑉𝑉, α 1 , … , α 𝑛𝑛 ) is given by a quadratic function with fixed coefficients, the change of which, in contrast to the parameters in the sources describing the wave energy generation and dissipation, is not provided. But in fact, the 𝐶𝐶 𝑑𝑑 coefficient is known with almost the same degree of uncertainty [18][19][20][21][22] as the parameters of mathematical models describing the dissipation and generation of sea waves. Uncertainty in the 𝐶𝐶 𝑑𝑑 value is especially typical for coastal regions located at a distance of up to 100-200 km from the coast.…”

Section: Features Of the Proposed Procedures For The Swan Model Tuningmentioning

confidence: 99%

Updated System for the Sea Wave Operational Forecast of the Black Sea Marine Forecasting Center

Ratner¹,

Fomin²,

Kholod³

et al. 2021

PhO

View full text Add to dashboard Cite

Purpose. The work is aimed at updating the sea wave forecasting system developed in the Black Sea Marine Forecasting Center by including the block of wind wave forecast in the Sevastopol region and by improving the wave forecast accuracy using the proposed procedure for the SWAN model tuning. Methods and Results. In the updated forecasting system, the possibility of performing the joint operational sea wave forecasts for the Black Sea and the Sevastopol region (with the 5 and 1 km spatial resolutions, respectively) became possible due to the nested grid method applied. To improve accuracy of the wave forecasts, the procedure for the SWAN model tuning was proposed. It is based on changing the parameterization of the surface friction coefficient Cd(V), where V is the surface wind speed. This permits to reduce the deviations of the forecasted wave heights from those obtained from the satellite altimetry measurements. Efficiency of the proposed procedure was assessed through comparison of the forecasting results with the remote sensing data. It is shown that in the forecasts supplied with an optimal choice of functional dependence Cd(V), the scattering index between the forecasted and measured values can be reduced by 20 %. Conclusions. Represented is the updated system of the Black Sea Marine Forecasting Center intended for the joint operational sea wave forecasts in the Black Sea and in the Sevastopol region. The results of model validation have shown that the procedure proposed for tuning the SWAN model makes it possible to reduce the deviations of the forecasted wave heights from those measured by the sensors installed at the altimetry satellites.

show abstract

Modification of the Charnock Wind Stress Formula to Include the Effects of Free Convection and Swell

Cited by 5 publications

References 41 publications

Observation and simulation of lake‐air heat and water transfer processes in a high‐altitude shallow lake on the Tibetan Plateau

Observation and simulation of lake‐air heat and water transfer processes in a high‐altitude shallow lake on the Tibetan Plateau

Updated System for the Sea Wave Operational Forecast of the Black Sea Marine Forecasting Center

Updated System for the Sea Wave Operational Forecast of the Black Sea Marine Forecasting Center

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