A new parameterization scheme for sea surface aerodynamic roughness

Pan, Yongdong; Sha, Wei E. I.; Zhu, Shouxian; Ge, Sufang

doi:10.1016/j.pnsc.2008.05.006

Cited by 10 publications

(10 citation statements)

References 15 publications

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“…Therefore, although here was used Lp, other metrics such as Hs or the peak wave frequency (fp) worked similarly. Due to this similitude, within the range of older waves, our adaptation of the formulation by Hwang [122] behaved reasonably similarly to our adaptation of the formulation by Pan et al [123] (Figure 3), and thus this formulation also showed a behavior more characteristic of the Charnock-based formulations.…”

Section: Roughness Length Under Rough Air-flowsupporting

confidence: 75%

“…Pan et al [123] went back to the z 0 dependency on the inverse wave age and size, proposing a new three-parameter formulation where the dimensionless roughness length scales with the u * -based inverse wave age, i.e., z 0 /H s u * /c p . We reformulated it into Equation (12a).…”

Section: Roughness Length Under Rough Air-flowmentioning

confidence: 99%

“…Its smooth-flow term was better estimated from a fixed-R r formulation (RMSD ≈ 0.0343 m•s −1 ) than from Wu's [35,62] smooth-flow formulation given in Equation (14) (RMSD ≈ 0.0376 m•s −1 ) ( Figure 5). The z 0' s rough-flow term was best estimated from the Pan et al [123] formulation in Equation (12) or the Gao et al [111] formulation for the coastal ocean in Equation (9a) (RMSD ≈ 0.0343 m•s −1 ), and was worst estimated from the Toba et al [97] formulation in Equations (7) and (8), or Gao et al [111] formulation for the open ocean in Equation (9b) (RMSD ≈ 0.0355 m•s −1 ) ( Figure 5). The rough-flow and smooth-flow terms need to be merged under transient air-flows.…”

Section: Converging Friction Velocitiesmentioning

confidence: 99%

See 2 more Smart Citations

The FuGas 2.5 Updated for the Effects of Surface Turbulence on the Transfer Velocity of Gases at the Atmosphere–Ocean Interface

Vieira

Mateus

Canelas

et al. 2020

JMSE

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Accurately estimating air–water gas exchanges requires considering other factors besides wind speed. These are particularly useful for coastal ocean applications, where the sea-state varies at fine spatial and temporal resolutions. We upgrade FuGas 2.5 with improved formulations of the gas transfer velocity parametrized based on friction velocity, kinetic energy dissipation, roughness length, air-flow conditions, drift current and wave field. We then test the algorithm with field survey data collected in the Baltic Sea during spring–summer of 2014 and 2015. Collapsing turbulence was observed when gravity waves were the roughness elements on the sea-surface, travelling at a speed identical to the wind. In such cases, the turbulence driven transfer velocities (from surface renewal and micro-scale wave breaking) could be reduced from ≈20 cm∙h−1 to ≤ 5 cm∙h−1. However, when peak gravity waves were too flat, they were presumably replaced by capillary-gravity waves as roughness elements. Then, a substantial increase in the turbulence and roughness length was observed, despite the low and moderate winds, leading to transfer velocities up to twice as large as those predicted by empirical u10-based formulations.

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Section: Roughness Length Under Rough Air-flowsupporting

confidence: 75%

Section: Roughness Length Under Rough Air-flowmentioning

confidence: 99%

Section: Converging Friction Velocitiesmentioning

confidence: 99%

See 1 more Smart Citation

The FuGas 2.5 Updated for the Effects of Surface Turbulence on the Transfer Velocity of Gases at the Atmosphere–Ocean Interface

Vieira

Mateus

Canelas

et al. 2020

JMSE

View full text Add to dashboard Cite

show abstract

“…The coefficients proposed by Taylor and Yelland [68] yielded implausibly high z 0 when applied to steep young waves originated by a storm over the central Mediterranean Sea and by strong Mistral blowing off-shore of southern France, corresponding to 2.85% of our observations. These extreme z 0 led to absurdly high u * and k w , and thus we imposed a maximum roughness length of 0.01 m. This value roughly matches the maximum expected from the application of alternative formulations for the estimation of z 0 from the wave field [70][71][72][73][74].…”

Section: Transfer Velocitymentioning

confidence: 53%

The FuGas 2.3 Framework for Atmosphere–Ocean Coupling: Comparing Algorithms for the Estimation of Solubilities and Gas Fluxes

et al. 2018

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Accurate estimates of the atmosphere-ocean fluxes of greenhouse gases and dimethyl sulphide (DMS) have great importance in climate change models. A significant part of these fluxes occur at the coastal ocean which, although much smaller than the open ocean, have more heterogeneous conditions. Hence, Earth System Modelling (ESM) requires representing the oceans at finer resolutions which, in turn, requires better descriptions of the chemical, physical and biological processes. The standard formulations for the solubilities and gas transfer velocities across air-water surfaces are 36 and 24 years old, and new alternatives have emerged. We have developed a framework combining the related geophysical processes and choosing from alternative formulations with different degrees of complexity. The framework was tested with fine resolution data from the European coastal ocean. Although the benchmark and alternative solubility formulations generally agreed well, their minor divergences yielded differences of up to 5.8% for CH 4 dissolved at the ocean surface. The transfer velocities differ strongly (often more than 100%), a consequence of the benchmark empirical wind-based formulation disregarding significant factors that were included in the alternatives. We conclude that ESM requires more comprehensive simulations of atmosphere-ocean interactions, and that further calibration and validation is needed for the formulations to be able to reproduce it. We propose this framework as a basis to update with formulations for processes specific to the air-water boundary, such as the presence of surfactants, rain, the hydration reaction or biological activity.

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“…Boundary conditions are derived from the law of the wall relying on appropriate formulations of sea-surface and apparent bottom-roughness parameters denoted z 0s,ω and z 0b,ω , respectively. Waves effects on sea-surface roughness are computed following the parameterization scheme proposed by Pan et al (2008) ln…”

Section: Coherensmentioning

confidence: 99%

Modelling impact of bottom roughness on sea surface temperature in the Sea of Iroise

Guillou¹,

Chapalain²,

Duvieilbourg

2013

Continental Shelf Research

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International audienceA hydrological model based on the coupling of the three-dimensional hydrodynamic module COHERENS (COupled Hydrodynamical-Ecological model for RegioNal and Shelf seas) with the wave propagation module SWAN (Simulating WAves Nearshore) is used to study the effects of bottom roughness on sea surface temperature (SST) in the nearshore areas of the Sea of Iroise (western end of french Brittany). Predicted time histories of SST are compared with the available field data collected at two offshore stations and along the route of a vessel travelling between the coast and the isle of Ushant. The comparison is extended to SST spatial distribution derived from remote-sensing observations for conditions characterising the development of horizontal thermal fronts in the Sea of Iroise. A numerical sensitivity study is conducted focusing on the impacts of the heterogeneous bottom roughnesses associated with (i) the granulometric distribution of seabed sediments and (ii) the apparent friction induced by the waves in the bottom boundary layer. Whereas moderate differences are obtained, both bottom-roughness distributions are found to influence the predicted SST leading to slight improvements of global predictions. The sensitivity of numerical simulations is exacerbated in areas of high thermal gradients. The effects of the bottom roughness associated with the seabed are thus revealed at the north-eastern and south-eastern edges of external Ushant thermal front. Waves have a major influence in the nearshore areas of the bay of Audierne and the western extend of Crozon peninsula

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A new parameterization scheme for sea surface aerodynamic roughness

Cited by 10 publications

References 15 publications

The FuGas 2.5 Updated for the Effects of Surface Turbulence on the Transfer Velocity of Gases at the Atmosphere–Ocean Interface

The FuGas 2.5 Updated for the Effects of Surface Turbulence on the Transfer Velocity of Gases at the Atmosphere–Ocean Interface

The FuGas 2.3 Framework for Atmosphere–Ocean Coupling: Comparing Algorithms for the Estimation of Solubilities and Gas Fluxes

Modelling impact of bottom roughness on sea surface temperature in the Sea of Iroise

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