Imperial College London

DrAdrianCallaghan

Faculty of EngineeringDepartment of Civil and Environmental Engineering

Senior Lecturer (Royal Society Shooter International Fellow)
 
 
 
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Contact

 

+44 (0)20 7594 6644a.callaghan Website

 
 
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Assistant

 

Miss Rebecca Naessens +44 (0)20 7594 5990

 
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Location

 

Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Publication Type
Year
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26 results found

Callaghan A, 2024, A Model for Air Entrainment Rates in Oceanic Whitecaps, Geophysical Research Letters, ISSN: 0094-8276

Journal article

Callaghan A, Deane G, Stokes D, 2024, A comparison of laboratory and field measurements of whitecap foam evolution from breaking waves, Journal of Geophysical Research: Oceans, Vol: 129, ISSN: 2169-9275

Sufficiently energetic breaking ocean waves produce distinctive visible foam signatures on the water surface called whitecaps. The mixture of surface whitecap foam cells, and sub-surface bubbles, results in the broad-band scattering of light that allow whitecaps to be measured with optical cameras. In this paper the temporal evolution of whitecap foam area from laboratory and oceanic breaking waves is compared. When appropriately scaled, the foam area time series for both laboratory and oceanic breaking waves follow similar trends, despite occurring in vastly different settings. Distinct similarities of the signature of foam stabilization due to the presence of surfactants in the controlled laboratory experiments are also found in the field suggesting foam stabilization may be a means to remotely sense the presence/absence or concentration of surfactants in the ocean. In addition, probability density distributions of key whitecap variables such as foam area growth and decay timescales and maximum foam area are compared between laboratory and oceanic whitecaps. The oceanic whitecaps are much larger in scale than the laboratory breaking waves, whereas the whitecap growth and decay timescales are similar in magnitude, the latter suggesting that the depths to which bubbles are injected during active air entrainment in the field are relatively shallow. The aggregated whitecap statistics are used to estimate the energy dissipation of individual whitecaps in a novel manner.

Journal article

Padilla E, Cao R, Callaghan AH, 2023, Spatial Interpolation of wave fields based on limited spatial measurements, IEEE Journal of Oceanic Engineering, Vol: 48, Pages: 1226-1235, ISSN: 0364-9059

In experimental campaigns investigating space-time varying signals, e.g., evolving wave fields, it is common for the spatial resolution not to be as high as desirable to properly capture the spatial variability of propagating water waves. This is often due to unavoidable experimental, technical and cost constraints. To overcome this limitation, we present a relatively simple procedure (called S-interp) to interpolate wave fields at spatial locations where no measurements are available. S-interp consists in the interpolation of wave fields along points being at the same phase. The main hypothesis of S-interp is that the wave field follows a linear-like evolution along points being at the same phase. Therefore, along these points, differences between the interpolatedand the actual wave fields are minimal. We use S-interp to successfully reconstruct missing areas of experimental non-breaking wave conditions. These wave conditions are focused wave events recorded by video cameras, whose wave fields are measured by surface detection analysis of the video images. Overall, the hypothesis of S-interp is seen to be valid even at the focal wave crest, where the performance of S-interp is assessed in terms of the normalized error. The main source of error for S-interp isseen to be the spacing between the probes, whereas the nonlinear effects of the wave fields seem secondary. The recommended spacing between probes when using S-interp is at most 10% of the characteristic wavelength to guarantee an upper limit of the error below 5%. The potential application of S-interp to random sea-states is discussed.

Journal article

Cao R, Padilla EM, Callaghan AH, 2023, The influence of bandwidth on the energetics ofintermediate to deep water laboratory breaking waves, Journal of Fluid Mechanics, Vol: 971, ISSN: 0022-1120

An experimental investigation of two-dimensional dispersively focused laboratory breaking waves is presented. We describe the bandwidth effect on breaking wave energetics, including spectral energy evolution, characteristic group velocity, energy dissipation and its rate, and breaking strength parameter, b . To evaluate the role of bandwidth, three definitions of wave group steepness are adopted where Ss and Sn are bandwidth-dependent and Sp remains constant when bandwidth is changed. Our data show two regimes of spectral energy evolution in breaking wave groups, with both regimes bandwidth-dependent: energy dissipation and gain occur at f>0.95fp ( fp is the peak frequency) and f<0.95fp , respectively. The characteristic group velocity, which is used in energy dissipation calculations, increases by up to 7 % after wave breaking, being larger for higher bandwidth breaking waves. An unambiguous bandwidth dependence is found between Sp and both the fractional and absolute wave energy dissipation. Wave groups of larger bandwidth break at a lower value of Sp and consequently lose relatively more energy. The energy dissipation rate depends on the breaking duration which itself is bandwidth dependent. Consequently, no clear bandwidth effect is observed in energy dissipation rate when compared with either Sp or Ss . However, there is a systematic bandwidth dependence in the variation of b when parameterised in terms of Sp , with their relationship becoming increasingly nonlinear as bandwidth increases. When parameterised with Ss , b shows a markedly reduced bandwidth dependence. Finally, the numerical breaking onset and relationship between b and Ss in the numerical study of Derakhti & Kirby (J. Fluid Mech., vol. 790, 2016, pp. 553–581) is validated experimentally.

Journal article

Goddijn-Murphy L, Woolf DK, Pereira R, Marandino CA, Callaghan AH, Piskozub Jet al., 2023, The links between marine plastic litter and the air-sea flux of greenhouse gases, Frontiers in Marine Science, Vol: 10, Pages: 1-7, ISSN: 2296-7745

Climate change and plastic pollution are two of the most pressing environmental challenges caused by human activity, and they are directly and indirectly linked. We focus on the relationship between marine plastic litter and the air-sea flux of greenhouse gases (GHGs). Marine plastic litter has the potential to both enhance and reduce oceanic GHG fluxes, but this depends on many factors that are not well understood. Different kinds of plastic behave quite differently in the sea, affecting air-sea gas exchange in different, largely unknown, ways. The mechanisms of air-sea exchange of GHGs have been extensively studied and if air-sea gas transfer coefficients and concentrations of the gas in water and air are known, calculating the resulting GHG fluxes is reasonably straightforward. However, relatively little is known about the consequences of marine plastic litter for gas transfer coefficients, concentrations, and fluxes. Here we evaluate the most important aspects controlling the exchange of GHGs between the sea and the atmosphere and how marine plastic litter could change these. The aim is to move towards improving air-sea GHG flux calculations in the presence of plastic litter and we have largely limited ourselves to identifying processes, rather than estimating relative importance.

Journal article

Callaghan AH, 2020, Estimates of Wave Breaking Energy Dissipation Rate from Measurements of Whitecap Coverage, Recent Advances in the Study of Oceanic Whitecaps, Editors: Vlahos, Publisher: Springer Nature Switzerland, ISBN: 978-3-030-36370-3

The easiest way to identify the occurrence, or recent occurrence of oceanic air-entraining breaking waves (whitecaps) from above the water surface is through photographic remote sensing of the sea surface. In this paper I estimate the energy dissipation rate due to breaking wave whitecaps using measurements of whitecap coverage of the sea surface. Several datasets are used that employed different methodologies for determining the whitecap coverage spanning almost 4 decades of research. The results show that, on average, the ratio of the energy dissipation rate due to whitecaps to the wind energy input rate to the upper ocean and wave field is close to unity above wind speeds of about 10m s-1. Below 10 m s-1, this energy flux ratio decreases steadily from unity as wind speed decreases, in agreement with several recent studies. The implication is that other dissipative processes play an important role in dissipating the wind energy input to the upper ocean and wave field at low wind speeds. These results suggest that variability in this energy flux ratio may be responsible for differences in measurements and parameterisations of whitecap coverage at low wind speeds.

Book chapter

Callaghan A, 2018, On the relationship between the energy dissipation rate of surface-breaking waves and oceanic whitecap coverage, Journal of Physical Oceanography, Vol: 48, Pages: 2609-2626, ISSN: 0022-3670

Wave breaking is the most important mechanism that leads to the dissipation of oceanic surface wave energy. A relationship between the energy dissipation rate associated with breaking wave whitecaps (Swcap) and the area of whitecap foam per unit area ocean surface (W) is expected, but there is a lack of consensus on what form this relationship should take. Here, mathematical representations of whitecap coverage (W), and growth phase whitecap coverage (Wgrowth) are derived, and an energy-balance approach is used to formulate W and Wgrowth in terms of Swcap. Both W and Wgrowth are found to be linearly proportional to Swcap, but also inversely proportional to the bubble plume penetration depth during active breaking. Since this depth can vary for breaking waves of different scales and slopes, there is likely no unique relationship between Swcap and either W or Wgrowth as bubble plume penetration depth must also be specified. Whitecap observations from the North Atlantic are used to estimate bubble plume penetration depth as a function of wind speed, and then used with W measurements to compute Swcap. An estimate of the relative magnitude of Swcap to the rate of energy input from the wind to the waves, Sin, is made. Above wind speeds of about 12 m/s, Sin is largely balanced by Swcap. At lower wind speeds the ratio Swcap/Sin quickly drops below unity with decreasing wind speed. It is proposed that sea state driven variability in both Swcap/Sin and bubble plume penetration depth are significant causes of variation in whitecap coverage datasets and parameterizations.

Journal article

Callaghan AH, Deane GB, Stokes MD, 2017, On the imprint of surfactant-driven stabilization of laboratory breaking wave foam with comparison to oceanic whitecaps, Journal of Geophysical Research: Oceans, Vol: 122, Pages: 6110-6128, ISSN: 2169-9275

Surfactants are ubiquitous in the global oceans: they help form the materially‐distinct sea surface microlayer (SML) across which global ocean‐atmosphere exchanges take place, and they reside on the surfaces of bubbles and whitecap foam cells prolonging their lifetime thus altering ocean albedo. Despite their importance, the occurrence, spatial distribution, and composition of surfactants within the upper ocean and the SML remains under‐characterized during conditions of vigorous wave breaking when in‐situ sampling methods are difficult to implement. Additionally, no quantitative framework exists to evaluate the importance of surfactant activity on ocean whitecap foam coverage estimates. Here we use individual laboratory breaking waves generated in filtered seawater and seawater with added soluble surfactant to identify the imprint of surfactant activity in whitecap foam evolution. The data show a distinct surfactant imprint in the decay phase of foam evolution. The area‐time‐integral of foam evolution is used to develop a time‐varying stabilization function, urn:x-wiley:21699275:media:jgrc22369:jgrc22369-math-0001 and a stabilization factor, urn:x-wiley:21699275:media:jgrc22369:jgrc22369-math-0002, which can be used to identify and quantify the extent of this surfactant imprint for individual breaking waves. The approach is then applied to wind‐driven oceanic whitecaps, and the laboratory and ocean urn:x-wiley:21699275:media:jgrc22369:jgrc22369-math-0003 distributions overlap. It is proposed that whitecap foam evolution may be used to determine the occurrence and extent of oceanic surfactant activity to complement traditional in‐situ techniques and extend measurement capabilities to more severe sea states occurring at wind speeds in excess of about 10 m/s. The analysis procedure also provides a framework to assess surfactant‐driven variability within and between whitecap coverage data sets.

Journal article

Bell TG, Landwehr S, Miller SD, de Bruyn WJ, Callaghan AH, Scanlon B, Ward B, Yang M, Saltzman ESet al., 2017, Estimation of bubble-mediated air–sea gas exchange from concurrent DMS and CO2 transfer velocities at intermediate–high wind speeds, Atmospheric Chemistry and Physics, Vol: 17, Pages: 9019-9033, ISSN: 1680-7316

Simultaneous air–sea fluxes and concentration differences of dimethylsulfide (DMS) and carbon dioxide (CO2) were measured during a summertime North Atlantic cruise in 2011. This data set reveals significant differences between the gas transfer velocities of these two gases (Δkw) over a range of wind speeds up to 21ms−1. These differences occur at and above the approximate wind speed threshold when waves begin breaking. Whitecap fraction (a proxy for bubbles) was also measured and has a positive relationship with Δkw, consistent with enhanced bubble-mediated transfer of the less soluble CO2 relative to that of the more soluble DMS. However, the correlation of Δkw with whitecap fraction is no stronger than with wind speed. Models used to estimate bubble-mediated transfer from in situ whitecap fraction underpredict the observations, particularly at intermediate wind speeds. Examining the differences between gas transfer velocities of gases with different solubilities is a useful way to detect the impact of bubble-mediated exchange. More simultaneous gas transfer measurements of different solubility gases across a wide range of oceanic conditions are needed to understand the factors controlling the magnitude and scaling of bubble-mediated gas exchange.

Journal article

Callaghan AH, Deane GB, Stokes MD, 2016, Laboratory air-entraining breaking waves: imaging visible foam signatures to estimate energy dissipation, Geophysical Research Letters, Vol: 43, Pages: 11320-11328, ISSN: 0094-8276

Oceanic air‐entraining breaking waves fundamentally influence weather and climate through bubble‐mediated ocean‐atmosphere exchanges, and influence marine engineering design by impacting statistics of wave heights, crest heights, and wave loading. However, estimating individual breaking wave energy dissipation in the field remains a fundamental problem. Using laboratory experiments, we introduce a new method to estimate energy dissipation by individual breaking waves using above‐water images of evolving foam. The data show the volume of the breaking wave two‐phase flow integrated in time during active breaking scales linearly with wave energy dissipated. To determine the volume time‐integral, above‐water images of surface foam provide the breaking wave timescale and horizontal extent of the submerged bubble plume, and the foam decay time provides an estimate of the bubble plume penetration depth. We anticipate that this novel remote sensing method will improve predictions of air‐sea exchanges, validate models of wave energy dissipation, and inform ocean engineering design.

Journal article

Deane GB, Stokes MD, Callaghan AH, 2016, The saturation of fluid turbulence in breaking laboratory waves and implications for whitecaps, Journal of Physical Oceanography, Vol: 46, Pages: 975-992, ISSN: 0022-3670

Measurements of energy dissipated in breaking laboratory waves, averaged over time and space and directly visualized with a bioluminescent technique, are presented. These data show that the energy dissipated in the crest of the breaking waves is constrained: average turbulence intensity within the crest saturates at around 0.5–1.2 W kg<jats:sup>−1</jats:sup>, whereas breaking crest volume scales with wave energy lost. These results are consistent with laboratory and field observations of the Hinze scale, which is the radius of the largest bubble entrained within a breaking crest that is stabilized against turbulent fragmentation. The Hinze scale depends on turbulence intensity but lies in the restricted range 0.7–1.7 mm over more than two orders of magnitude variation in underlying unbroken wave energy. The results have important implications for understanding the energetics of breaking waves in the field, the injection of turbulence into the upper ocean, and air–sea exchange processes in wind-driven seas.

Journal article

Scanlon B, Breivik Ø, Bidlot J-R, Janssen PAEM, Callaghan AH, Ward Bet al., 2016, Modeling Whitecap Fraction with a Wave Model, Journal of Physical Oceanography, Vol: 46, Pages: 887-894, ISSN: 0022-3670

<jats:title>Abstract</jats:title><jats:p>High-resolution measurements of actively breaking whitecap fraction (<jats:italic>W</jats:italic><jats:sub><jats:italic>FA</jats:italic></jats:sub>) and total whitecap fraction (<jats:italic>W</jats:italic><jats:sub><jats:italic>FT</jats:italic></jats:sub>) from the Knorr11 field experiment in the Atlantic Ocean are compared with estimates of whitecap fraction modeled from the dissipation source term of the ECMWF wave model. The results reveal a strong linear relationship between model results and observed measurements. This indicates that the wave model dissipation is an accurate estimate of total whitecap fraction. The study also reveals that the dissipation source term is more closely related to <jats:italic>W</jats:italic><jats:sub><jats:italic>FA</jats:italic></jats:sub> than <jats:italic>W</jats:italic><jats:sub><jats:italic>FT</jats:italic></jats:sub>, which includes the additional contribution from maturing (stage B) whitecaps.</jats:p>

Journal article

Goddijn-Murphy L, Woolf DK, Callaghan AH, Nightingale PD, Shutler JDet al., 2016, A reconciliation of empirical and mechanistic models of the air-sea gas transfer velocity, Journal of Geophysical Research: Oceans, Vol: 121, Pages: 818-835, ISSN: 2169-9275

Journal article

Wain DJ, Lilly JM, Callaghan AH, Yashayaev I, Ward Bet al., 2015, A breaking internal wave in the surface ocean boundary layer, Journal of Geophysical Research: Oceans, Vol: 120, Pages: 4151-4161, ISSN: 2169-9275

<jats:title>Abstract</jats:title><jats:p>High‐temporal resolution measurements in the Labrador Sea surface layer are presented using an upwardly profiling autonomous microstructure instrument, which captures an internal wave in the act of breaking at the base of the surface mixed layer, driving turbulence levels 2–3 orders of magnitude above the background. While lower‐frequency (near‐inertial) internal waves are known to be important sources of turbulence, we report here a higher‐frequency internal wave breaking near the ocean surface. Due to observational limitations, the exact nature of the instability cannot be conclusively identified, but the interaction of wave‐induced velocity with unresolved background shear appears to be the most likely candidate. These observations add a new process to the list of those currently being considered as potentially important for near‐surface mixing. The geographical distribution and global significance of such features are unknown, and underscore the need for more extensive small‐scale, rapid observations of the ocean surface layer.</jats:p>

Journal article

Walesby K, Vialard J, Minnett PJ, Callaghan AH, Ward Bet al., 2015, Observations indicative of rain‐induced double diffusion in the ocean surface boundary layer, Geophysical Research Letters, Vol: 42, Pages: 3963-3972, ISSN: 0094-8276

<jats:title>Abstract</jats:title><jats:p>Double diffusion can result in the formation of thermohaline staircases, typically observed in the ocean interior. The observations presented here were acquired in the ocean surface boundary layer with the autonomous microstructure Air‐Sea Interaction Profiler. An intense rain event (rainfall rates of up to 35 mm/h) resulted in cooler, fresher water (up to 0.15 practical salinity unit (psu) over the upper 7–10 m) overlaying warmer, saltier water, a situation potentially conducive to double‐diffusive mixing. Although not as crisp as interfaces in the interior ocean because of elevated background mixing, a total of 303 thermohaline interfaces were detected within and at the base of the fresh layer, with mean changes in temperature (<jats:italic>T</jats:italic>) and salinity (<jats:italic>S</jats:italic>) across interfaces of 20 × 10<jats:sup>−3∘</jats:sup>C and 22 × 10<jats:sup>−3</jats:sup> psu, respectively. These results call for new studies to disambiguate whether such interfaces are formed through double‐diffusive mixing or shear instabilities and understand any long‐term impacts on near‐surface stratification.</jats:p>

Journal article

Callaghan AH, Ward B, Vialard J, 2014, Influence of surface forcing on near-surface and mixing layer turbulence in the tropical Indian Ocean, Deep Sea Research Part I: Oceanographic Research Papers, Vol: 94, Pages: 107-123, ISSN: 0967-0637

Journal article

Callaghan AH, Stokes MD, Deane GB, 2014, The effect of water temperature on air entrainment, bubble plumes, and surface foam in a laboratory breaking-wave analog, Journal of Geophysical Research: Oceans, Vol: 119, Pages: 7463-7482, ISSN: 2169-9275

Journal article

Ward B, Fristedt T, Callaghan AH, Sutherland G, Sanchez X, Vialard J, Doeschate ATet al., 2014, The Air–Sea Interaction Profiler (ASIP): An Autonomous Upwardly Rising Profiler for Microstructure Measurements in the Upper Ocean, Journal of Atmospheric and Oceanic Technology, Vol: 31, Pages: 2246-2267, ISSN: 0739-0572

<jats:title>Abstract</jats:title> <jats:p>The upper few meters of the ocean form a critical layer for air–sea interaction, but because of observational challenges this region is undersampled. However, the physical processes controlling momentum transfer, gas exchange, and heat transfer are all concentrated in the uppermost region of the ocean. To study this region, the Air–Sea Interaction Profiler (ASIP) was developed. This is an autonomous microstructure vertical profiling instrument that provides data from a maximum depth of 100 m to the ocean surface and allows measurements to be performed in an undisturbed environment. The core sensor package on ASIP includes shear probes, microstructure and CTD-quality temperature and conductivity sensors, a photosynthetically active radiation (PAR) sensor, and an oxygen optode providing a repeated high-resolution dataset immediately below the air–sea interface. Autonomous profiling is accomplished with thrusters that submerge the positively buoyant instrument. Once the desired depth is reached, ASIP ascends through the water column acquiring data. At the surface, ASIP acquires its position and transmits this over the Iridium satellite network. ASIP is then placed in a low-power mode for a specified period, whereupon it repeats the profile cycle. Two-way communication over the Iridium network allows mission parameters to be changed in real time. ASIP has been used to study several scientific questions, such as the impact of diurnal warming on atmospheric processes, turbulence scaling in the upper ocean, parameterizing air–sea gas exchange, salinity gradients in the ocean surface boundary layer (OSBL), and consequences for remote sensing.</jats:p>

Journal article

Meskhidze N, Petters MD, Tsigaridis K, Bates T, O'Dowd C, Reid J, Lewis ER, Gantt B, Anguelova MD, Bhave PV, Bird J, Callaghan AH, Ceburnis D, Chang R, Clarke A, de Leeuw G, Deane G, DeMott PJ, Elliot S, Facchini MC, Fairall CW, Hawkins L, Hu Y, Hudson JG, Johnson MS, Kaku KC, Keene WC, Kieber DJ, Long MS, Mårtensson M, Modini RL, Osburn CL, Prather KA, Pszenny A, Rinaldi M, Russell LM, Salter M, Sayer AM, Smirnov A, Suda SR, Toth TD, Worsnop DR, Wozniak A, Zorn SRet al., 2013, Production mechanisms, number concentration, size distribution, chemical composition, and optical properties of sea spray aerosols, Atmospheric Science Letters, Vol: 14, Pages: 207-213, ISSN: 1530-261X

Journal article

Callaghan AH, 2013, An improved whitecap timescale for sea spray aerosol production flux modeling using the discrete whitecap method, Journal of Geophysical Research: Atmospheres, Vol: 118, Pages: 9997-9997, ISSN: 2169-897X

<jats:title>Abstract</jats:title><jats:p>The discrete whitecap method (DWM) to model the sea spray aerosol (SSA) production flux explicitly requires a whitecap timescale, which up to now has only considered a whitecap decay timescale, <jats:italic>τ</jats:italic><jats:sub>decay</jats:sub>. A reevaluation of the DWM suggests that the whitecap timescale should account for the total whitecap lifetime (<jats:italic>τ</jats:italic><jats:sub>wcap</jats:sub>), which consists of both the formation timescale (<jats:italic>τ</jats:italic><jats:sub>form</jats:sub>) and the decay timescale (timescale definitions are given in the text). Here values of <jats:italic>τ</jats:italic><jats:sub>form</jats:sub> for 552 oceanic whitecaps measured at the Martha's Vineyard Coastal Observatory on the east coast of the USA are presented, and added to the corresponding values of <jats:italic>τ</jats:italic><jats:sub>decay</jats:sub> to form 552 whitecap timescales. For the majority of whitecaps, <jats:italic>τ</jats:italic><jats:sub>form</jats:sub> makes up about 20–25% of <jats:italic>τ</jats:italic><jats:sub>wcap</jats:sub>, but this can be as large as 70% depending on the value of <jats:italic>τ</jats:italic><jats:sub>decay</jats:sub>. Furthermore, an area‐weighted mean whitecap timescale for use in the DWM (<jats:italic>τ</jats:italic><jats:sub>DWM</jats:sub>) is defined that encompasses the variable nature of individual whitecap lifetimes within a given time period, and is calculated to be 5.3 s for this entire data set. This value is combined with previously published whitecap coverage parameterizations and estimates of SSA particle production per whitecap area to form a size‐resolved SSA production flux par

Journal article

Callaghan AH, Deane GB, Stokes MD, 2013, Two Regimes of Laboratory Whitecap Foam Decay: Bubble-Plume Controlled and Surfactant Stabilized, Journal of Physical Oceanography, Vol: 43, Pages: 1114-1126, ISSN: 0022-3670

<jats:title>Abstract</jats:title><jats:p>A laboratory experiment to quantify whitecap foam decay time in the presence or absence of surface active material is presented. The investigation was carried out in the glass seawater channel at the Hydraulics Facility of Scripps Institution of Oceanography. Whitecaps were generated with focused, breaking wave packets in filtered seawater pumped from La Jolla Shores Beach with and without the addition of the surfactant Triton X-100. Concentrations of Triton X-100 (204 μg L−1) were chosen to correspond to ocean conditions of medium productivity. Whitecap foam and subsurface bubble-plume decay times were determined from digital images for a range of wave scales and wave slopes. The experiment showed that foam lifetime is variable and controlled by subsurface bubble-plume-degassing times, which are a function of wave scale and breaking wave slope. This is true whether or not surfactants are present. However, in the presence of surfactants, whitecap foam is stabilized and persists for roughly a factor of 3 times its clean seawater value. The range of foam decay times observed in the laboratory study lie within the range of values observed in an oceanic dataset obtained off Martha’s Vineyard in 2008.</jats:p>

Journal article

Callaghan AH, Deane GB, Stokes MD, Ward Bet al., 2012, Observed variation in the decay time of oceanic whitecap foam, Journal of Geophysical Research: Oceans, Vol: 117, ISSN: 0148-0227

<jats:p>Whitecap foam decay times for 552 individual breaking waves determined from digital images of the sea surface are reported. The images had sub‐centimeter pixel resolution and were acquired at frame rates between 3 and 6 frames per second at the Martha's Vineyard Coastal Observatory over a 10‐day period in 2008, subdivided into 4 observation periods. Whitecap foam decay times for individual events varied between 0.2 s to 10.4 s across the entire data set. A systematic positive correlation between whitecap foam decay time and maximum whitecap foam patch area was found for each observation period. For a given whitecap size within each observation period, the decay times varied between a factor of 2 and 5, with the largest variation occurring during unsteady environmental forcing conditions. Within observation periods, bin‐averaged decay times varied by up to a factor of 4 across the range of foam patch areas. Between observation periods, the effective whitecap foam decay time, which we define as the area‐weighted mean decay time, varied by a factor of 3.4 between 1.4 s and 4.8 s. We found a weak correlation between decay times and individual event‐averaged breaking wave speeds. The variation in the active breaking area across all 4 observation periods was small, indicating relatively uniform surface whitecap area generating potential. We speculate that the variation in the foam decay times may be due to (i) the effect of surfactants on bubble and foam stability, and (ii) differences between bubble plume characteristics caused by a variation in breaking wave type.</jats:p>

Journal article

Goddijn-Murphy L, Woolf DK, Callaghan AH, 2011, Parameterizations and Algorithms for Oceanic Whitecap Coverage, Journal of Physical Oceanography, Vol: 41, Pages: 742-756, ISSN: 0022-3670

<jats:title>Abstract</jats:title> <jats:p>Shipboard measurements of fractional whitecap coverage W and wind speed at 10-m height, obtained during the 2006 Marine Aerosol Production (MAP) campaign, have been combined with ECMWF wave model and Quick Scatterometer (QuikSCAT) satellite wind speed data for assessment of existing W parameterizations. The wind history trend found in an earlier study of the MAP data could be associated with wave development on whitecapping, as previously postulated. Whitecapping was shown to be mainly wind driven; for high wind speeds (&amp;gt;9 m s−1), a minor reduction in the scatter of in situ W data points could be achieved by including sea state conditions or by using parameters related to wave breaking. The W values were slightly larger for decreasing wind/developed waves than for increasing wind/developing waves, whereas cross-swell conditions (deflection angle between wind and swell waves between ±45° and ±135°) appeared to dampen whitecapping. Tabulated curve fitting results of the different parameterizations show that the errors that could not be attributed to the propagation of the standard error in U10 remained largely unexplained. It is possible that the counteracting effects of wave development and cross swell undermine the performance of the simple parameterizations in this study.</jats:p>

Journal article

Callaghan AH, White M, 2009, Automated Processing of Sea Surface Images for the Determination of Whitecap Coverage, Journal of Atmospheric and Oceanic Technology, Vol: 26, Pages: 383-394, ISSN: 0739-0572

<jats:title>Abstract</jats:title> <jats:p>Sea surface images have been collected to determine the percentage whitecap coverage (W) since the late 1960s. Image processing methods have changed dramatically since the beginning of whitecap studies. An automated whitecap extraction (AWE) technique has been developed at the National University of Ireland, Galway, that allows images to be analyzed for percentage whitecap coverage without the need of a human analyst. AWE analyzes digital images and determines a suitable threshold with which whitecaps can be separated from unbroken background water. By determining a threshold for each individual image, AWE is suitable for images obtained in conditions of changing ambient illumination. AWE is also suitable to process images that have been taken from both stable and nonstable platforms (such as towers and research vessels, respectively). Using techniques based on derivative analysis, AWE provides an objective method to determine an appropriate threshold for the identification of whitecaps in sea surface images without the need for a human analyst. The automated method allows large numbers of images to be analyzed in a relatively short amount of time. AWE can be used to analyze hundreds of images per individual W data point, which produces more convergent values of W.</jats:p>

Journal article

Callaghan A, de Leeuw G, Cohen L, O'Dowd CDet al., 2008, Relationship of oceanic whitecap coverage to wind speed and wind history, Geophysical Research Letters, Vol: 35, ISSN: 0094-8276

<jats:p>Sea surface images obtained during the 2006 Marine Aerosol Production (MAP) campaign in the North East Atlantic were analysed for values of percentage whitecap coverage (<jats:italic>W</jats:italic>). Values of <jats:italic>W</jats:italic> are presented for wind speeds up to <jats:italic>circa</jats:italic> 23 m s<jats:sup>−1</jats:sup>. The <jats:italic>W</jats:italic> data were divided into two overlapping groups and a piecewise, wind‐speed‐only parameterization of <jats:italic>W</jats:italic> is proposed that is valid for wind speeds between 3.70 m s<jats:sup>−1</jats:sup> and 23.09 m s<jats:sup>−1</jats:sup>. Segregation of data points based upon a 2.5 hour wind history acted to decrease data scatter at wind speeds above approximately 9.25 m s<jats:sup>−1</jats:sup>. At these wind speeds <jats:italic>W</jats:italic> values were greater for decreasing wind speeds than for increasing wind speeds. No clear wind history effect was observed at wind speeds below 9.25 m s<jats:sup>−1</jats:sup>.</jats:p>

Journal article

Callaghan AH, Deane GB, Stokes MD, 2008, Observed physical and environmental causes of scatter in whitecap coverage values in a fetch‐limited coastal zone, Journal of Geophysical Research: Oceans, Vol: 113, ISSN: 0148-0227

<jats:p>Meteorological and oceanographic data along with sea surface images were recorded at a fetch‐limited coastal site to investigate the effect of physical and environmental conditions on whitecap coverage <jats:italic>W</jats:italic>. An automated image‐processing technique allowed over 100,000 images to be analyzed for <jats:italic>W</jats:italic>. Data analysis showed that many processes influenced <jats:italic>W</jats:italic>. The presence of tidal currents appeared to have augmented values of <jats:italic>W</jats:italic> under certain specific conditions. Analysis of wave spectra indicated the ubiquitous presence of swell propagating northward. Scatter in <jats:italic>W</jats:italic> was markedly absent in mixed seas when the spectral intensity of the wind waves was of the same order of magnitude as the spectral intensity of the swell waves. Swell‐dominated seas introduced much more scatter in <jats:italic>W</jats:italic>. <jats:italic>W</jats:italic> was approximately one third lower in swell‐dominated seas than in mixed seas. Specifically, steep swell waves (steepness values greater than 0.01) that propagated opposite to wind wave direction appeared to have reduced <jats:italic>W</jats:italic> at wind speeds below approximately 7.5 m s<jats:sup>−1</jats:sup>, but this effect needs more investigation. The coastal site enabled the possibility of investigating physical and environmental effects on <jats:italic>W</jats:italic> that would otherwise have been more difficult to observe in the open ocean.</jats:p>

Journal article

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