Air–sea gas transfer velocity estimates from the Jason-1 and TOPEX altimeters: Prospects for a long-term global time series

Estimation of global and regional air–sea fluxes of climatically important gases is a key goal of current climate research programs. Gas transfer velocities needed to compute these fluxes can be estimated by combining altimeter-derived mean square slope with an empirical relation between transfer velocity and mean square slope derived from field measurements of gas fluxes and small-scale wave spectra [Frew, N.M., Bock, E.J., Schimpf, U., Hara, T., Hauβecker, H., Edson, J.B., McGillis, W.R., Nelson, R.K., McKenna, S.P., Uz, B.M., Jähne, B., 2004. Air–sea gas transfer: Its dependence on wind stress, small-scale roughness and surface films, J. Geophys. Res., 109, C08S17, doi: 10.1029/2003JC002131.]. We previously reported initial results from a dual-frequency (Ku- and C-band) altimeter algorithm [Glover, D.M., Frew, N.M., McCue, S.J., Bock, E.J., 2002. A Multi-year Time Series of Global Gas Transfer Velocity from the TOPEX Dual Frequency, Normalized Radar Backscatter Algorithm, In: Gas Transfer at Water Surfaces, editors: Donelan, M., Drennan, W., Saltzman, E., and Wanninkhof, R., Geophysical Monograph 127, American Geophysical Union, Washington, DC, 325–331.] for estimating the air–sea gas transfer velocity (k) from the mean square slope of short wind waves (40–100 rad/m) and derived a 6-year time series of global transfer velocities based on TOPEX observations. Since the launch of the follow-on altimeter Jason-1 in December 2001 and commencement of the TOPEX/Jason-1 Tandem Mission, we have extended this time series to 12 years, with improvements to the model parameters used in our algorithm and using the latest corrected data releases. The prospect of deriving multi-year and interdecadal time series of gas transfer velocity from TOPEX, Jason-1 and follow-on altimeter missions depends on precise intercalibration of the normalized backscatter. During the Tandem Mission collinear phase, both satellites followed identical orbits with a mere 73-s time separation. The resulting collocated, near-coincident normalized radar backscatter (σ°) data from both altimeters present a unique opportunity to intercalibrate the two instruments, compare derived fields of transfer velocity and estimate the precision of the algorithm. Initial results suggest that the monthly gas transfer velocity fields generated from the two altimeters are very similar. Comparison of along-track Ku-band and C-band σ° during the collinear phase indicates that observed discrepancies are due primarily to small offsets between TOPEX and Jason-1 σ°. The Jason-1 k values have an apparent bias of + 4% relative to TOPEX, while the precision estimated from the two observation sets is 5–7% and scales with k. The resultant long-term, global, mean k is 16 cm/h.     

Parameterization of air–sea gas fluxes at extreme wind speeds

Air–sea flux measurements of O₂ and N₂ obtained during Hurricane Frances in September 2004 [D'Asaro, E. A. and McNeil, C. L., 2006. Measurements of air–sea gas exchange at extreme wind speeds. Journal Marine Systems, this edition.] using air-deployed neutrally buoyant floats reveal the first evidence of a new regime of air–sea gas transfer occurring at wind speeds in excess of 35 m s^− 1. In this regime, plumes of bubbles 1 mm and smaller in size are transported down from near the surface of the ocean to greater depths by vertical turbulent currents with speeds up to 20−30 cm s^− 1. These bubble plumes mostly dissolve before reaching a depth of approximately 20 m as a result of hydrostatic compression. Injection of air into the ocean by this mechanism results in the invasion of gases in proportion to their tropospheric molar gas ratios, and further supersaturation of less soluble gases. A new formulation for air–sea fluxes of weakly soluble gases as a function of wind speed is proposed to extend existing formulations [Woolf, D.K, 1997. Bubbles and their role in gas exchange. In: Liss, P.S., and Duce, R.A., (Eds.), The Sea Surface and Global Change. Cambridge University Press, Cambridge, UK, pp. 173–205.] to span the entire natural range of wind speeds over the open ocean, which includes hurricanes. The new formulation has separate contributions to air–sea gas flux from: 1) non-supersaturating near-surface equilibration processes, which include direct transfer associated with the air–sea interface and ventilation associated with surface wave breaking; 2) partial dissolution of bubbles smaller than 1 mm that mix into the ocean via turbulence; and 3) complete dissolution of bubbles of up to 1 mm in size via subduction of bubble plumes. The model can be simplified by combining “surface equilibration” terms that allow exchange of gases into and out of the ocean, and “gas injection” terms that only allow gas to enter the ocean. The model was tested against the Hurricane Frances data set. Although all the model parameters cannot be determined uniquely, some features are clear. The fluxes due to the surface equilibration terms, estimated both from data and from model inversions, increase rapidly at high wind speed but are still far below those predicted using the cubic parameterization of Wanninkhof and McGillis [Wannikhof, R. and McGillis, W.R., 1999. A cubic relationship between air–sea CO₂ exchange and wind speed. Geophysical Research Letters, 26:1889–1892.] at high wind speed. The fluxes due to gas injection terms increase with wind speed even more rapidly, causing bubble injection to dominate at the highest wind speeds.     

An approach to estimation of near-surface turbulence and CO2 transfer velocity from remote sensing data

The air–sea CO₂ exchange is primarily determined by the boundary-layer processes in the near-surface layer of the ocean since it is a water-side limited gas. As a consequence, the interfacial component of the CO₂ transfer velocity can be linked to parameters of turbulence in the near-surface layer of the ocean. The development of remote sensing techniques provides a possibility to quantify the dissipation of the turbulent kinetic energy in the near-surface layer of the ocean and the air–sea CO₂ transfer velocity on a global scale. In this work, the dissipation rate of the turbulent kinetic energy in the near-surface layer of the ocean and its patchiness has been linked to the air–sea CO₂ transfer velocity with a boundary-layer type model. Field observations of upper ocean turbulence, laboratory studies, and the direct CO₂ flux measurements are used to validate the model. The model is then forced with the TOPEX POSEIDON wind speed and significant wave height to demonstrate its applicability for estimating the distribution of the near-surface turbulence dissipation rate and gas transfer velocity for an extended (decadal) time period. A future version of this remote sensing algorithm will incorporate directional wind/wave data being available from QUIKSCAT, a now-cast wave model, and satellite heat fluxes. The inclusion of microwave imagery from the Special Sensor Microwave Imager (SSM/I) and the Synthetic Aperture Radar (SAR) will provide additional information on the fractional whitecap coverage and sea surface turbulence patchiness.     

Whitecap coverage in coastal environment for steady and unsteady wave field conditions

Breaking waves represent a “key” parameter for many applications involved with a large number of environmental phenomena. In particular, it is well recognized that the whitecap cover induced by breaking waves allows substantial enhancement of heat, momentum, gas and particle transfer at the air–sea interface. A large number of studies were conducted during the last decades on the variation of the whitecap fraction, commonly noted W. The results presented in this paper deal with the evolution of the whitecap coverage in coastal zone. In such areas, the wave field is often unsteady with an important variety of sea state developments. The present analysis is based on an extensive series of data obtained during an experimental campaign which took place on the Mediterranean coast in 2001. The results allow observation of the influence of the sea state conditions of the wave field on the whitecap coverage. In addition, this paper confirms the occurrence of a peak in the variations of the whitecap fraction with the wave age for coastal areas as suggested by Lafon et al. [Lafon, C., Piazzola, J., Forget, P., Le Calvé, O. and Despiau, S., 2004. Analysis of the variations of the whitecap fraction as measured in a coastal zone. Boundary-Layer Meteorol., 111: 339-360.]. A wave age dependent model for the whitecap fraction is then proposed, which takes into account both the wind and the wave influence, and hence, is characteristics of the different sea state conditions.     

Seasonal study of dissolved CH4, CO2 and N2O in a shallow tidal system of the bay of Cádiz (SW Spain)

During 2004, 10 samplings were performed in order to measure dissolved methane (CH₄), carbon dioxide (CO₂) and nitrous oxide (N₂O) in the surface waters of Río San Pedro, a tidal creek in the salt marsh area of the Bay of Cádiz (SW Spain). The inner partvs of the creek is affected by the inputs coming from an intensive fish farm and the drainage of an extensive salt marsh area.Dissolved CH₄, CO₂ and N₂O concentrations ranged from 11 to 88 nM, 36 to 108 μM and 14 to 50 nM, respectively. Surface waters were in all cases oversaturated with respect to the atmosphere, reaching values of up to 5000% for CH₄, 1240% for CO₂ and 840% for N₂O. Dissolved CH₄, CO₂ and N₂O showed a significant tidal and seasonal variability. Over a tidal cycle, concentrations were always highest during low tide, which points to the influence of the inputs from the fish farm effluent and the drainage of the adjacent salt marsh area, as well as in situ production within the system. Dissolved CH₄, CO₂ and N₂O seasonal patterns were similar and showed maximum concentrations in summer conditions. Using four different parameterizations to calculate the gas transfer coefficients [Liss, P.S. and Merlivat, L., 1986. Air-sea exchange rates: introduction and synthesis. In P. Buat-Ménard (Ed.), The Role of Air-Sea Exchanges in Geochemical Cycling. Reidel, Dordrecht, The Netherlands, p. 113–127.; Clark, J.F., Schlosser, P., Simpson, H.J., Stute, M., Wanninkhof, R., and Ho, D.T., 1995. Relationship between gas transfer velocities and wind speeds in the tidal Hudson River determined by the dual tracer technique. In: B. Jähne and E. Monahan (Eds.), Air-Water Gas Transfer: AEON Verlag and Studio, Hanau, Germany, pp. 785–800.; Carini, S., Weston, N., Hopkinson, G., Tucker, J., Giblin, A. and Vallino, J., 1996. Gas exchanges rates in the Parker River estuary, Massachusetts. Biol. Bull., 191: 333–334.; Kremer, J.N., Reischauer, A. and D'Avanzo, C., 2003. Estuary-specific variation in the air-water gas exchange coefficient for oxygen. Estuaries, 26: 829–836.], the averaged air–water fluxes of CH₄, CO₂ and N₂O from the creek to the atmosphere ranged between 34 and 150 μmol CH₄ m^− 2 day^− 1, 73 and 177 mmol CO₂ m^− 2 day^− 1 and 24 and 62 μmol N₂O m⁻² day⁻¹, respectively.     

The combined effect of rain and wind on air–water gas exchange: A feasibility study

A series of experiments were conducted at University of Delaware's Air–Sea Interaction Laboratory to examine the combined effects of rain and wind on air–water gas exchange. During this study, ASIL WRX I, a combination of 3 rain rates and 4 wind speeds were used, for a total of 12 different environmental conditions. The SF₆ evasion method was used to determine the bulk gas transfer velocities, and airside profiles of wind and CO₂ were used to estimate flux–profiles of momentum and carbon dioxide. In addition to measurements of fluxes with and without rain in a wind–wave boundary layer, measurements of wave properties were also obtained. Rain is shown to alter the wind profile in the flume, and dampen surface waves. Also, SF₆ evasion indicates that with the present experimental setup, for most of the experimental conditions, rain and wind combine linearly to influence air–water gas exchange. Flux–profile relationships for marine atmospheric boundary layers, which were performed to scale up to field measurements, were explored by a comparison between SF₆-derived bulk fluxes and airside CO₂ profile measurements.     

Evaluating transfer velocity-wind speed relationship using a long-term series of direct eddy correlation CO2 flux measurements

Long-term observations of the marine atmospheric boundary layer were performed by an eddy correlation system, which was set-up on a platform in the Baltic Sea. In this experiment the three-dimensional wind vector and the turbulent fluxes of momentum, sensible and latent heat and CO₂ were measured for one and a half years. Simultaneously the CO₂ partial pressure p_CO2 in surface water was measured by a submersible autonomous moored instrument for CO₂ at the platform in 7-m depth. The high-resolution eddy correlation measurements of the atmospheric CO₂ flux F_CO2, together with the measurements of the CO₂ partial pressure differences between air and sea Δp_CO2 led to a long-term data set which provided the possibility to investigate the parameterization of the CO₂ transfer velocity k as a function of 10-m wind speed u in a statistical manner. From half-hour mean CO₂ fluxes and CO₂ partial pressure differences, k was calculated using k = F_CO2 / (K₀Δp_CO2), with K₀ the CO₂ solubility. The half-hour mean data points, used for the determination of the k–u parameterization, show large scatter. However, assuming a linear, quadratic dependency the analysis yields: k₆₆₀ = 0.365u² + 0.46u (k at 20 °C and salinity 35 psu) with a correlation coefficient of r² = 0.81. The large scatter indicates that the kinetics of the air–sea CO₂ transfer velocity is not only a function of the wind speed alone, but might also be controlled by other environmental parameters and mechanisms, such as sea state and surface coverage with surfactants.     

Effect of wave boundary layer on sea-to-air dimethylsulfide transfer velocity during typhoon passage

A full-spectral third-generation ocean wind–wave model (Wavewatch-III) implemented in the South China Sea is used to investigate the effects of the wave boundary layer on the drag coefficient and the sea-to-air transfer velocity of dimethylsulfide (DMS) during passage of Typhoon Wukong (September 5–11, 2000) with a maximum sustained wind speed of 38 m s^− 1. The model is driven by the reanalyzed surface winds (1° × 1°, four times daily) from the National Centers for Environmental Prediction. It is found that the wave boundary layer evidently enhances (16.5%) the drag coefficient (in turn increases the momentum flux across the air–sea interface), and reduces (13.1%) the sea-to-air DMS transfer velocity (in turn decreases the sea-to-air DMS flux). This indicates the possibility of important roles of wave boundary layer in atmospheric DMS contents and global climate system.     

Lengthscales of motions that control air–water gas transfer in grid-stirred turbulence

The relationship between the gas transfer velocity and turbulent lengthscales is investigated experimentally in a grid-stirred turbulent flow. The horizontal velocity field at the water surface is measured using particle image velocimetry (PIV). The gas transfer velocity for oxygen is obtained through reaeration experiments. In addition, the gas transfer process by surface-renewal eddies is visualized using laser-induced fluorescence (LIF) technique, in which carbon dioxide is used as the tracer gas. The definition of the Taylor microscale holds that the root-mean-square (RMS) of the surface divergence is expressed by the square root of the turbulent kinetic energy divided by the Taylor microscale. Experimentally obtained data support this scaling. They show the gas transfer velocity to be proportional to the square root of the RMS of the surface divergence. These experimental results imply that the Taylor microscale is an important parameter for gas transfer velocity at the air–water interface. These relations indicate that a nondimensional gas transfer velocity is proportional to the − 1/4 power of a turbulent-macroscale Reynolds number, which is similar to a small-eddy model, assuming that turbulent eddies with the Kolmogorov scale control the gas transfer process. However, this Reynolds number dependence does not necessarily mean the superiority of turbulent eddies with the Kolmogorov scale in the gas transfer. The LIF visualizations in horizontal and vertical planes close to the air–water interface indicate that the horizontal CO₂-concentration field has a fine spatial pattern, which resembles that of the surface divergence field, and that surface-renewal motions observed in the vertical plane have a larger lengthscale than the Kolmogorov scale. We infer from both PIV and LIF results that the Taylor microscale is an important lengthscale for air–water gas transfer.     

Gas transfer velocities of CO2 and CH4 in a tropical reservoir and its river downstream

We have measured simultaneously the methane (CH₄) and carbon dioxide (CO₂) surface concentrations and water–air fluxes by floating chambers (FC) in the Petit-Saut Reservoir (French Guiana) and its tidal river (Sinnamary River) downstream of the dam, during the two field experiments in wet (May 2003) and dry season (December 2003). The eddy covariance (EC) technique was also used for CO₂ fluxes on the lake. The comparison of fluxes obtained by FC and EC showed little discrepancies mainly due to differences in measurements durations which resulted in different average wind speeds. When comparing the gas transfer velocity (k₆₀₀) for a given wind speed, both methods gave similar results. On the lake and excluding rainy events, we obtained an exponential relationship between k₆₀₀ and U₁₀, with a significant intercept at 1.7 cm h^− 1, probably due to thermal effects. Gas transfer velocity was also positively related to rainfall rates reaching 26.5 cm h⁻¹ for a rainfall rate of 36 mm h^− 1. During a 24-h experiment in dry season, rainfall accounted for as much as 25% of the k₆₀₀. In the river downstream of the dam, k₆₀₀ values were 3 to 4 times higher than on the lake, and followed a linear relationship with U₁₀.     

Measurement of air–water CO2 transfer at four coastal sites using a chamber method

We measured the air–water CO₂ flux in four coastal regions (two coral reefs, one estuary, and one coastal brackish lake) using a chamber method, which has the highest spatial resolution of the methods available for measuring coastal air–water gas flux. Some of the measurements were considerably higher than expected from reported wind-dependent relationships. The average k₆₀₀ values for Shiraho Reef, Fukido Reef, Fukido River, and Lake Nakaumi were 1.5 ± 0.6, 3.2 ± 0.3, 0.69 ± 0.26, and 2.2 ± 0.9 (mean ± S.D.) times larger than the wind-dependent relationships. Results were compared with current-dependent relationships and vertical turbulence intensity (VTI). VTI is an index of water-surface stirring and is calculated from near-surface vertical velocity. Although some measurements from the reefs and river closely matched those expected from wind-dependent relationships, others were considerably higher. All data were correlated with VTI and were qualitatively explained by bottom macro-roughness enhancement. In Lake Nakaumi, results tended to differ from the wind-dependent relationships, and the difference between the measured and expected gas-transfer velocity was correlated with biological DO changes and/or the intensity of density stratification. We found these factors to have important effects on coastal gas flux. In addition, the chamber method was an effective tool for evaluating coastal gas flux.     

Air–sea gas exchange at extreme wind speeds measured by autonomous oceanographic floats

Measurements of the air–sea fluxes of N₂ and O₂ were made in winds of 15–57 m s^− 1 beneath Hurricane Frances using two types of air-deployed neutrally buoyant and profiling underwater floats. Two “Lagrangian floats” measured O₂ and total gas tension (GT) in pre-storm and post-storm profiles and in the actively turbulent mixed layer during the storm. A single “EM-APEX float” profiled continuously from 30 to 200 m before, during and after the storm. All floats measured temperature and salinity. N₂ concentrations were computed from GT and O₂ after correcting for instrumental effects. Gas fluxes were computed by three methods. First, a one-dimensional mixed layer budget diagnosed the changes in mixed layer concentrations given the pre-storm profile and a time varying mixed layer depth. This model was calibrated using temperature and salinity data. The difference between the predicted mixed layer concentrations of O₂ and N₂ and those measured was attributed to air–sea gas fluxes F_BO and F_BN. Second, the covariance flux F_CO(z) = wO₂′(z) was computed, where w is the vertical motion of the water-following Lagrangian floats, O₂′ is a high-pass filtered O₂ concentration and (z) is an average over covariance pairs as a function of depth. The profile F_CO(z) was extrapolated to the surface to yield the surface O₂ flux F_CO(0). Third, a deficit of O₂ was found in the upper few meters of the ocean at the height of the storm. A flux F_SO, moving O₂ out of the ocean, was calculated by dividing this deficit by the residence time of the water in this layer, inferred from the Lagrangian floats. The three methods gave generally consistent results. At the highest winds, gas transfer is dominated by bubbles created by surface wave breaking, injected into the ocean by large-scale turbulent eddies and dissolving near 10-m depth. This conclusion is supported by observations of fluxes into the ocean despite its supersaturation; by the molar flux ratio F_BO/F_BN, which is closer to that of air rather than that appropriate for Schmidt number scaling; by O₂ increases at about 10-m depth along the water trajectories accompanied by a reduction in void fraction as measured by conductivity; and from the profile of F_CO(z), which peaks near 10 m instead of at the surface.At the highest winds O₂ and N₂ are injected into the ocean by bubbles dissolving at depth. This, plus entrainment of gas-rich water from below, supersaturates the mixed layer causing gas to flux out of the near-surface ocean. A net influx of gas results from the balance of these two competing processes. At lower speeds, the total gas fluxes, F_BO, F_BN and F_CO(0), are out of the ocean and downgradient.     

The Mercator global ocean operational analysis system: Assessment and validation of an 11-year reanalysis

This paper presents Prototype Système 2 Global (PSY2G), the first Mercator global Ocean General Circulation Model (OGCM) to assimilate along-track sea level anomaly (SLA) satellite data. Based on a coarse resolution ocean model, this system was developed mainly for climatic purposes and will provide, for example, initial oceanic states for coupled ocean-atmosphere seasonal predictions. It has been operational since 3 September 2003 and produces an analysis and a two-week forecast for the global ocean every week. The PSY2G system uses an incremental assimilation scheme based on the Cooper and Haines [Cooper, M., Haines, K., 1996. Data assimilation with water property conservation. J. Geophys. Res., 101, 1059-1077.] lifting–lowering of isopycnals. The SLA increment is obtained using an optimal interpolation method then the correction is partitioned into baroclinic and barotropic contributions. The baroclinic ocean state correction consists of temperature, salinity and geostrophic velocity increments and the barotropic correction is a barotropic velocity increment. A reanalysis (1993–2003) was carried out that enabled the PSY2G system to perform its first operational cycle. All available SLA data sets (TOPEX/Poséïdon, ERS2, Geosat-Follow-On, Jason1 and Envisat) were assimilated for the 1993–2003 period. The major objective of this study is to assess the reanalysis from both an assimilation and a thermodynamic point of view in order to evaluate its realism, especially in the tropical band which is a key region for climatic studies. Although the system is also able to deliver forecasts, we have mainly focused on analysis. These results are useful because they give an a priori estimation of the qualities and capabilities of the operational ocean analysis system that has been implemented. In particular, the reanalysis identifies some regional biases in sea level variability such as near the Antarctic Circumpolar Current, in the eastern Equatorial Pacific and in the Norwegian Sea (generally less than 1 cm) with a small seasonal cycle. This is attributed to changes in mean circulation and vertical stratification caused by the assimilation methodology. But the model's low resolution, inaccurate physical parameterisations (especially for ocean–ice interactions) and surface atmospheric forcing also contribute to the occurrence of the SLA biases. A detailed analysis of the thermohaline structure of the ocean reveals that the isopycnal lifting–lowering tends to diffuse vertically the main thermocline. The impact on temperature is that the surface layer (0–200 m) becomes cooler whereas in deeper waters (from 500 to 1500 m), the ocean becomes slightly warmer. This is particularly true in the tropics, between 30°N and 30°S. However it can be demonstrated that the assimilation improves the variability in both surface currents and sub-surface temperature in the Equatorial Pacific Ocean.     

Coupled renewal model of ocean viscous sublayer, thermal skin effect and interfacial gas transfer velocity

A previously developed renewal model included parameterizations for the thermal skin effect and interfacial gas transfer velocity. The more readily available cool skin data were used for an adjustment of the gas transfer parameterization. In this work, the renewal concept is extended to include the velocity difference across the viscous sublayer and to account for the stage of surface wave development. As a result, the empirical coefficients that enter the renewal model have been specified more accurately using laboratory data on the surface wind drift current. In addition, the coefficient linking the cool skin and gas transfer parameterization formulas has been determined from the probability distribution function for renewal events. A comparison of the upgraded renewal model with the thermal skin data collected during the COARE and more recent field programs and with gas transfer data collected during GasEx-01 experiment suggests that the renewal model can be a useful tool for producing a physically based parameterization for the interfacial CO₂ transfer velocity. Model uncertainties associated with the effect of surface films are discussed.     

Influence of convection on mixed-layer evolution: comparison of two mixing parameterizations with buoys data in the Bay of Biscay

In this study, we compare two 1-D mixing parameterizations developed by Gaspar et al. [J. Geophys. Res. C95 (C9) (1990) 16179] (G90) and Large et al. [Rev. Geophys. 32 (1994) 363] (L94), respectively. Both models are tested against drifting Marisonde bouys deployed in the Bay of Biscay during PRECOCE experiment (1997–1998) [Mariette, V., Ratsivalaka, C., Verbéque V., Leborgne, E., 1999. CAMPAGNE PREOCOCE (PREdiction du comportement des Couches superficielles de l'Océan le long des Côtes Européennes, Tomes 1, 2 and 3, Rapport EPSHOM/CMO/RE/NP 11 du 31 mai 1999]. Periods of stabilizing and destabilizing conditions are successively examined by using both realistic and schematic dynamical and thermodynamical air–sea fluxes. Schematic conditions applied over one diurnal cycle evidence the relative performance of G90 and L94 parameterizations as a function of surface inputs and stratification. The results obtained from these schematic cases are used to compare the results obtained by G90 and L94 over periods of 2 to 10 weeks along three Marisonde buoy trajectories. The ability of both models to simulate the seasonal thermocline formation in Spring as well as its destruction in Fall is discussed. If the nonlocal parameterization used by L94 is taken in its complete form (including the diapycnal mixing), it allows the mixed-layer deepening in Fall in a more satisfactory way than the local parameterization used by G90. The results obtained in Spring by both models are debatable.     

Inorganic carbon fluxes through the boundaries of the Greenland Sea Basin based on in situ observations and water transport estimates

A carbon budget for the exchange of total dissolved inorganic carbon C_T between the Greenland Sea and the surrounding seas has been constructed for winter and summer situations. An extensive data set of C_T collected over the years 1994–1997 within the European Sub-polar Ocean Programmes (ESOP1 and ESOP2) are used for the budget calculation. Based on these data, mean values of C_T in eight different boxes representing the inflow and outflow of water through the boundaries of the Greenland Sea Basin are estimated. The obtained values are then combined with simulated water transports taken from the ESOP2 version of the Miami Isopycnic Coordinate Ocean Model (MICOM). The fluxes of inorganic carbon are presented for three layers; a surface mixed layer, an intermediate layer and a deep layer, and the imbalance in the fluxes are attributed to air–sea exchange, biological fixation of inorganic carbon, and sedimentation. The main influx of carbon is found in the surface and the deep layers in the Fram Strait, and in the surface waters of direct Atlantic origin, whereas the main outflux is found in the surface layer over the Jan Mayen Fracture Zone and the Knipovich Ridge, transporting carbon into the Atlantic Ocean via the Denmark Strait and towards the Arctic Ocean via the Norwegian Sea, respectively. The flux calculation indicates that there is a net transport of carbon out of the Greenland Sea during wintertime. In the absence of biological activity, this imbalance is attributed to air sea exchange, and requires an oceanic uptake of CO₂ of 0.024±0.006 Gt C yr⁻¹. The flux calculations from the summer period are complicated by biological fixation of inorganic carbon, and show that data on organic carbon is required in order to estimate the air–sea exchange in the area.     

Time-series analysis of remote-sensed chlorophyll and environmental factors in the Santa Monica–San Pedro Basin off Southern California

The time-series of remote-sensed surface chlorophyll concentration measured by SeaWiFS radiometer from September 1997 to December 2001 and the relevant hydrological and meteorological factors (remote-sensed sea surface temperature, atmospheric precipitation, air temperature and wind stress) in Santa Monica Bay and adjacent waters off southern California were analyzed using wavelet and cross-correlation statistical methods. All parameters exhibited evident seasonal patterns of variation. Wavelet analysis revealed salient long-term variations most evident in air temperature during El Niño 1997–1998 and in wind stress during La Niña 1998–1999. Short-period (<100 days) variations of remote-sensed chlorophyll biomass were mostly typical to spring seasons. Chlorophyll biomass was significantly correlated with air temperature and wind stress: an increase of chlorophyll biomass followed with 5–6-day time lag an increase of wind stress accompanied by a simultaneous decrease of air temperature. The mechanism of these variations was an intensification of phytoplankton growth resulting from the mixing of water column by wind stress and entrainment of nutrients into the euphotic layer.     

Protist entrapment in newly formed sea ice in the Coastal Arctic Ocean

Protist abundance and taxonomic composition were determined in four development stages of newly formed sea ice (new ice, nilas, young ice and thin first-year ice) and in the underlying surface waters of the Canadian Beaufort Sea from 30 September to 19 November 2003. Pico- and nanoalgae were counted by flow cytometry whereas photosynthetic and heterotrophic protists ≥ 4 µm were identified and counted by inverted microscopy. Protists were always present in sea ice and surface water samples throughout the study period. The most abundant protists in sea ice and surface waters were cells < 4 µm. They were less abundant in sea ice (418–3051 × 10³ cells L^− 1) than in surface waters (1393–5373 × 10³ cells L^− 1). In contrast, larger protists (≥ 4 µm) were more abundant in sea ice (59–821 × 10³ cells L^− 1) than in surface waters (22–256 × 10³ cells L^− 1). These results suggest a selective incorporation of larger cells into sea ice. The ≥ 4 µm protist assemblage was composed of a total number of 73 taxa, including 12 centric diatom species, 7 pennate diatoms, 11 dinoflagellates and 16 flagellates. The taxonomic composition in the early stage of ice formation (i.e., new ice) was very similar to that observed in surface waters and was composed of a mixed population of nanoflagellates (Prasinophyceae and Prymnesiophyceae), diatoms (mainly Chaetoceros species) and dinoflagellates. In older stages of sea ice (i.e., young ice and thin first-year ice), the taxonomic composition became markedly different from that of the surface waters. These older ice samples contained relatively fewer Prasinophyceae and more unidentified nanoflagellates than the younger ice. Diatom resting spores and dinoflagellate cysts were generally more abundant in sea ice than in surface waters. However, further studies are needed to determine the importance of this winter survival strategy in Arctic sea ice. This study clearly shows the selective incorporation of large cells (≥ 4 µm) in newly formed sea ice and the change in the taxonomic composition of protists between sea ice and surface waters as the fall season progresses.     

The influence of different turbulence schemes on modelling primary production in a 1D coupled physical–biological model

A one-dimensional (1D) coupled physical–microbiological model has been applied to a site in the central North Sea. The impact of the choice of the turbulence closure scheme on the modelling the primary production has been investigated.The model was run with four different parameterisations of vertical mixing of heat, momentum and dissolved and suspended matters, using M2 tidal forcing and the hourly mean meteorological forcing of 1989 to reproduce the annual thermal structure and primary production. The four mixing parameterisations are: Level 2 turbulence closure scheme [Mellor, G.L., Yamada, T., 1974. A hierarchy of turbulence closure models for planetary boundary layers. J. Atmos. Sci. 31, 1791–1806; Mellor, G.L., Yamada, T., 1982. Development of a turbulence closure model for geophysical Fluid problems. Rev. Geophys. Space Phys. 20 (4) 851–875] using an explicit numerical scheme [Sharples, J., Tett, P., 1994. Modelling the effect of physical variability on the midwater chlorophyll maximum. J. Mar. Res. 52, 219–238]; a version of the Level 2.5 turbulence closure scheme [Galperin, B., Kantha, L.H., Hassid, S., Rosati, A., 1988. A quasi-equilibrium turbulent energy model for geophysical flows. J. Atmos. Sci. 45, 55–62; Ruddick, K.G., Deleersnijder, E., Luyten, P.J., Ozer, J., 1995. Haline stratification in the rhine/meuse freshwater plume: a 3D model sensitivity analysis. Cont. Shelf Res. 15 (13) 1597–1630] simplified to use an algebraic mixing length by Sharples and Simpson [Sharples, J., Simpson, J.H., 1995. Semidiurnal and longer period stability cycles in the Liverpool Bay region of freshwater influence. Cont. Shelf Res. 15, 295–313], also solved explicitly; the same simplified L2.5 scheme with an implicit numerical solution and modified vertical discretisation scheme [Annan, J.D., 1999. Numerical methods for the solution of the turbulence energy equations in the shelf seas. Int. J. Numer. Methods Fluids 29, 193–206]; and another version of the same scheme (but using a different algebraic mixing length) as described by Xing and Davies [Xing, J., Davies, A.M., 1996a. Application of turbulence energy models to the computation of tidal currents and mixing intensities in the shelf edge regions. J. Phys. Oceanogr. 26, 417–447; Xing, J., Davies, A.M., 1996b. Application of a range of turbulence models to the computation of tidal currents and mixing intensities in shelf edge regions. Cont. Shelf. Res. 16, 517–547; Xing, J., Davies, A.M., 1998. Application of a range of turbulence energy models to the computation of the internal tide. Int. J. Numer. Methods Fluids 26, 1055–1084]. Various model outputs at the sea surface and in depth profiles have been compared with data collected in 1989 as part of the North Sea Project [Huthnance, J.M., 1990. Progress on North Sea Project. NERC News, vol. 12, pp. 25–29, UK]. It is shown that the biological results are extremely sensitive to the small changes in the physical conditions, which arise due to the different turbulence schemes tested. The timing of the spring bloom and the maintenance of the midwater chlorophyll maximum all differ greatly between model runs, and the gross primary production varies by a factor of two from the highest to lowest results. The simplified Level 2.5 scheme, implemented using the numerical methods of Annan [Annan, J.D., 1999. Numerical methods for the solution of the turbulence energy equations in the shelf seas. Int. J. Numer. Methods Fluids 29, 193–206], produces results, which give the best agreement with the available data.