Anna Rutgersson

A Global View on the Wind Sea and Swell Climate and Variability from ERA-40

In this paper a detailed global climatology of wind sea and swell parameters, based on the ERA-40 wave reanalysis, is presented. The spatial pattern of the swell dominance of the Earth’s Oceans, in ...

A case study of air-sea interaction during swell conditions

Air-sea interaction data from a situation with pronounced unidirectional swell have been analyzed. Measurements of turbulence at three levels (10, 18, and 26 m above mean sea level) together with directional wave buoy data from the site Ostergarnsholm in the Baltic Sea were used. The situation, which lasted for ∼48 hours, appeared in the aftermath of a gale. The wind direction during the swell situation turned slowly within a 90° sector. Both during the gale phase and the swell phase the over-water fetch was >150 km. The wind speed during the swell phase was typically 4 m s−1. During the swell phase a wind maximum near or below the lowest wind speed measuring level 10 m was observed. The net momentum flux was very small, resulting in CD values ∼0.7 × 10−3. Throughout the lowest 26 m, covered by the tower measurements, turbulence intensities in all three components remained high despite the low value of the kinematic momentum flux -u′w′¯ resulting in a reduction of the correlation coefficient for the longitudinal and vertical velocity from its typical value around −0.35 to between −0.2 and 0 (and with some positive values at the higher measuring levels), appearing abruptly at wave age c0/U10 equal to 1.2. Turbulence spectra of the horizontal components were shown not to scale with height above the water surface, in contrast to vertical velocity spectra for which such a variation was observed in the low-frequency range. In addition, spectral peaks in the horizontal wind spectra were found at a frequency as low as 10−3 Hz. From a comparison with results from a previous study it was concluded that this turbulence is of the “inactive” kind, being brought down from the upper parts of the boundary layer by pressure transport.

A global perspective on Langmuir turbulence in the ocean surface boundary layer

The turbulent mixing in thin ocean surface boundary layers (OSBL), which occupy the upper 100 m or so of the ocean, control the exchange of heat and trace gases between the atmosphere and ocean. Here we show that current parameterizations of this turbulent mixing lead to systematic and substantial errors in the depth of the OSBL in global climate models, which then leads to biases in sea surface temperature. One reason, we argue, is that current parameterizations are missing key surface-wave processes that force Langmuir turbulence that deepens the OSBL more rapidly than steady wind forcing. Scaling arguments are presented to identify two dimensionless parameters that measure the importance of wave forcing against wind forcing, and against buoyancy forcing. A global perspective on the occurrence of wave-forced turbulence is developed using re-analysis data to compute these parameters globally. The diagnostic study developed here suggests that turbulent energy available for mixing the OSBL is under-estimated without forcing by surface waves. Wave-forcing and hence Langmuir turbulence could be important over wide areas of the ocean and in all seasons in the Southern Ocean. We conclude that surface-wave-forced Langmuir turbulence is an important process in the OSBL that requires parameterization. Citation: Belcher, S. E., et al. (2012), A global perspective on Langmuir turbulence in the ocean surface boundary layer, Geophys. Res. Lett., 39, L18605, doi: 10.1029/2012GL052932.

Future changes in the Baltic Sea acid-base (pH) and oxygen balances

ABSTRACT Possible future changes in Baltic Sea acid–base (pH) and oxygen balances were studied using a catchment–sea coupled model system and numerical experiments based on meteorological and hydrological forcing datasets and scenarios. By using objective statistical methods, climate runs for present climate conditions were examined and evaluated using Baltic Sea modelling. The results indicate that increased nutrient loads will not inhibit future Baltic Sea acidification; instead, the seasonal pH cycle will be amplified by increased biological production and mineralization. All examined scenarios indicate future acidification of the whole Baltic Sea that is insensitive to the chosen global climate model. The main factor controlling the direction and magnitude of future pH changes is atmospheric CO2 concentration (i.e. emissions). Climate change and land-derived changes (e.g. nutrient loads) affect acidification mainly by altering the seasonal cycle and deep-water conditions. Apart from decreasing pH, we also project a decreased saturation state of calcium carbonate, decreased respiration index and increasing hypoxic area – all factors that will threaten the marine ecosystem. We demonstrate that substantial reductions in fossil-fuel burning are needed to minimise the coming pH decrease and that substantial reductions in nutrient loads are needed to reduce the coming increase in hypoxic and anoxic waters.

Wave-Induced Wind in the Marine Boundary Layer

Recent field observations and large-eddy simulations have shown that the impact of fast swell on the marine atmospheric boundary layer (MABL) might be stronger than previously assumed. For low to moderate winds blowing in the same direction as the waves, swell propagates faster than the mean wind. The momentum flux above the sea surface will then have two major components: the turbulent shear stress, directed downward, and the swell-induced stress, directed upward. For sufficiently high wave age values, the wave-induced component becomes increasingly dominant, and the total momentum flux will be directed into the atmosphere. Recent field measurements have shown that this upward momentum transfer from the ocean into the atmosphere has a considerable impact on the surface layer flow dynamics and on the turbulence structure of the overall MABL. The vertical wind profile will no longer exhibit a logarithmic shape because an acceleration of the airflow near the surface will take place, generating a low-level wave-driven wind maximum (a wind jet). As waves propagate away from their generation area as swell, some of the wave momentum will be returned to the atmosphere in the form of wave-driven winds. A model that qualitatively reproduces the wave-following atmospheric flow and the wave-generated wind maximum, as seen from measurements, is proposed. The model assumes a stationary momentum and turbulent kinetic energy balance and uses the dampening of the waves at the surface to describe the momentum flux from the waves to the atmosphere. In this study, simultaneous observations of wind profiles, turbulent fluxes, and wave spectra during swell events are presented and compared with the model. In the absence of an established model for the linear damping ratio during swell conditions, the model is combined with observations to estimate the wave damping. For the cases in which the observations showed a pronounced swell signal and almost no wind waves, the agreement between observed and modeled wind profiles is remarkably good. The resulting attenuation length is found to be relatively short, which suggests that the estimated damping ratios are too large. The authors attribute this, at least partly, to processes not accounted for by the model, such as the existence of an atmospheric background wind. In the model, this extra momentum must be supplied by the waves in terms of a larger damping ratio.

Use of conventional stability parameters during swell

The situation with swell is of climatological importance over the Baltic Sea since swell is present during as much as 40% of the time. In this study, two periods with unstable and two periods with stable stratification and wind following swell are investigated. Data are taken at a small flat island in the Baltic Sea. During unstable stratification the turbulent structure shows great resemblance to the free convective boundary layer and scales with the boundary layer height. Since surface heat flux is too small to support the high levels of turbulence present, inactive turbulence is probably the dominating source. For the stably stratified layer, there are smaller differences between data with and without swell. The turbulence is mainly transported upward into the atmosphere with the aid of pressure fluctuations induced by the waves. For most of the data with swell the gradients are smaller than for growing sea. During unstable conditions the wind gradients are negative, indicating the presence of a wave-driven wind. The gradients increase with increasing height above the surface. The drag coefficient is smaller than is usually found for both stable and unstable stratification and varies very little with wind and stratification. There are only small variations in the heat transfer coefficients with changing stratification, but they are significantly different for stable and unstable stratification.

Measured and simulated latent and sensible heat fluxes at two marine sites in the Baltic Sea

In this study, turbulent heat flux data from two sites within the Baltic Sea are compared with estimates from two models. The main focus is on the latent heat flux. The measuring sites are located on small islands close to the islands of Bornholm and Gotland. Both sites have a wide wind direction sector with undisturbed over-water fetch. Mean parameters and direct fluxes were measured on masts during May to December 1998.The two models used in this study are the regional-scale atmospheric model HIRLAM and the ocean model PROBE-Baltic. It is shown that both models overestimate the sensible and latent heat fluxes. The overestimation can, to a large extent, be explained by errors in the air-water temperature and humidity differences. From comparing observed and modelled data, the estimated 8-month mean errors in temperature and humidity are up to 1 °C and 1 g kg-1, respectively. The mean errors in the sensible and latent heat fluxes for the same period are approximately 15 and 30 W m-2, respectively.Bulk transfer coefficients used for calculating heat and humidity fluxes at the surface were shown to agree rather well with the measurements, at least for the unstable data. For stable stratification, the scatter in data is generally large, and it appears that the bulk formulation chosen overestimates turbulent heat fluxes.

Transfer Across the Air-Sea Interface

The efficiency of transfer of gases and particles across the air-sea interface is controlled by several physical, biological and chemical processes in the atmosphere and water which are described here (including waves, large- and small-scale turbulence, bubbles, sea spray, rain and surface films). For a deeper understanding of relevant transport mechanisms, several models have been developed, ranging from conceptual models to numerical models. Most frequently the transfer is described by various functional dependencies of the wind speed, but more detailed descriptions need additional information. The study of gas transfer mechanisms uses a variety of experimental methods ranging from laboratory studies to carbon budgets, mass balance methods, micrometeorological techniques and thermographic techniques. Different methods resolve the transfer at different scales of time and space; this is important to take into account when comparing different results. Air-sea transfer is relevant in a wide range of applications, for example, local and regional fluxes, global models, remote sensing and computations of global inventories. The sensitivity of global models to the description of transfer velocity is limited; it is however likely that the formulations are more important when the resolution increases and other processes in models are improved. For global flux estimates using inventories or remote sensing products the accuracy of the transfer formulation as well as the accuracy of the wind field is crucial.

Diurnal cycle of lake methane flux

Air-lake methane flux (FCH4) and partial pressure of methane in the atmosphere (pCH4a) were measured using the eddy covariance method over a Swedish lake for an extended period. The measurements show a diurnal cycle in both FCH4 and pCH4a with high values during nighttime (FCH4 ≈ 300 nmol m−2 s−1, pCH4a ≈ 2.5 µatm) and low values during day (FCH4 ≈ 0 nmol m−2 s−1, pCH4a ≈ 2.0 µatm) for a large part of the data set. This diurnal cycle persist in all open water season; however, the magnitude of the diurnal cycle is largest in the spring months. Estimations of buoyancy in the water show that high nighttime fluxes coincide with convective periods. Our interpretation of these results is that the convective mixing enhances the diffusive flux, in analogy to previous studies. We also suggest that the convection may bring methane-rich water from the bottom to the surface and trigger bubble release from the sediment. A diurnal cycle is not observed for all convective occasions, indicating that the presence of convection is not sufficient for enhanced nighttime flux; other factors are also necessary. The observed diurnal cycle of pCH4a is explained with the variation of FCH4 and a changing internal boundary layer above the lake. The presence of a diurnal cycle of FCH4 stresses the importance of making long-term continuous flux measurements. A lack of FCH4 measurements during night may significantly bias estimations of total CH4 emissions from lakes to the atmosphere.

Oceanic convective mixing and the impact on air‐sea gas transfer velocity

Combination of surface water cooling and a deep ocean mixed layer generates convective eddies scaling with the depth of a mixed layer that enhances the efficiency of the airsea transfer of CO2 (and possibly other gases). This enhancement is explained by the convective eddies disturbing the molecular diffusion layer and inducing increased turbulent mixing in the water. The enhancement can be introduced into existing formulations for calculating the air‐ sea exchange of gases by using an additional resistance, due to large‐scale convection acting in parallel with other processes. The additional resistance is expressed here as 1rwc=g (w*qu*w , where w*u*w characterizes the relative role of surface shear andbuoyancy forces