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Despite a large number of studies, out of all drivers of radiative forcing, the effect of aerosols has the largest uncertainty in global climate model radiative forcing estimates. There have been studies of aerosol optical properties in climate models, but the effects of particle number size distribution need a more thorough inspection. We investigated the trends and seasonality of particle number concentrations in nucleation, Aitken, and accumulation modes at 21 measurement sites in Europe and the Arctic. For 13 of those sites, with longer measurement time series, we compared the field observations with the results from five climate models, namely EC-Earth3, ECHAM-M7, ECHAM-SALSA, NorESM1.2, and UKESM1. This is the first extensive comparison of detailed aerosol size distribution trends between in situ observations from Europe and five earth system models (ESMs). We found that the trends of particle number concentrations were mostly consistent and decreasing in both measurements and models. However, for many sites, climate models showed weaker decreasing trends than the measurements. Seasonal variability in measured number concentrations, quantified by the ratio between maximum and minimum monthly number concentration, was typically stronger at northern measurement sites compared to other locations. Models had large differences in their seasonal representation, and they can be roughly divided into two categories: for EC-Earth and NorESM, the seasonal cycle was relatively similar for all sites, and for other models the pattern of seasonality varied between northern and southern sites. In addition, the variability in concentrations across sites varied between models, some having relatively similar concentrations for all sites, whereas others showed clear differences in concentrations between remote and urban sites. To conclude, although all of the model simulations had identical input data to describe anthropogenic mass emissions, trends in differently sized particles vary among the models due to assumptions in emission sizes and differences in how models treat size-dependent aerosol processes. The inter-model variability was largest in the accumulation mode, i.e. sizes which have implications for aerosol-cloud interactions. Our analysis also indicates that between models there is a large variation in efficiency of long-range transportation of aerosols to remote locations. The differences in model results are most likely due to the more complex effect of different processes instead of one specific feature (e.g. the representation of aerosol or emission size distributions). Hence, a more detailed characterization of microphysical processes and deposition processes affecting the long-range transport is needed to understand the model variability.

A new method based on the Transformer model is proposed for post-processing of numerical weather prediction (NWP) forecasts of 2 m air temperature. The Transformer is a machine learning (ML) model based on self-attention, which extracts information about which inputs are most important for the prediction. It is trained using time series input from NWP variables and crowd-sourced 2 m air temperature observations from more than 1000 private weather stations (PWSs). The performance of the new post-processing model is evaluated using both observational data from PWSs and completely independent observations from the Danish Meteorological Institute (DMI) network of surface synoptic observations (SYNOP) stations. The performance of the Transformer model is compared against the raw NWP forecast, as well as against two benchmark post-processing models; a linear regression (LR) model and a neural network (NN). The results evaluated using PWS observations show an improvement in the 2 m temperature forecasts with respect to both bias and standard deviation (STD) for all three post-processing models, with the Transformer model showing the largest improvement. The raw NWP forecast, LR, NN and Transformer model have a bias and STD of 0.34 and 1.96 degrees C, 0.03 and 1.63 degrees C, 0.10 and 1.53 degrees C and 0.02 and 1.13 degrees C, respectively. The corresponding results using DMI SYNOP stations also show improved forecasts, where the Transformer model performs better than both the raw NWP forecast and the two benchmark models. However, a dependence on distance to the coast and cold temperatures is observed.

Abstract Pollutant dispersion by a tall-building cluster within a low-rise neighbourhood of Beijing is investigated using both full-scale Large-Eddy Simulation and water flume experiments at 1:2400 model-to-full scale with Particle Image Velocimetry and Planar Laser-Induced Fluorescence. The Large-Eddy Simulation and flume results of this realistic test case agree remarkably well despite differences in the inflow conditions and scale. Tall buildings have strong influence on the local flow and the development of the rooftop shear layer which dominates vertical momentum and scalar fluxes. Additional measurements using tall-buildings-only models at both 1:2400 and 1:4800 scales indicates the rooftop shear layer is insensitive to the scale. The relatively thicker incoming boundary layer affects the Reynolds stresses, the relative size of the pollutant source affects the concentration statistics and the relative laser-sheet thickness affects the spatially averaged results of the measured flow field. Low-rise buildings around the tall building cluster cause minor but non-negligible offsets in the peak magnitude and vertical location, and have a similar influence on the velocity and concentration statistics as the scale choice. These observations are generally applicable to pollutant dispersion of realistic tall building clusters in cities. The consistency between simulations and water tunnel experiments indicates the suitability of both methodologies. Graphical abstract

Persistence is an important characteristic of many complex systems in nature, related to how long the system remains at a certain state before changing to a different one. The study of complex systems' persistence involves different definitions and uses different techniques, depending on whether short-term or long-term persistence is considered. In this paper we discuss the most important definitions, concepts, methods, literature and latest results on persistence in complex systems. Firstly, the most used definitions of persistence in short-term and long-term cases are presented. The most relevant methods to characterize persistence are then discussed in both cases. A complete literature review is also carried out. We also present and discuss some relevant results on persistence, and give empirical evidence of performance in different detailed case studies, for both short-term and long-term persistence. A perspective on the future of persistence concludes the work. This research has been partially supported by the project PID2020-115454GB-C21 of the Spanish Ministry of Science and Innovation (MICINN). This research has also been partially supported by Comunidad de Madrid, PROMINT-CM project (grant ref: P2018/EMT-4366). J. Del Ser would like to thank the Basque Government for its funding support through the EMAITEK and ELKARTEK programs (3KIA project, KK-2020/00049), as well as the consolidated research group MATHMODE (ref. T1294-19). GCV work is supported by the European Research Council (ERC) under the ERC-CoG-2014 SEDAL Consolidator grant (grant agreement 647423).

River inflow affects the spatiotemporal variability of carbon dioxide (CO2) in the water column of lakes and may locally influence CO2 gas exchange with the atmosphere. However, spatiotemporal CO2 variability at river inflow sites is often unknown leaving estimates of lake-wide CO2 emission uncertain. Here, we investigated the CO2 concentration and flux variability along a river-impacted bay and remote sampling locations of Lake Onego. During 3 years, we resolved spatial CO2 gradients between river inflow and central lake and recorded the temporal course of CO2 in the bay from the ice-covered period to early summer. We found that the river had a major influence on the spatial CO2 variability during ice-covered periods and contributed similar to 35% to the total amount of CO2 in the bay. The bay was a source of CO2 to the atmosphere at ice-melt each year emitting 2-15 times the amount as an equally sized area in the central lake. However, there was large interannual variability in the spring CO2 emission from the bay related to differences in discharge and climate that affected the hydrodynamic development of the lake during spring. In early summer, the spatial CO2 variability was unrelated to the river signal but correlated negatively with dissolved oxygen concentrations instead indicating a stronger biological control on CO2. Our study reveals a large variability of CO2 and its drivers at river inflow sites at the seasonal and at the interannual time scale. Understanding these dynamics is essential for predicting lake-wide CO2 fluxes more accurately under a warming climate.

The remoteness and extreme conditions of the Arctic make it a very difficult environment to investigate. In these polar regions covered by sea ice, the wind is relatively strong due to the absence of obstructions and redistributes a large part of the deposited snow mass, which complicates estimates for precipitation hardly distinguishable from blowing or drifting snow. Moreover, the snow mass balance in the sea ice system is still poorly understood, notably due to the complex structure of its surface. Quantitatively assessing the snow distribution on sea ice and its connection to the sea ice surface features is an important step to remove the snow mass balance uncertainties (i.e., snow transport contribution) in the Arctic environment. In this work we introduce snowBedFoam 1.0., a physics-based snow transport model implemented in the open-source fluid dynamics software OpenFOAM. We combine the numerical simulations with terrestrial laser scan observations of surface dynamics to simulate snow deposition in a MOSAiC (Multidisciplinary Drifting Observatory for the Study of Arctic Climate) sea ice domain with a complicated structure typical for pressure ridges. The results demonstrate that a large fraction of snow accumulates in their vicinity, which compares favorably against scanner measurements. However, the approximations imposed by the numerical framework, together with potential measurement errors (precipitation), give rise to quantitative inaccuracies, which should be addressed in future work. The modeling of snow distribution on sea ice should help to better constrain precipitation estimates and more generally assess and predict snow and ice dynamics in the Arctic.

In this “Grand Challenges” paper, we review how the carbon isotopic composition of atmospheric CO2 has changed since the Industrial Revolution due to human activities and their influence on the natural carbon cycle, and we provide new estimates of possible future changes for a range of scenarios. Emissions of CO2 from fossil fuel combustion and land use change reduce the ratio of 13C/12C in atmospheric CO2 (δ13CO2). This is because 12C is preferentially assimilated during photosynthesis and δ13C in plant-derived carbon in terrestrial ecosystems and fossil fuels is lower than atmospheric δ13CO2. Emissions of CO2 from fossil fuel combustion also reduce the ratio of 14C/C in atmospheric CO2 (Δ14CO2) because 14C is absent in million-year-old fossil fuels, which have been stored for much longer than the radioactive decay time of 14C. Atmospheric Δ14CO2 rapidly increased in the 1950s to 1960s because of 14C produced during nuclear bomb testing. The resulting trends in δ13C and Δ14C in atmospheric CO2 are influenced not only by these human emissions but also by natural carbon exchanges that mix carbon between the atmosphere and ocean and terrestrial ecosystems. This mixing caused Δ14CO2 to return toward preindustrial levels in the first few decades after the spike from nuclear testing. More recently, as the bomb 14C excess is now mostly well mixed with the decadally overturning carbon reservoirs, fossil fuel emissions have become the main factor driving further decreases in atmospheric Δ14CO2. For δ13CO2, in addition to exchanges between reservoirs, the extent to which 12C is preferentially assimilated during photosynthesis appears to have increased, slowing down the recent δ13CO2 trend slightly. A new compilation of ice core and flask δ13CO2 observations indicates that the decline in δ13CO2 since the preindustrial period is less than some prior estimates, which may have incorporated artifacts owing to offsets from different laboratories' measurements. Atmospheric observations of δ13CO2 have been used to investigate carbon fluxes and the functioning of plants, and they are used for comparison with δ13C in other materials such as tree rings. Atmospheric observations of Δ14CO2 have been used to quantify the rate of air-sea gas exchange and ocean circulation, and the rate of net primary production and the turnover time of carbon in plant material and soils. Atmospheric observations of Δ14CO2 are also used for comparison with Δ14C in other materials in many fields such as archaeology, forensics, and physiology. Another major application is the assessment of regional emissions of CO2 from fossil fuel combustion using Δ14CO2 observations and models. In the future, δ13CO2 and Δ14CO2 will continue to change. The sign and magnitude of the changes are mainly determined by global fossil fuel emissions. We present here simulations of future δ13CO2 and Δ14CO2 for six scenarios based on the shared socioeconomic pathways (SSPs) from the 6th Coupled Model Intercomparison Project (CMIP6). Applications using atmospheric δ13CO2 and Δ14CO2 observations in carbon cycle science and many other fields will be affected by these future changes. We recommend an increased effort toward making coordinated measurements of δ13C and Δ14C across the Earth System and for further development of isotopic modeling and model-data analysis tools. ©2020. American Geophysical Union. All Rights Reserved.

Headwater streams are important in the carbon cycle and there is a need to better parametrize and quantify exchange of carbon-relevant gases. Thus, we characterized variability in the gas exchange coefficient (k2) and dissolved oxygen (O2) gas transfer velocity (k) in two lowland headwaters of the River Avon (UK). The traditional one-station open-water method was complemented by in situ quantification of riverine sources and sinks of O2 (i.e., groundwater inflow, photosynthesis, and respiration in both the water column and benthic compartment) enabling direct hourly estimates of k2 at the reach–scale (~ 150 m) without relying on the nighttime regression method. Obtained k2 values ranged from 0.001 h−1 to 0.600 h−1. Average daytime k2 were a factor two higher than values at night, likely due to diel changes in water temperature and wind. Temperature contributed up to 46% of the variability in k on an hourly scale, but clustering temperature incrementally strengthened the statistical relationship. Our analysis suggested that k variability is aligned with dominant temperature trends rather than with short-term changes. Similarly, wind correlation with k increased when clustering wind speeds in increments correspondent with dominant variations (1 m s−1). Time scale is thus an important consideration when resolving physical drivers of gas exchange. Mean estimates of k600 from recent parametrizations proposed for upscaling, when applied to the settings of this study, were found to be in agreement with our independent O2 budget assessment (within < 10%), adding further support to the validity of upscaling efforts aiming at quantifying large-scale riverine gas emissions.

We estimated monthly air-sea CO2 fluxes in the Arctic Ocean and its adjacent seas north of 60 degrees N from 1997 to 2014. This was done by mapping partial pressure of CO2 in the surface water (pCO(2w)) using a self-organizing map (SOM) technique incorporating chlorophyll a concentration (Chl a), sea surface temperature, sea surface salinity, sea ice concentration, atmospheric CO2 mixing ratio, and geographical position. We applied new algorithms for extracting Chl a from satellite remote sensing reflectance with close examination of uncertainty of the obtained Chl a values. The overall relationship between pCO(2w) and Chl a was negative, whereas the relationship varied among seasons and regions. The addition of Chl a as a parameter in the SOM process enabled us to improve the estimate of pCO(2w), particularly via better representation of its decline in spring, which resulted from biologically mediated pCO(2w) reduction. As a result of the inclusion of Chl a, the uncertainty in the CO2 flux estimate was reduced, with a net annual Arctic Ocean CO2 uptake of 180 +/- 130 TgCyr(-1). Seasonal to interannual variation in the CO2 influx was also calculated.

Ground-based atmospheric observations of CO2, δ(O2∕N2), N2O, and CH4 were used to make estimates of the air–sea fluxes of these species from the Lüderitz and Walvis Bay upwelling cells in the northern Benguela region, during upwelling events. Average flux densities (±1σ) were 0.65±0.4 µmol m−2 s−1 for CO2, -5.1±2.5 µmol m−2 s−1 for O2 (as APO), 0.61±0.5 nmol m−2 s−1 for N2O, and 4.8±6.3 nmol m−2 s−1 for CH4. A comparison of our top-down (i.e., inferred from atmospheric anomalies) flux estimates with shipboard-based measurements showed that the two approaches agreed within ±55 % on average, though the degree of agreement varied by species and was best for CO2. Since the top-down method overestimated the flux density relative to the shipboard-based approach for all species, we also present flux density estimates that have been tuned to best match the shipboard fluxes. During the study, upwelling events were sources of CO2, N2O, and CH4 to the atmosphere. N2O fluxes were fairly low, in accordance with previous work suggesting that the evasion of this gas from the Benguela is smaller than for other eastern boundary upwelling systems (EBUS). Conversely, CH4 release was quite high for the marine environment, a result that supports studies that indicated a large sedimentary source of CH4 in the Walvis Bay area. These results demonstrate the suitability of atmospheric time series for characterizing the temporal variability of upwelling events and their influence on the overall marine greenhouse gas (GHG) emissions from the northern Benguela region.

Aerosol principal sources and sinks over eastern North Atlantic waters were studied through the deployment of an aerosol chemistry gradient sampling system. The chemical gradients of primary and secondary aerosol components – specifically, sea salt (SS), water-insoluble organic matter (WIOM), water-soluble organic matter (WSOM), nitrate, ammonium, oxalate, amines, methanesulfonic acid (MSA) and water-soluble organic nitrogen (WSON) – were examined in great detail. Sea salt fluxes were estimated by the boundary layer box model and ranged from 0.3 to 3.5 ng m−2 s−1 over the wind speed range of 5–12 m s−1 and compared well with the derived fluxes from existing sea salt source parameterisations. The observed seasonal pattern of sea salt gradients was mainly driven by wind stress in addition to the yet unquantified effect of marine OM modifying fractional contributions of SS and OM in sea spray. WIOM gradients were a complex combination of rising and waning biological activity, especially in the flux footprint area, and wind-driven primary sea spray production supporting the coupling of recently developed sea spray and marine OM parameterisations.

International audience; Gas exchange across the air–water interface is a key process determining the release of greenhouse gases from surface waters and a fundamental component of gas dynamics in aquatic systems. To experimentally quantify the gas transfer velocity in a wide range of aquatic settings, a novel method based on recently developed techniques for the in situ, near-continuous measurement of dissolved (noble) gases with a field portable mass spectrometer is presented. Variations in observed dissolved gas concentrations are damped and lagged with respect to equilibrium concentrations, being the result of (a) temperature (and thus solubility) variations, (b) water depth, and (c) the specific gas transfer velocity (ki). The method fits a model to the measured gas concentrations to derive the gas transfer velocity from the amplitude and the phase lag between observed and equilibrium concentrations. With the current experimental setup, the method is sensitive to gas transfer velocities of 0.05–9 m/day (for N2), at a water depth of 1 m, and a given daily water temperature variation of 10 °C. Experiments were performed (a) in a controlled experiment to prove the concept and to confirm the capability to determine low transfer velocities and (b) in a field study in a shallow coastal lagoon covering a range of transfer velocities, demonstrating the field applicability of the method.

Parameterisation of the air–sea gas transfer velocity of CO2 and other trace gases under open-ocean conditions has been a focus of air–sea interaction research and is required for accurately determining ocean carbon uptake. Ships are the most widely used platform for air–sea flux measurements but the quality of the data can be compromised by airflow distortion and sensor cross-sensitivity effects. Recent improvements in the understanding of these effects have led to enhanced corrections to the shipboard eddy covariance (EC) measurements.Here, we present a revised analysis of eddy covariance measurements of air–sea CO2 and momentum fluxes from the Southern Ocean Surface Ocean Aerosol Production (SOAP) study. We show that it is possible to significantly reduce the scatter in the EC data and achieve consistency between measurements taken on station and with the ship underway. The gas transfer velocities from the EC measurements correlate better with the EC friction velocity (u*) than with mean wind speeds derived from shipboard measurements corrected with an airflow distortion model. For the observed range of wind speeds (u10 N = 3–23 m s−1), the transfer velocities can be parameterised with a linear fit to u*. The SOAP data are compared to previous gas transfer parameterisations using u10 N computed from the EC friction velocity with the drag coefficient from the Coupled Ocean–Atmosphere Response Experiment (COARE) model version 3.5. The SOAP results are consistent with previous gas transfer studies, but at high wind speeds they do not support the sharp increase in gas transfer associated with bubble-mediated transfer predicted by physically based models.

Minimising the uncertainties in estimates of air-sea CO2 exchange is an important step toward increasing the confidence in assessments of the CO2 cycle. Using an atmospheric transport model makes it possible to investigate the direct impact of atmospheric parameters on the air-sea CO2 flux along with its sensitivity to, for example, short-term temporal variability in wind speed, atmospheric mixing height and atmospheric CO2 concentration. With this study, the importance of high spatiotemporal resolution of atmospheric parameters for the air-sea CO2 flux is assessed for six sub-basins within the Baltic Sea and Danish inner waters. A new climatology of surface water partial pressure of CO2 (pCO(2)(w)) has been developed for this coastal area based on available data from monitoring stations and on-board pCO(2)(w) measuring systems. Parameterisations depending on wind speed were applied for the transfer velocity to calculate the air-sea CO2 flux. Two model simulations were conducted - one including short-term variability in atmospheric CO2 (VAT), and one where it was not included (CAT).A seasonal cycle in the air-sea CO2 flux was found for both simulations for all sub-basins with uptake of CO2 in summer and release of CO2 to the atmosphere in winter. During the simulated period 2005-2010, the average annual net uptake of atmospheric CO2 for the Baltic Sea, Danish straits and Kattegat was 287 and 471 Gg C yr(-1) for the VAT and CAT simulations, respectively. The obtained difference of 184 Gg C yr(-1) was found to be significant, and thus ignoring short-term variability in atmospheric CO2 does have a sizeable effect on the air-sea CO2 exchange. The combination of the atmospheric model and the new pCO(2)(w) fields has also made it possible to make an estimate of the marine part of the Danish CO2 budget for the first time. A net annual uptake of 2613 Gg C yr(-1) was found for the Danish waters.A large uncertainty is connected to the air-sea CO2 flux in particular caused by the transfer velocity parameterisation and the applied pCO(2)(w) climatology. However, as a significant difference of 184 Gg C yr(-1) is obtained between the VAT and CAT simulations, the present study underlines the importance of including short-term variability in atmospheric CO2 concentration in future model studies of the air-sea exchange in order to minimise the uncertainty.

Minimising the uncertainties in estimates of air–sea CO2 exchange is an important step toward increasing the confidence in assessments of the CO2 cycle. Using an atmospheric transport model makes it possible to investigate the direct impact of atmospheric parameters on the air–sea CO2 flux along with its sensitivity to, for example, short-term temporal variability in wind speed, atmospheric mixing height and atmospheric CO2 concentration. With this study, the importance of high spatiotemporal resolution of atmospheric parameters for the air–sea CO2 flux is assessed for six sub-basins within the Baltic Sea and Danish inner waters. A new climatology of surface water partial pressure of CO2 (pCO2w) has been developed for this coastal area based on available data from monitoring stations and on-board pCO2w measuring systems. Parameterisations depending on wind speed were applied for the transfer velocity to calculate the air–sea CO2 flux. Two model simulations were conducted – one including short-term variability in atmospheric CO2 (VAT), and one where it was not included (CAT). A seasonal cycle in the air–sea CO2 flux was found for both simulations for all sub-basins with uptake of CO2 in summer and release of CO2 to the atmosphere in winter. During the simulated period 2005–2010, the average annual net uptake of atmospheric CO2 for the Baltic Sea, Danish straits and Kattegat was 287 and 471 Gg C yr−1 for the VAT and CAT simulations, respectively. The obtained difference of 184 Gg C yr−1 was found to be significant, and thus ignoring short-term variability in atmospheric CO2 does have a sizeable effect on the air–sea CO2 exchange. The combination of the atmospheric model and the new pCO2w fields has also made it possible to make an estimate of the marine part of the Danish CO2 budget for the first time. A net annual uptake of 2613 Gg C yr−1 was found for the Danish waters. A large uncertainty is connected to the air–sea CO2 flux in particular caused by the transfer velocity parameterisation and the applied pCO2w climatology. However, as a significant difference of 184 Gg C yr−1 is obtained between the VAT and CAT simulations, the present study underlines the importance of including short-term variability in atmospheric CO2 concentration in future model studies of the air–sea exchange in order to minimise the uncertainty.

We estimated monthly air–sea CO2 fluxes in the Arctic Ocean and its adjacent seas north of 60∘ N from 1997 to 2014. This was done by mapping partial pressure of CO2 in the surface water (pCO2w) using a self-organizing map (SOM) technique incorporating chlorophyll a concentration (Chl a), sea surface temperature, sea surface salinity, sea ice concentration, atmospheric CO2 mixing ratio, and geographical position. We applied new algorithms for extracting Chl a from satellite remote sensing reflectance with close examination of uncertainty of the obtained Chl a values. The overall relationship between pCO2w and Chl a was negative, whereas the relationship varied among seasons and regions. The addition of Chl a as a parameter in the SOM process enabled us to improve the estimate of pCO2w, particularly via better representation of its decline in spring, which resulted from biologically mediated pCO2w reduction. As a result of the inclusion of Chl a, the uncertainty in the CO2 flux estimate was reduced, with a net annual Arctic Ocean CO2 uptake of 180 ± 130 Tg C yr−1. Seasonal to interannual variation in the CO2 influx was also calculated.

Shallow lakes are a key component of the global carbon cycle. It is, therefore, important to know how shallow lake ecosystems will respond to the current climate change. Global warming affects not only average temperatures, but also the frequency of heat waves (HW). The impact of extreme events on ecosystems processes, particularly greenhouse gas (GHG) emissions, is uncertain. Using the world's longest-running shallow lake experiment, we studied the effects of a simulated summer HW on the fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O). The experimental mesocosms had been exposed to different temperature treatments and nutrient loading for 11years prior to the artificial HW. In general, there was an increase in total GHG emissions during the 1-month artificial HW, with a significant increase in CO2, CH4 and N2O being observed in the shallow lake mesocosms. No significant effect of the HW on CO2 emissions could be traced, though, in the mesocosms with high nutrient levels. Furthermore, the data suggested that in addition to the direct effect of increased temperature on metabolic processes during the HW, biotic interactions exerted a significant control of GHG emissions. For example, at low nutrient levels, increased CO2 emissions were associated with low macrophyte abundance, whereas at high nutrient levels, decreased phytoplankton abundance was linked to increased emissions of CO2 and CH4. In contrast to the observable heat-wave effect, no clear general effect of the long-term temperature treatments could be discerned over the summer, likely because the potential effects of the moderate temperature increase, applied as a press disturbance, were overridden by biotic interactions. This study demonstrates that the role of biotic interactions needs to be considered within the context of global warming on ecosystem processes.

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.

The exploitation of global navigation satellite systems Earth-reflected signals to perform ocean mesoscale altimetry from space has been originally proposed at the beginning of the 1990s. This technique is generally defined as “GNSS-R.” Since then, the versatility and availability of the GNSS-R has been the subject of studies targeting many other earth remote sensing applications, for both ocean and land. GNSS-R observables (called GNSS-R “waveforms”) are typically obtained by performing a complex cross-correlation of the received GNSS reflected signals with a locally generated replica of one of the open access GNSS signals, evaluated over a pre-defined set of delays of the local replica. The knowledge of the statistical properties of GNSS-R waveforms is of fundamental importance in order to define the retrieval algorithms to estimate the geophysical parameters and in order to optimize the accuracy of these estimations. The statistical properties of interest are mainly: 1) the correlation between realizations of GNSS-R waveforms generated at different time instants (generally defined as slow-time correlation) and 2) the correlation between the different delay samples of a given GNSS-R waveform (generally defined as fast-time or sample-to-sample correlation). The modeling and analysis of the slow-time statistical properties has been the subject of previous works. On the other hand, this paper presents for the first time a detailed analytical model describing the sample-to-sample statistics of GNSS-R waveforms. The model has been validated with real measurements of global positioning systems (GPSs) reflected signals collected by UK-DMC receiver, showing excellent agreement with the observations from space. The model is generic and can be easily extended to GNSS-R waveforms from other systems. For altimetry applications, the knowledge of waveform statistics allows to assess the dependence of altimetry performance on critical system/instrument and retrieval parameters such as the sampling frequency, the receiver bandwidth or signal-to-noise-ratio (SNR). This paper also presents an analysis of the impact of these parameters on instrument performance, the conclusions of which are general and constitute an important basis for optimization of future GNSS-R instruments.

Eddy covariance measurements of air–sea CO2 fluxes can be affected by cross-sensitivities of the CO2 measurement to water vapour, resulting in order-of-magnitude biases. Well-established causes for these biases are (i) cross-sensitivity of the broadband non-dispersive infrared sensors due to band-broadening and spectral overlap (commercial sensors typically correct for this) and (ii) the effect of air density fluctuations (removed by determining the dry air CO2 mixing ratio). Another bias related to water vapour fluctuations has recently been observed with open-path sensors, attributed to sea salt build-up and water films on sensor optics. Two very different approaches have been used to deal with these water vapour-related biases. Miller et al. (2010) employed a membrane drier to physically eliminate 97% of the water vapour fluctuations in the sample air before it entered a closed-path gas analyser. Prytherch et al. (2010a) employed the empirical (Peter K. Taylor, PKT) post-processing correction to correct open-path sensor data. In this paper, we test these methods side by side using data from the Surface Ocean Aerosol Production (SOAP) experiment in the Southern Ocean. The air–sea CO2 flux was directly measured with four closed-path analysers, two of which were positioned down-stream of a membrane dryer. The CO2 fluxes from the two dried gas analysers matched each other and were in general agreement with common parameterisations. The flux estimates from the un-dried sensors agreed with the dried sensors only during periods with low latent heat flux (&leq;7 W m−2). When latent heat flux was higher, CO2 flux estimates from the un-dried sensors exhibited large scatter and an order-of-magnitude bias. Applying the PKT correction to the flux data from the un-dried analysers did not remove the bias when compared to the data from the dried gas analyser. The results of this study demonstrate the validity of measuring CO2 fluxes using a pre-dried air stream and show that the PKT correction is not valid for the correction of CO2 fluxes.

[1] Since the 1980s, a dramatic downward trend in North African dustiness and transport to the tropical Atlantic Ocean has been observed by different data sets and methods. The precise causes of this trend have previously been difficult to understand, partly due to the sparse observational record. Here we show that a decrease in surface wind speeds associated with increased roughness due to more vegetation in the Sahel is the most likely cause of the observed drop in dust emission. Associated changes in turbulence and evapotranspiration, and changes in large-scale circulation, are secondary contributors. Past work has tried to explain negative correlations between North African dust and precipitation through impacts on emission thresholds due to changes in soil moisture and vegetation cover. The use of novel diagnostic tools applied here to long-term surface observations suggests that this is not the dominating effect. Our results are consistent with a recently observed global decrease in surface wind speed, known as “stilling”, and demonstrate the importance of representing vegetation-related roughness changes in models. They also offer a new mechanism of how land-use change and agriculture can impact the Sahelian climate. Citation: Cowie, S. M., P. Knippertz, and J. H. Marsham (2013), Are vegetation-related roughness changes the cause of the recent decrease in dust emission from the Sahel?, Geophys. Res. Lett., 40, 1868–1872, doi:10.1002/grl.50273

We performed measurements of carbon dioxide fugacity (fCO(2)) in the surface water under Arctic sea ice from January to June 2015 during the Norwegian young sea ICE (N-ICE2015) expedition. Over this period, the ship drifted with four different ice floes and covered the deep Nansen Basin, the slopes north of Svalbard, and the Yermak Plateau. This unique winter-to-spring data set includes the first winter-time under-ice water fCO(2) observations in this region. The observed under-ice fCO(2) ranged between 315 mu atm in winter and 153 mu atm in spring, hence was undersaturated relative to the atmospheric fCO(2). Although the sea ice partly prevented direct CO2 exchange between ocean and atmosphere, frequently occurring leads and breakup of the ice sheet promoted sea-air CO2 fluxes. The CO2 sink varied between 0.3 and 86 mmol C m(-2) d(-1), depending strongly on the open-water fractions (OW) and storm events. The maximum sea-air CO2 fluxes occurred during storm events in February and June. In winter, the main drivers of the change in under-ice water fCO(2) were dissolution of CaCO3 (ikaite) and vertical mixing. In June, in addition to these processes, primary production and sea-air CO2 fluxes were important. The cumulative loss due to CaCO3 dissolution of 0.7 mol C m(-2) in the upper 10 m played a major role in sustaining the undersaturation of fCO(2) during the entire study. The relative effects of the total fCO(2) change due to CaCO3 dissolution was 38%, primary production 26%, vertical mixing 16%, sea-air CO2 fluxes 16%, and temperature and salinity insignificant.

The air-sea gas transfer velocity k is frequently estimated as an empirical function of wind speed. However, it is widely recognized that k depends on processes other than wind speed alone. The small-eddy model, which describes periodic events of small eddies disturbing the sea surface with water from below, suggests a direct relation between k and the dissipation rate of turbulent kinetic energy at the air-sea interface. This relation has been proven both in laboratories and in the field in various freshwater and coastal environments, but to date has not been verified in open ocean conditions. Here, concurrent North Atlantic field observations of and eddy covariance measurements of DMS and CO2 air-sea gas flux are presented. Using measurements, we compare the small-eddy model at various depths to previously published observations. Extrapolating the measured profiles to the thickness of the viscous sublayer allows us to formulate a function of k that depends solely on the water side friction velocity uw , which can be inferred from direct eddy covariance measurements of the air-side friction velocity ua . These field observations are generally consistent with the theoretical small-eddy model. Utilizing a variable Schmidt number exponent in the model, rather than a constant value of 1 2 yields improved agreement between model and observations. This research was originally published in Journal of Geophysical Research: Oceans. © 2017 Wiley

The objective of the study is to provide global grids (0.5°) of revised annual coefficients for the Priestley–Taylor (P-T) and Hargreaves–Samani (H-S) evapotranspiration methods after calibration based on the ASCE (American Society of Civil Engineers)-standardized Penman–Monteith method (the ASCE method includes two reference crops: short-clipped grass and tall alfalfa). The analysis also includes the development of a global grid of revised annual coefficients for solar radiation (Rs) estimations using the respective Rs formula of H-S. The analysis was based on global gridded climatic data of the period 1950–2000. The method for deriving annual coefficients of the P-T and H-S methods was based on partial weighted averages (PWAs) of their mean monthly values. This method estimates the annual values considering the amplitude of the parameter under investigation (ETo and Rs) giving more weight to the monthly coefficients of the months with higher ETo values (or Rs values for the case of the H-S radiation formula). The method also eliminates the effect of unreasonably high or low monthly coefficients that may occur during periods where ETo and Rs fall below a specific threshold. The new coefficients were validated based on data from 140 stations located in various climatic zones of the USA and Australia with expanded observations up to 2016. The validation procedure for ETo estimations of the short reference crop showed that the P-T and H-S methods with the new revised coefficients outperformed the standard methods reducing the estimated root mean square error (RMSE) in ETo values by 40 and 25 %, respectively. The estimations of Rs using the H-S formula with revised coefficients reduced the RMSE by 28 % in comparison to the standard H-S formula. Finally, a raster database was built consisting of (a) global maps for the mean monthly ETo values estimated by ASCE-standardized method for both reference crops, (b) global maps for the revised annual coefficients of the P-T and H-S evapotranspiration methods for both reference crops and a global map for the revised annual coefficient of the H-S radiation formula and (c) global maps that indicate the optimum locations for using the standard P-T and H-S methods and their possible annual errors based on reference values. The database can support estimations of ETo and solar radiation for locations where climatic data are limited and it can support studies which require such estimations on larger scales (e.g. country, continent, world). The datasets produced in this study are archived in the PANGAEA database (https://doi.org/10.1594/PANGAEA.868808) and in the ESRN database (http://www.esrn-database.org or http://esrn-database.weebly.com).

The Ocean Model Intercomparison Project (OMIP) focuses on the physics and biogeochemistry of the ocean component of Earth system models participating in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). OMIP aims to provide standard protocols and diagnostics for ocean models, while offering a forum to promote their common assessment and improvement. It also offers to compare solutions of the same ocean models when forced with reanalysis data (OMIP simulations) vs. when integrated within fully coupled Earth system models (CMIP6). Here we detail simulation protocols and diagnostics for OMIP's biogeochemical and inert chemical tracers. These passive-tracer simulations will be coupled to ocean circulation models, initialized with observational data or output from a model spin-up, and forced by repeating the 1948–2009 surface fluxes of heat, fresh water, and momentum. These so-called OMIP-BGC simulations include three inert chemical tracers (CFC-11, CFC-12, SF6) and biogeochemical tracers (e.g., dissolved inorganic carbon, carbon isotopes, alkalinity, nutrients, and oxygen). Modelers will use their preferred prognostic BGC model but should follow common guidelines for gas exchange and carbonate chemistry. Simulations include both natural and total carbon tracers. The required forced simulation (omip1) will be initialized with gridded observational climatologies. An optional forced simulation (omip1-spunup) will be initialized instead with BGC fields from a long model spin-up, preferably for 2000 years or more, and forced by repeating the same 62-year meteorological forcing. That optional run will also include abiotic tracers of total dissolved inorganic carbon and radiocarbon, CTabio and 14CTabio, to assess deep-ocean ventilation and distinguish the role of physics vs. biology. These simulations will be forced by observed atmospheric histories of the three inert gases and CO2 as well as carbon isotope ratios of CO2. OMIP-BGC simulation protocols are founded on those from previous phases of the Ocean Carbon-Cycle Model Intercomparison Project. They have been merged and updated to reflect improvements concerning gas exchange, carbonate chemistry, and new data for initial conditions and atmospheric gas histories. Code is provided to facilitate their implementation.

Ammonia (NH3) emission from animal manure contributes to air pollution and ecosystem degradation, and the loss of reactive nitrogen (N) from agricultural systems. Estimates of NH3 emission are necessary for national inventories and nutrient management, and NH3 emission from field-applied manure has been measured in many studies over the past few decades. In this work, we facilitate the use of these data by collecting and organizing them in the ALFAM2 database. In this paper we describe the development of the database and summarise its contents, quantify effects of application methods and other variables on emission using a data subset, and discuss challenges for data analysis and model development. The database contains measurements of emission, manure and soil properties, weather, application technique, and other variables for 1895 plots from 22 research institutes in 12 countries. Data on five manure types (cattle, pig, mink, poultry, mixed, as well as sludge and “other”) applied to three types of crops (grass, small grains, maize, as well as stubble and bare soil) are included. Application methods represented in the database include broadcast, trailing hose, trailing shoe (narrow band application), and open slot injection. Cattle manure application to grassland was the most common combination, and analysis of this subset (with dry matter (DM) limited to

A parameterization for the deposition velocity of an ocean-reactive atmospheric gas (such as ozone) is developed. The parameterization is based on integration of the turbulent-molecular transport equation (with a chemical source term) in the ocean. It extends previous work that only considered reactions within the oceanic molecular sublayer. The sensitivity of the ocean-side transport to reaction rate and wind forcing is examined. A more complicated case with a much more reactive thin surfactant layer is also considered. The full atmosphere-ocean deposition velocity is obtained by matching boundary conditions at the interface. For an assumed ocean reaction rate of 103 s¿1, the enhancement for ozone deposition by oceanic turbulence is found to be up to a factor of three for meteorological data obtained in a recent cruise off the East Coast of the U.S.

Relationships were developed to predict ammonia (NH3) nitrogen losses from cattle manure in animal housing, during manure storage, following field application, and during grazing. Ammonia loss in each phase was predicted using a mechanistic model for NH3 volatilized from the surface of an aqueous solution of ammonium where the NH3 is transported to the free atmosphere through a pathway with finite resistance. Ammonia emission rate was a function of the ammoniacal N content in the manure, ambient temperature, manure pH, manure moisture content, and the exposed manure surface area. Model relationships were calibrated by selecting values for the resistance to NH3 transport for the various loss pathways, which predicted daily and annual emissions similar to those reported in published studies. In further evaluation, these calibrated relationships predicted average annual losses similar to those documented in previous work over a range in climate locations. These relationships were integrated into a whole-farm simulation model to provide a tool for evaluating and comparing long-term nitrogen losses along with other performance, environmental, and economic aspects of farm production. Whole-farm simulations illustrated that the use of a free stall barn, bottom-loaded slurry storage, and direct injection of manure into the soil reduced NH3 emissions by 33% to 50% compared to other commonly used dairy housing and manure handling systems in the northeastern U.S. The improvement in nitrogen utilization more than offset the increased cost in manure handling, providing a small increase in farm profit. The farm model provides a research and teaching tool for evaluating and comparing the economic and environmental sustainability of dairy and beef production systems.

[1] Gas transfer rates were determined from vertical profile measurements of atmospheric dimethylsulfide (DMS) gradients over the equatorial Pacific Ocean obtained during the GasEx-2001 cruise. A quadratic relationship between gas transfer velocity and wind speed was derived from the DMS flux measurements; this relationship was in close agreement with a parameterization derived from relaxed eddy accumulation measurements of DMS over the northeastern Pacific Ocean. However, the GasEx-2001 relationship results in gas transfer rates that are a factor 2 higher than gas transfer rates calculated from a parameterization that is based on coincident eddy correlation measurements of CO2 flux. The measurement precision of both the profiling and eddy correlation techniques applied during GasEx-2001 is comparable; the two gas transfer data sets are in agreement within their uncertainty. Differences in the number of samples and the wind speed range over which CO2 and DMS fluxes were measured are likely causes for the observed discrepancy.

A new sea spray source function (SSSF), termed Oceanflux Sea Spray Aerosol or OSSA, was derived based on in-situ sea spray aerosol measurements along with meteorological/physical parameters. Submicron sea spray aerosol fluxes derived from particle number concentration measurements at the Mace Head coastal station, on the west coast of Ireland, were used together with open-ocean eddy correlation flux measurements from the Eastern Atlantic Sea Spray, Gas Flux, and Whitecap (SEASAW) project cruise. In the overlapping size range, the data for Mace Head and SEASAW were found to be in a good agreement, which allowed deriving the new SSSF from the combined dataset spanning the dry diameter range from 15 nm to 6 μm. The OSSA source function has been parameterized in terms of five lognormal modes and the Reynolds number instead of the more commonly used wind speed, thereby encapsulating important influences of wave height, wind history, friction velocity, and viscosity. This formulation accounts for the different flux relationships associated with rising and waning wind speeds since these are included in the Reynolds number. Furthermore, the Reynolds number incorporates the kinematic viscosity of water, thus the SSSF inherently includes dependences on sea surface temperature and salinity. The temperature dependence of the resulting SSSF is similar to that of other in-situ derived source functions and results in lower production fluxes for cold waters and enhanced fluxes from warm waters as compared with SSSF formulations that do not include temperature effects.

Lakes and other inland waters contribute significantly to regional and global carbon budgets. Emissions from lakes are often computed as the product of a gas transfer coefficient, k 600 , and the difference in concentration across the diffusive boundary layer at the air–water interface. Eddy covariance (EC) techniques are increasingly being used in lacustrine gas flux studies and tend to report higher values for derived k 600 than other approaches. Using results from an EC study of a small, boreal lake, we modelled k 600 using a boundary-layer approach that included wind shear and cooling. During stratification, fluxes estimated by EC occasionally were higher than those obtained by our models. The high fluxes co-occurred with winds strong enough to induce deflections of the thermocline. We attribute the higher measured fluxes to upwelling-induced spatial variability in surface concentrations of CO 2 within the EC footprint. We modelled the increased gas concentrations due to the upwelling and corrected our k 600 values using these higher CO 2 concentrations. This approach led to greater congruence between measured and modelled k values during the stratified period. k 600 has a well-resolved and ~cubic relationship with wind speed when the water column is unstratified and the dissolved gases well mixed. During stratification and using the corrected k 600 , the same pattern is evident at higher winds, but k 600 has a median value of ~7 cm h −1 when winds are less than 6 m s −1 , similar to observations in recent oceanographic studies. Our models for k 600 provide estimates of gas evasion at least 200% higher than earlier wind-based models. Our improved k 600 estimates emphasize the need for integrating within lake physics into models of greenhouse gas evasion. Keywords: carbon dioxide, gas transfer, upwelling, eddy covariance, heat flux, thermocline tilting (Published: 19 May 2014) Citation: Tellus B 2014, 66 , 22827, http://dx.doi.org/10.3402/tellusb.v66.22827

Simultaneous measurements of near-surface aerosol (0.12 < R < 9.25 μm) and bubble spectra (13 < R < 620 μm) were made during five buoy deployments in the open ocean of the North Atlantic and used to estimate aerosol fluxes per unit area of whitecap. The measurements were made during two cruises as part of the Sea Spray, Gas Flux, and Whitecaps (SEASAW) project, a UK contribution to the international Surface Ocean Lower Atmosphere Study (SOLAS) program. The mean bubble number concentrations for each deployment are in broad agreement with other open ocean spectra and are consistently one to two orders of magnitude lower than surf zone studies. Production fluxes per unit area of whitecap are estimated from the mean aerosol concentration for each buoy deployment. They are found to increase with wind speed, and span the range of values found by previous laboratory and surf-zone studies for particles with radius at 80% relative humidity, R80 < 1 μm, but to drop off more rapidly with increasing particle size for larger particles. Estimates of the mean sea spray flux were made by scaling the whitecap production fluxes with in situ estimates of whitecap fraction. The sea spray fluxes are also compared with simultaneous individual eddy covariance flux estimates, and with a sea spray source function derived from them.

Volatile halogenated organic compounds containing bromine and iodine, which are naturally produced in the ocean, are involved in ozone depletion in both the troposphere and stratosphere. Three prominent compounds transporting large amounts of marine halogens into the atmosphere are bromoform (CHBr3), dibromomethane (CH2Br2) and methyl iodide (CH3I). The input of marine halogens to the stratosphere has been estimated from observations and modelling studies using low-resolution oceanic emission scenarios derived from top-down approaches. In order to improve emission inventory estimates, we calculate data-based high resolution global sea-to-air flux estimates of these compounds from surface observations within the HalOcAt (Halocarbons in the Ocean and Atmosphere) database (https://halocat.geomar.de/). Global maps of marine and atmospheric surface concentrations are derived from the data which are divided into coastal, shelf and open ocean regions. Considering physical and biogeochemical characteristics of ocean and atmosphere, the open ocean water and atmosphere data are classified into 21 regions. The available data are interpolated onto a 1°×1° grid while missing grid values are interpolated with latitudinal and longitudinal dependent regression techniques reflecting the compounds' distributions. With the generated surface concentration climatologies for the ocean and atmosphere, global sea-to-air concentration gradients and sea-to-air fluxes are calculated. Based on these calculations we estimate a total global flux of 1.5/2.5 Gmol Br yr−1 for CHBr3, 0.78/0.98 Gmol Br yr−1 for CH2Br2 and 1.24/1.45 Gmol Br yr−1 for CH3I (robust fit/ordinary least squares regression techniques). Contrary to recent studies, negative fluxes occur in each sea-to-air flux climatology, mainly in the Arctic and Antarctic regions. "Hot spots" for global polybromomethane emissions are located in the equatorial region, whereas methyl iodide emissions are enhanced in the subtropical gyre regions. Inter-annual and seasonal variation is contained within our flux calculations for all three compounds. Compared to earlier studies, our global fluxes are at the lower end of estimates, especially for bromoform. An under-representation of coastal emissions and of extreme events in our estimate might explain the mismatch between our bottom-up emission estimate and top-down approaches.

Climate change and changing nutrient loadings are the two main aspects of global change that are linked to the increase in the prevalence of coastal hypoxia – the depletion of oxygen in the bottom waters of coastal areas. However, it remains uncertain how strongly these two drivers will each increase the risk of hypoxia over the next decades. Through model simulations we have investigated the relative influence of climate change and nutrient run-off on the bottom water oxygen dynamics in the Oyster Grounds, an area in the central North Sea experiencing summer stratification. Simulations were performed with a one-dimensional ecosystem model that couples hydrodynamics, pelagic biogeochemistry and sediment diagenesis. Climatological conditions for the North Sea over the next 100 yr were derived from a global-scale climate model. Our results indicate that changing climatological conditions will increase the risk of hypoxia. The bottom water oxygen concentration in late summer is predicted to decrease by 24 μM or 11.5% in the year 2100. More intense stratification is the dominant factor responsible for this decrease (58%), followed by the reduced solubility of oxygen at higher water temperature (27%), while the remaining part could be attributed to enhanced metabolic rates in warmer bottom waters (15%). Relative to these climate change effects, changes in nutrient runoff are also important and may even have a stronger impact on the bottom water oxygenation. Decreased nutrient loadings strongly decrease the probability of hypoxic events. This stresses the importance of continued eutrophication management in coastal areas, which could function as a mitigation tool to counteract the effects of rising temperatures.

[1] We simulate the generation and microphysical evolution of sea-salt aerosol using a climatologically driven 3-D microphysical model for the year 2006. We then apply Mie theory to calculate the extinction and scattering efficiencies of our transported, size-resolved sea-salt aerosol, accounting for hygroscopic growth due to changes in ambient relative humidity. We calculate the column optical thickness of our modeled sea-salt aerosol for comparison to three previously published wind speed–dependent clean marine air optical thickness formulations. Variously derived from optical thickness measurements and retrievals taken from the Midway Island AERONET site, the satellite-based MODIS instruments, and the Global Atmospheric Watch (GAW) site at Mace Head, Ireland, the three formulations report similar background levels of clean marine AOT at zero wind speed but significantly different functional dependencies for nonzero wind speeds. We find that our modeled sea-salt aerosol optical thickness very closely depends on the square of surface wind speed under steady state conditions. This relationship is consistent across all latitudes. However, due to the fact that steady state winds are seldom maintained, the 24 h mean wind is more frequently applicable to calculations of sea-salt AOT, with only slightly diminished accuracy.

As part of the U. K. contribution to the international Surface Ocean-Lower Atmosphere Study, a series of three related projects-DOGEE, SEASAW, and HiWASE-undertook experimental studies of the processes controlling the physical exchange of gases and sea spray aerosol at the sea surface. The studies share a common goal: to reduce the high degree of uncertainty in current parameterization schemes. The wide variety of measurements made during the studies, which incorporated tracer and surfactant release experiments, included direct eddy correlation fluxes, detailed wave spectra, wind history, photographic retrievals of whitecap fraction, aerosol-size spectra and composition, surfactant concentration, and bubble populations in the ocean mixed layer. Measurements were made during three cruises in the northeast Atlantic on the RRS Discovery during 2006 and 2007; a fourth campaign has been making continuous measurements on the Norwegian weather ship Polarfront since September 2006. This paper provides an overview of the three projects and some of the highlights of the measurement campaigns.

The effect of diurnal variations in sea surface temperature (SST) on the air-sea flux of CO2 over the central Atlantic ocean and Mediterranean Sea (60 S-60 N, 60 W-45 E) is evaluated for 2005-2006. We use high spatial resolution hourly satellite ocean skin temperature data to determine the diurnal warming (Delta SST). The CO2 flux is then computed using three different temperature fields - a foundation temperature (T-f, measured at a depth where there is no diurnal variation), T-f plus the hourly Delta SST and T-f plus the monthly average of the Delta SSTs. This is done in conjunction with a physically-based parameterisation for the gas transfer velocity (NOAA-COARE). The differences between the fluxes evaluated for these three different temperature fields quantify the effects of both diurnal warming and diurnal covariations. We find that including diurnal warming increases the CO2 flux out of this region of the Atlantic for 2005 2006 from 9.6 Tg C a(-1) to 30.4 Tg C a(-1) (hourly Delta SST) and 31.2 Tg C a(-1) (monthly average of Delta SST measurements). Diurnal warming in this region, therefore, has a large impact on the annual net CO2 flux but diurnal covariations are negligible. However, in this region of the Atlantic the uptake and outgassing of CO2 is approximately balanced over the annual cycle, so although we find diurnal warming has a very large effect here, the Atlantic as a whole is a very strong carbon sink (e. g. -920 Tg C a(-1) Takahashi et al., 2002) making this is a small contribution to the Atlantic carbon budget.

A parameterization for the deposition velocity of an ocean-reactive atmospheric gas (such as ozone) is developed. The parameterization is based on integration of the turbulent-molecular transport equation (with a chemical source term) in the ocean. It extends previous work that only considered reactions within the oceanic molecular sublayer. The sensitivity of the ocean-side transport to reaction rate and wind forcing is examined. A more complicated case with a much more reactive thin surfactant layer is also considered. The full atmosphere-ocean deposition velocity is obtained by matching boundary conditions at the interface. For an assumed ocean reaction rate of 103 s-1, the enhancement for ozone deposition by oceanic turbulence is found to be up to a factor of three for meteorological data obtained in a recent cruise off the East Coast of the U.S.