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Size-spectral approaches quantify the efficiency of energy transfer through food webs, but theory and field studies disagree over how changes in temperature, nutrients, and extreme weather impact on this efficiency. We address this at two scales: via 6 years of weekly sampling of the plankton size spectrum at the Plymouth L4 shelf sea site, and via a new, global-scale, meta-analysis of aquatic size spectra. The time series showed that with summertime nutrient starvation, the energy transfer efficiency from picoplankton to macroplankton decreased (i.e., steepening slopes of the size spectra). This reflected increasing dominance by small cells and their microbial consumers. The extreme storms in winter 2013/2014 caused high metazoan mortality, steep size-spectral slopes, and reduced plankton biomass. However, recovery was within months, demonstrating an inbuilt resilience of the system. Both L4 and our meta-analysis showed steep slopes of normalized size spectra (median −1.11). This reflects much lower values, either of trophic transfer efficiency (3.5%) or predator–prey mass ratio (569), compared to commonly quoted values. Results from the meta-analysis further showed that to represent energy transfer faithfully, size spectra are best constructed in units of carbon mass and not biovolume, and span a mass range of > 107. When this range is covered, both the meta-analysis and time series show a dome-shaped relationship between spectral slopes and plankton biomass, with steepening slopes under increasingly oligotrophic and eutrophic conditions. This suggests that ocean warming could decrease the efficiency of energy transfer through pelagic food webs via indirect effects of increasing stratification and nutrient starvation.

Shelf-seas play a key role in both the global carbon cycle and coastal marine ecosystems through the drawn-down and fixing of carbon, as measured through phytoplankton net primary production (NPP). Measuring NPP in situ, and extrapolating this to the local, regional and global scale presents challenges however because of limitations with the techniques utilised (e.g. radiocarbon isotopes), data sparsity and the inherent biogeochemical heterogeneity of coastal and open-shelf waters. Here, we introduce a powerful new technique based on the synergistic use of in situ glider profiles and satellite Earth Observation measurements which can be implemented in a real-time or delayed mode system. We apply this system to a fleet of gliders successively deployed over a 19-month time-frame in the North Sea, generating an unprecedented fine scale time-series of NPP in the region (Loveday and Smyth, 2020). At the large-scale, this time-series gives close agreement with existing satellite-based estimates of NPP for the region and previous in situ estimates. What has not been elucidated before is the high-frequency, small-scale, depth-resolved variability associated with bloom phenology, mesoscale phenomena and mixed layer dynamics.

The flux of CO2 between the atmosphere and the ocean is often estimated as the air–sea gas concentration difference multiplied by the gas transfer velocity (K660). The first order driver for K660 over the ocean is wind through its influence on near surface hydrodynamics. However, field observations have shown substantial variability in the wind speed dependencies of K660. In this study we measured K660 with the eddy covariance technique during a ~ 11,000 km long Southern Ocean transect. In parallel, we made a novel measurement of the gas transfer efficiency (GTE) based on partial equilibration of CO2 using a Segmented Flow Coil Equilibrator system. GTE varied by 20% during the transect, was distinct in different water masses, and related to K660. At a moderate wind speed of 7 m s−1, K660 associated with high GTE exceeded K660 with low GTE by 30% in the mean. The sensitivity of K660 towards GTE was stronger at lower wind speeds and weaker at higher wind speeds. Naturally-occurring organics in seawater, some of which are surface active, may be the cause of the variability in GTE and in K660. Neglecting these variations could result in biases in the computed air–sea CO2 fluxes.

The accurate representation of precipitation across the Earth’s surface is crucial to furthering our knowledge and understanding of the Earth System and its component processes. Precipitation poses a number of challenges, particularly due to the variability of precipitation over time and space and whether it falls as snow or rain. While conventional measures of precipitation are reasonably good at the location of their measurement, their distribution across the Earth’s surface is uneven with some regions having no surface measurements. Spaceborne sensors have the capability of providing regular observations across the Earth’s surface that can provide estimates of precipitation. However, the estimation of precipitation from satellite observations is not necessarily straightforward. Visible and/or infrared techniques rely upon imprecise cloud-top to surface precipitation relationships, while the sensitivity of passive microwave techniques to different precipitation types is not consistent. Active microwave (radar) observations provide the most direct satellite measurements of precipitation but cannot provide estimates close to the surface and are generally not sufficiently sensitive to resolve light precipitation. This is particularly problematic at mid to high latitudes, where light and/or shallow precipitation dominates. This paper compares measurements made by ground-based weather radars, Micro Rain Radars and the spaceborne Dual-frequency Precipitation Radar to study both light precipitation intensity and shallow precipitation occurrence and to assess their impact on satellites retrievals of precipitation at the mid to high latitudes.

Oceanography has entered an era of new observing platforms, such as biogeochemical-Argo floats and gliders, some of which will provide three-dimensional maps of essential ecosystem variables on the North-West European (NWE) Shelf. In a foreseeable future operational centers will use multi-platform assimilation to integrate those valuable data into ecosystem reanalysis and forecast systems. Here we address some important questions related to glider biogeochemical data assimilation (DA) and introduce multi-platform DA in a preoperational model of the NWE Shelf sea ecosystem. We test the impact of the different multi-platform system components (glider vs. satellite, physical vs. biogeochemical) on the simulated biogeochemical variables. To characterize the model performance, we focus on the period around the phytoplankton spring bloom, since the bloom is a major ecosystem driver on the NWE Shelf. We found that the timing and magnitude of the phytoplankton bloom is insensitive to the physical DA, which is explained in the study. To correct the simulated phytoplankton bloom one needs to assimilate chlorophyll observations from glider or satellite Ocean Color (OC) into the model. Although outperformed by the glider chlorophyll assimilation, we show that OC assimilation has mostly desirable impact on the sub-surface chlorophyll. Since the OC assimilation updates chlorophyll only in the mixed layer, the impact on the sub-surface chlorophyll is the result of the model dynamical response to the assimilation. We demonstrate that the multi-platform assimilation combines the advantages of its components and always performs comparably to its best performing component.

1. The increasing illumination of our world by artificial light at night (ALAN) has created a new field of global change research with impacts now being demonstrated across taxa, biological ranks and spatial scales. Following advances in terrestrial ecology, marine ALAN has become a rapidly growing research area attracting scientists from across all biomes. Technological limitations, complexities of researching many coastal and marine ecosystems and the interdisciplinary nature of ALAN research present numerous challenges. 2. Drawing on expertise from optical oceanographers, modellers, community ecologists, experimental and molecular biologists, we share practical advice and solutions that have proven useful for marine ALAN research. Discussing lessons learnt early on can help in the effective and efficient development of a field. 3. The guide follows a sensory ecology approach to marine light pollution and consolidates physics, ecology and biology. First, we introduce marine lightscapes highlighting how these differ from terrestrial ones and provide an overview of biological adaptations to them. Second, we discuss study design and technology to best quantify ALAN exposure of and impacts on marine and coastal organisms including molecular tools and approaches to scale-up marine ALAN research. 4. We conclude that the growing field of marine ALAN research presents opportunities not only for improving our understanding of this globally widespread stressor, but also for advancing fundamental marine photobiology, chronobiology and night-time ecology. Interdisciplinary research will be essential to gain insights into natural marine lightscapes shaping the ecology and evolution coastal and marine ecosystems.

Continental margins are disproportionally important for global primary production, fisheries and CO2 uptake. However, across the Northeast Atlantic shelves, there has been an ongoing summertime decline of key biota-large diatoms, dinoflagellates and copepods-that traditionally fuel higher tropic levels such as fish, sea birds and marine mammals. Here, we combine multiple time series with in situ process studies to link these declines to summer nutrient stress and increasing proportions of picophytoplankton that can comprise up to 90% of the combined pico- and nanophytoplankton biomass in coastal areas. Among the pico-fraction, it is the cyanobacterium Synechococcus that flourishes when iron and nitrogen resupply to surface waters are diminished. Our field data show how traits beyond small size give Synechococcus a competitive edge over pico- and nanoeukaryotes. Key is their ability to grow at low irradiances near the nutricline, which is aided by their superior light-harvesting system and high affinity to iron. However, minute size and lack of essential biomolecules (e.g. omega-3 polyunsaturated fatty acids and sterols) render Synechococcus poor primary producers to sustain shelf sea food webs efficiently. The combination of earlier spring blooms and lower summer food quantity and quality creates an increasing period of suboptimal feeding conditions for zooplankton at a time of year when their metabolic demand is highest. We suggest that this nutrition-related mismatch has contributed to the widespread, ~50% decline in summer copepod abundance we observe over the last 60 years. With Synechococcus clades being prominent from the tropics to the Arctic and their abundances increasing worldwide, our study informs projections of future food web dynamics in coastal and shelf areas where droughts and stratification lead to increasing nutrient starvation of surface waters.

Accelerating coastal development is increasing the exposure of marine ecosystems to nighttime light pollution, but is anthropogenic light reaching the seafloor in sufficient quantities to have ecological impacts? Using a combination of mapping, and radiative transfer modelling utilising in situ measurements of optical seawater properties, we quantified artificial light exposure at the sea surface, beneath the sea surface, and at the sea floor of an urbanised temperate estuary bordered by an LED lit city. Up to 76% of the three-dimensional seafloor area was exposed to biologically important light pollution. Exposure to green wavelengths was highest, while exposure to red wavelengths was nominal. We conclude that light pollution from coastal cities is likely having deleterious impacts on seafloor ecosystems which provide vital ecosystem services. A comprehensive understanding of these impacts is urgently needed.

This work evaluates the sensitivity of CO 2 air–sea gas exchange in a coastal site to four different model system configurations of the 1D coupled hydrodynamic–ecosystem model GOTM–ERSEM, towards identifying critical dynamics of relevance when specifically addressing quantification of air–sea CO 2 exchange. The European Sea Regional Ecosystem Model (ERSEM) is a biomass and functional group-based biogeochemical model that includes a comprehensive carbonate system and explicitly simulates the production of dissolved organic carbon, dissolved inorganic carbon and organic matter. The model was implemented at the coastal station L4 (4 nm south of Plymouth, 50°15.00’N, 4°13.02’W, depth of 51 m). The model performance was evaluated using more than 1500 hydrological and biochemical observations routinely collected at L4 through the Western Coastal Observatory activities of 2008—-2009. In addition to a reference simulation (A), we ran three distinct experiments to investigate the sensitivity of the carbonate system and modeled air–sea fluxes to (B) the sea-surface temperature (SST) diurnal cycle and thus also the near-surface vertical gradients, (C) biological suppression of gas exchange and (D) data assimilation using satellite Earth observation data. The reference simulation captures well the physical environment (simulated SST has a correlation with observations equal to 0.94 with a p> 0.95). Overall, the model captures the seasonal signal in most biogeochemical variables including the air–sea flux of CO 2 and primary production and can capture some of the intra-seasonal variability and short-lived blooms. The model correctly reproduces the seasonality of nutrients (correlation > 0.80 for silicate, nitrate and phosphate), surface chlorophyll-a (correlation > 0.43) and total biomass (correlation > 0.7) in a two year run for 2008–2009. The model simulates well the concentration of DIC, pH and in-water partial pressure of CO 2 (pCO 2 ) with correlations between 0.4–0.5. The model result suggest that L4 is a weak net source of CO 2 (0.3–1.8 molCm − 2 year − 1 ). The results of the three sensitivity experiments indicate that both resolving the temperature profile near the surface and assimilation of surface chlorophyll-a significantly impact the skill of simulating the biogeochemistry at L4 and all of the carbonate chemistry related variables. These results indicate that our forecasting ability of CO 2 air–sea flux in shelf seas environments and their impact in climate modeling should consider both model refinements as means of reducing uncertainties and errors in any future climate projections.

Phytoplankton phenology and the length of the growing season have implications that cascade through trophic levels and ultimately impact the global carbon flux to the seafloor. Coupled hydrodynamic‐ecosystem models must accurately predict timing and duration of phytoplankton blooms in order to predict the impact of environmental change on ecosystem dynamics. Meteorological conditions, such as solar irradiance, air temperature and wind‐speed are known to strongly impact the timing of phytoplankton blooms. Here, we investigate the impact of degrading the temporal resolution of meteorological forcing (wind, surface pressure, air and dew point temperatures) from 1‐24 hours using a 1D coupled hydrodynamic‐ecosystem model at two contrasting shelf‐sea sites: one coastal intermediately stratified site (L4) and one offshore site with constant summer stratification (CCS). Higher temporal resolutions of meteorological forcing resulted in greater wind stress acting on the sea surface increasing water column turbulent kinetic energy. Consequently, the water column was stratified for a smaller proportion of the year producing a delayed onset of the spring phytoplankton bloom by up to 6 days, often earlier cessation of the autumn bloom, and shortened growing season of up to 23 days. Despite opposing trends in gross primary production between sites, a weakened microbial loop occurred with higher meteorological resolution due to reduced dissolved organic carbon production by phytoplankton caused by differences in resource limitation: light at CCS and nitrate at L4. Caution should be taken when comparing model runs with differing meteorological forcing resolutions. Recalibration of hydrodynamic‐ecosystem models may be required if meteorological resolution is upgraded. Plain Language Summary Computer models are used to predict the impact of changes in environmental pressures such as climate change on marine ecosystems. To predict these changes models need to accurately simulate the period when marine plants (phytoplankton) grow rapidly, termed the phytoplankton bloom, as these plants act as a food source to the marine food‐chain. The models are run by defining meteorological variables, such as light, air temperature and wind speed which are known to strongly impact the timing of phytoplankton blooms. In this paper we investigate the impact in changing the time period between inputs of meteorological variables from 1 hour to 24 hours at two contrasting marine sites. The shorter the timespan between inputs, the more fluctuations in wind speed, resulting in increased wind stress acting on the sea surface and therefore greater turbulence and mixing within the water column. Consequently the predicted length of growing season is reduced with the spring phytoplankton bloom starting up to 6 days later and the autumn bloom often terminating earlier. Implications for ecosystem function are site dependent. Caution should be taken when comparing model results using different time gaps of meteorological inputs and models may need retuning if upgraded to hourly meteorological inputs.

We present a detailed analysis of long-term aerosol measurements from four sun photometer sites (from west to east: Plymouth, Chilbolton, Dunkirk, Oostende) and four Department for Environment, Food & Rural Affairs surface sites (from west to east: Plymouth, Southampton, Portsmouth, Eastbourne) near the English Channel. From the early 2000s to about 2016, annual mean Aerosol Optical Depth (AOD) from all sun photometer sites decreased by an overall average of 23% decade-1 (range of 15–28% decade-1). From 2010 to 2017, annual mean concentration of particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5) from all the surface sites decreased by an overall average of 44% decade-1 (range of 7–64% decade-1). Seasonally, the highest aerosol loading is generally found around the springtime, and this maximum has been decreasing much faster over recent years than during the other seasons. This is driven by the interaction between the seasonal weather patterns (e.g. reduced westerly flow and drier weather in the spring) and the main emission sources being predominantly from the European Continent. We find clear spatial gradients in the aerosol loading as well as aerosol composition. From west to east along the English Channel, PM2.5 concentration increases with a mean gradient of about 0.007 μg m-3 km-1. At the westernmost site Plymouth, sea spray is estimated on average to account for 16% of the AOD and 13% of the particulate matter with aerodynamic diameter less than 10 μm (PM10). The importance of sea spray is reduced by at least a factor of two at the more eastern sites. The long-term decrease in aerosol loading along the English Channel appears to be more strongly driven by the reduced anthropogenic emissions, rather than by changes in the large-scale circulation such as the North Atlantic Oscillation. Clean ups in road vehicles and ship emissions, however, do not appear to be strong drivers for the long-term trends in aerosol loading at these coastal sites.

A consistently calibrated 40-year-long data set of visible-channel remote-sensing reflectance has been derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor global time series. The data set uses as its source the Pathfinder Atmospheres – Extended (PATMOS-x) v5.3 Climate Data Record for top-of-atmosphere (TOA) visible-channel reflectances. This paper describes the theoretical basis for the atmospheric correction procedure and its subsequent implementation, including the necessary ancillary data files used and quality flags applied, in order to determine remote-sensing reflectance. The resulting data set is produced at daily, and archived at monthly, resolution, on a 0.1∘×0.1∘ grid at https://doi.org/10.1594/PANGAEA.892175. The primary aim of deriving this data set is to highlight regions of the global ocean affected by highly reflective blooms of the coccolithophorid Emiliania huxleyi (where lith concentration >2–5×104 mL−1) over the past 40 years.

WOS:000450233300040; The Plymouth L4 time plankton series in the Western English Channel is a textbook example of a shallow, stratifying shelf sea system. Over its 30 yr of weekly sampling, this site has provided a diverse and contrasting suite of numerical and conceptual models of plankton bloom formation, phenology, and seasonal succession. The most recent of these papers, Kenitz et al. (2017) has initiated this comment, partly because we feel that it has presented a slightly misleading picture of the plankton composition at this site, and of a robust, recurring seasonal succession. We address this by illustrating the extent of inter-annual variability in phenology that occurs at the site, and which needs to be captured better within models. However our main aim is to foster a much better integration of the variety of top-down and bottom-up processes that have all been suggested to be key in driving seasonal succession. Some of these, particularly the multiple grazing and growth controls contributing to the so-called "loophole hypothesis" may be complementary, but others, such as the role of copepod feeding traits in driving species succession (Kenitz et al. 2017) offer testable competing hypotheses. The basic assumptions and outputs of all these models need to be validated more critically, both against time series data and process studies that include the finding of unselective feeding. We suggest that the variability in plankton phenology (and not just mean timing and amplitude) could be used to diagnose the performance of alternative models of plankton succession.

The pelagic copepods Oithona similis and Calanus helgolandicus have overlapping geographic ranges, yet contrast in feeding mode, reproductive strategy, and body size. We investigate how these contrasting traits influence the seasonality of copepod abundance and reproductive output under environmental variation, using time series data collected over 25 years at the Western Channel Observatory station L4. The proportional change in Egg Production Rate (EPR, eggs female-1 d-1) over the annual cycle was ~10-fold and similar for both species, although EPR of O. similis was only ~ 11% that of C. helgolandicus. The timing of EPR maxima for O. similis coincided with increased Sea Surface Temperature (SST) in summer, likely due to a temperature-dependent brooding period. Conversely, EPR of broadcast spawning C. helgolandicus was more strongly related to Net Heat Flux (NHF) and diatom biomass, both parameters associated with the spring phytoplankton bloom. In both species, female body mass negatively correlated with SST, with a 7.5% reduction in body mass per °C in C. helgolandicus compared to just 2.3% in O. similis. Finally, seasonality of EPR and adult and copepodite abundance was strongly decoupled in both species, suggesting that optimum conditions for reproduction and abundance occur at different times of the year.

Predictions of the ocean-atmosphere flux of dimethyl sulfide will be improved by understanding what controls seasonal and regional variations in dimethylsulfoniopropionate (DMSP) production. To investigate the influence of high levels of irradiance including ultraviolet radiation (UVR), on DMSP synthesis rates (mu DMSP) and inorganic carbon fixation (mu POC) by natural phytoplankton communities, nine experiments were carried out at different locations in the low nutrient, high light environment of the northeastern Tropical Atlantic. Rates of mu DMSP and mu POC were determined by measuring the incorporation of inorganic C-13 into DMSP and particulate organic carbon. Based on measurements over discrete time intervals during the day, a unique mu DMSP vs. irradiance (P vs. E) relationship was established. Comparison is made with the P vs. E relationship for mu POC, indicating that light saturation of DMSP occurs at similar irradiance to mu POC and is closely coupled to carbon fixation on a diel basis. Photoinhibition during the middle of the day was exacerbated by exposure to UVR, causing an additional 55-60% inhibition of both mu DMSP and mu POC at the highest light levels. In addition, decreased production of DMSP in response to UVR-induced photoxidative stress, contrasted with the increased net synthesis of photoprotective xanthophyll pigments. Together these results indicate that DMSP production by phytoplankton in the tropical ocean is not regulated in the short term by the necessity to control increasing photooxidative stress as irradiance increases during the day. The study provides new insight into the regulation of resource allocation into this biogeochemically important, multi-functional compatible solute.

The environmental impacts of artificial light at night have been a rapidly growing field of global change science in recent years. Yet, light pollution has not achieved parity with other global change phenomena in the level of concern and interest it receives from the scientific community, government and nongovernmental organizations. This is despite the globally widespread, expanding and changing nature of night-time lighting and the immediacy, severity and phylogenetic breath of its impacts. In this opinion piece, we evidence 10 reasons why artificial light at night should be a focus for global change research in the 21st century. Our reasons extend beyond those concerned principally with the environment, to also include impacts on human health, culture and biodiversity conservation more generally. We conclude that the growing use of night-time lighting will continue to raise numerous ecological, human health and cultural issues, but that opportunities exist to mitigate its impacts by combining novel technologies with sound scientific evidence. The potential gains from appropriate management extend far beyond those for the environment, indeed it may play a key role in transitioning towards a more sustainable society.

The near-surface layer of the ocean is a habitat in which plankton are subjected to very different stresses to those in deeper layers. These include high turbulence and illumination, allowing increased visibility to predators, and exposure to harmful UV radiation. To provide insights into stress caused by UV, we examined the occurrence of protective UV-absorbing compounds called mycosporine-like amino acids (MAAs) in seston and zooplankton along an Atlantic Meridional Transect (AMT) between 45°S and 50°N. Seston contained most MAAs per unit phytoplankton carbon in the northern Atlantic gyre and equatorial region and this coincided with distribution of the nitrogen fixing cyanobacterium Trichodesmium spp. and increased UV transparency but not irradiance. Asterina-330 was the most abundant MAA in the seston. MAAs were detected in a third of the zooplankton tested and these taxa varied greatly both in the amount and diversity of the MAAs that they contained with copepods in temperate regions containing highest concentration of MAAs. Most commonly found MAAs in zooplankton were palythine and shinorine. Juvenile copepods were found not to contain any MAAs. We determined abundance and richness of zooplankton inhabiting the top 50 cm of the ocean. Zooplankton abundance and genera richness was low in the surface waters in contrast to the dome-shaped latitudinal trend in genera richness commonly found from depth-integrated zooplankton sampling. The lack of any measurable MAA compounds in nauplii across the whole transect was concomitant with their severe (3–6-fold) reduction in nauplii densities in the near-surface layer, as compared to the underlying water column. Overall we suggest that the UV stress on life near the surface, particularly in the warmer, oligotrophic and brightly-lit low latitudes, imposes radically different pressures on zooplankton communities compared to the rest of the epipelagic.

Sea surface temperature (SST) is an essential climate variable that can be measured routinely from Earth Observation (EO) with high temporal and spatial coverage. To evaluate its suitability for an application, it is critical to know the accuracy and precision (performance) of the EO SST data. This requires comparisons with co-located and concomitant in situ data. Owing to a relatively large network of in situ platforms there is a good understanding of the performance of EO SST data in the open ocean. However, at the coastline this performance is not well known, impeded by a lack of in situ data. Here, we used in situ SST measurements collected by a group of surfers over a three year period in the coastal waters of the UK and Ireland, to improve our understanding of the performance of EO SST data at the coastline. At two beaches near the city of Plymouth, UK, the in situ SST measurements collected by the surfers were compared with in situ SST collected from two autonomous buoys located ∼7 km and ∼33 km from the coastline, and showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected by the surfers around the coastline, and those collected offshore by the two autonomous buoys, were used to evaluate the performance of operational Advanced Very High Resolution Radiometer (AVHRR) EO SST data. Results indicate: (i) a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square errors in the range of 1.0 to 2.0 °C depending on the temporal difference between match-ups, significantly higher than those at the two offshore stations (0.4 to 0.6 °C); (ii) a systematic negative bias in the AVHRR retrievals of approximately 1 °C at the coastline, not observed at the two offshore stations; and (iii) an increase in the root mean square error at the coastline when the temporal difference between match-ups exceeded three hours. Harnessing new solutions to improve in situ sampling coverage at the coastline, such as tagging surfers with sensors, can improve our understanding of the performance of EO SST data in coastal regions, helping inform users interested in EO SST products for coastal applications. Yet, validating EO SST products using in situ SST data at the coastline is challenged by difficulties reconciling the two measurements, which are provided at different spatial scales in a dynamic and complex environment.

We have developed two hyperspectral radiometer systems which require no moving parts, shade rings or motorised tracking, making them ideally suited for autonomous use in the inhospitable remote marine environment. Both systems are able to measure direct and diffuse hyperspectral irradiance in the wavelength range 350–1050 nm at 6 nm (Spectrometer 1) or 3.5 nm (Spectrometer 2) resolution. Marine field trials along a 100° transect (between 50° N and 50° S) of the Atlantic Ocean resulted in close agreement with existing commercially available instruments in measuring (1) photosynthetically available radiation (PAR), with both spectrometers giving regression slopes close to unity (Spectrometer 1: 0.960; Spectrometer 2: 1.006) and R2 ∼ 0.96; (2) irradiant energy, with R2 ∼ 0.98 and a regression slope of 0.75 which can be accounted for by the difference in wavelength integration range; and (3) hyperspectral irradiance where the agreement on average was between 2 and 5 %. Two long duration land-based field campaigns of up to 18 months allowed both spectrometers to be well calibrated. This was also invaluable for empirically correcting for the wider field of view (FOV) of the spectrometers in comparison with the current generation of sun photometers ( ∼ 7.5° compared with ∼ 1°). The need for this correction was also confirmed and independently quantified by atmospheric radiative transfer modelling and found to be a function of aerosol optical depth (AOD) and solar zenith angle. Once Spectrometer 2 was well calibrated and the FOV effect corrected for, the RMSE in retrievals of AOD when compared with a CIMEL sun photometer were reduced to ∼ 0.02–0.03 with R2 > 0.95 at wavelengths 440, 500, 670 and 870 nm. Corrections for the FOV as well as ship motion were applied to the data from the marine field trials. This resulted in AOD500 nm ranging between 0.05 in the clear background marine aerosol regions and ∼ 0.5 within the Saharan dust plume. The RMSE between the handheld Microtops sun photometer and Spectrometer 2 was between 0.047 and 0.057 with R2 > 0.94.

Atmospheric forcing applied as ocean model boundary conditions can have a critical impact on the quality of ocean forecasts. This paper assesses the sensitivity of an eddy-resolving (1.5 km resolution) regional ocean model of the north-west European Shelf (NWS) to the choice of atmospheric forcing and atmosphere–ocean coupling. The analysis is focused on a month-long simulation experiment for July 2014 and evaluation of simulated sea surface temperature (SST) in a shallow near-coastal region to the south-west of the UK (Celtic Sea and western English Channel). Observations of the ocean and atmosphere are used to evaluate model results, with a particular focus on the L4 ocean buoy from the Western Channel Observatory as a rare example of co-located data above and below the sea surface. The impacts of differences in the atmospheric forcing are illustrated by comparing results from an ocean model run in forcing mode using operational global-scale numerical weather prediction (NWP) data with an ocean model run forced by a convective-scale regional atmosphere model. The value of dynamically representing feedbacks between the atmosphere and ocean state is assessed via the use of these model components within a fully coupled ocean–wave–atmosphere system. Simulated SSTs show considerable sensitivity to atmospheric forcing and to the impact of model coupling in near-coastal areas. A warm ocean bias relative to in situ observations in the simulation forced by global-scale NWP (0.7 K in the model domain) is shown to be reduced (to 0.4 K) via the use of the 1.5 km resolution regional atmospheric forcing. When simulated in coupled mode, this bias is further reduced (by 0.2 K). Results demonstrate much greater variability of both the surface heat budget terms and the near-surface winds in the convective-scale atmosphere model data, as might be expected. Assessment of the surface heat budget and wind forcing over the ocean is challenging due to a scarcity of observations. However, it can be demonstrated that the wind speed over the ocean simulated by the convective-scale atmosphere did not agree as well with the limited number of observations as the global-scale NWP data did. Further partially coupled experiments are discussed to better understand why the degraded wind forcing does not detrimentally impact on SST results.

In this study we demonstrate the many strengths of scale analysis: we use it to evaluate the Nucleus for European Modelling of the Ocean model skill in representing sea surface temperature (SST) in the Southern Ocean by comparing three model resolutions: 1/12°, 1/4°, and 1°. We show that while 4–5 times resolution scale is sufficient for each model resolution to reproduce the magnitude of satellite Earth Observation (EO) SST spatial variability to within ±10%, the representation of ∼100-km SST variability patterns is substantially (e.g., ∼50% at 750 km) improved by increasing model resolution from 1° to 1/12°. We also analyzed the dominant scales of the SST model input drivers (short-wave radiation, air-sea heat fluxes, wind stress components, wind stress curl, and bathymetry) variability with the purpose of determining the optimal SST model input driver resolution. The SST magnitude of variability is shown to scale with two power law regimes separated by a scaling break at ∼200-km scale. The analysis of the spatial and temporal scales of dominant SST driver impact helps to interpret this scaling break as a separation between two different dynamical regimes: the (relatively) fast SST dynamics below ∼200 km governed by eddies, fronts, Ekman upwelling, and air-sea heat exchange, while above ∼200 km the SST variability is dominated by long-term (seasonal and supraseasonal) modes and the SST geography.

Macroalgae drive the largest CO2 flux fixed globally by marine macrophytes. Most of the resulting biomass is exported through the coastal ocean as detritus and yet almost no field measurements have verified its potential net sequestration in marine sediments. This gap limits the scope for the inclusion of macroalgae within blue carbon schemes that support ocean carbon sequestration globally, and the understanding of the role their carbon plays within distal food webs. Here, we pursued three lines of evidence (eDNA sequencing, Bayesian Stable Isotope Mixing Modeling, and benthic-pelagic process measurements) to generate needed, novel data addressing this gap. To this end, a 13-month study was undertaken at a deep coastal sedimentary site in the English Channel, and the surrounding shoreline of Plymouth, UK. The eDNA sequencing indicated that detritus from most macroalgae in surrounding shores occurs within deep, coastal sediments, with detritus supply reflecting the seasonal ecology of individual species. Bayesian stable isotope mixing modeling [C and N] highlighted its vital role in supporting the deep coastal benthic food web (22–36% of diets), especially when other resources are seasonally low. The magnitude of detritus uptake within the food web and sediments varies seasonally, with an average net sedimentary organic macroalgal carbon sequestration of 8.75 g C·m−2·yr−1. The average net sequestration of particulate organic carbon in sediments is 58.74 g C·m−2·yr−1, the two rates corresponding to 4–5% and 26–37% of those associated with mangroves, salt marshes, and seagrass beds, systems more readily identified as blue carbon habitats. These novel data provide important first estimates that help to contextualize the importance of macroalgal-sedimentary connectivity for deep coastal food webs, and measured fluxes help constrain its role within global blue carbon that can support policy development. At a time when climate change mitigation is at the foreground of environmental policy development, embracing the full potential of the ocean in supporting climate regulation via CO2 sequestration is a necessity.

Compelling evidence is presented that sub-micron picoplankton shape, internal structure and orientation in combination leads to a disproportionate enhancement of differential forward scatter compared with differential side scatter when analyzed with a flow cytometer. Theoretical evidence is provided which results in an order of magnitude amplification in the forward scatter direction, with little or no change in the side scatter: this discounts the possibility of “doublets” caused by multiple particles simultaneously present in the laser beam. Observational evidence from progressively finer filtered seawater samples shows up to three orders of magnitude enhancement in the forward scatter direction and sizes of Prochlorococcus close to that reported in the literature (0.61 ± 0.17 µm). It therefore seems likely that flow cytometrically observed “bi-modal size distributions” of Prochlorococcus are instead the manifestation of intra-population differences in shape (spherical – prolate with preferential alignment) and internal structure (homogenous – heterogenous).

We are in an era of unprecedented data volumes generated from observations and model simulations. This is particularly true from satellite Earth Observations (EO) and global scale oceanographic models. This presents us with an opportunity to evaluate large scale oceanographic model outputs using EO data. Previous work on model skill evaluation has led to a plethora of metrics. The paper defines two new model skill evaluation metrics. The metrics are based on the theory of universal multifractals and their purpose is to measure the structural similarity between the model predictions and the EO data. The two metrics have the following advantages over the standard techniques: a) they are scale-free, b) they carry important part of information about how model represents different oceanographic drivers. Those two metrics are then used in the paper to evaluate the performance of the FVCOM model in the shelf seas around the south-west coast of the UK.

We present air–sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the south-west coast of the United Kingdom. Measurements from the south-westerly direction (open water sector) were made at three different sampling heights (approximately 15, 18, and 27 m above mean sea level, a.m.s.l.), each from a different period during 2014–2015. At sampling heights ≥ 18 m a.m.s.l., measured fluxes of momentum and sensible heat demonstrate reasonable ( ≤ ±20 % in the mean) agreement with transfer rates over the open ocean. This confirms the suitability of PPAO for air–sea exchange measurements in shelf regions. Covariance air–sea CO2 fluxes demonstrate high temporal variability. Air-to-sea transport of CO2 declined from spring to summer in both years, coinciding with the breakdown of the spring phytoplankton bloom. We report, to the best of our knowledge, the first successful eddy covariance measurements of CH4 emissions from a marine environment. Higher sea-to-air CH4 fluxes were observed during rising tides (20 ± 3; 38 ± 3; 29 ± 6 µmole m−2 d−1 at 15, 18, 27 m a.m.s.l.) than during falling tides (14 ± 2; 22 ± 2; 21 ± 5 µmole m−2 d−1), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. These fluxes are a few times higher than the predicted CH4 emissions over the open ocean and are significantly lower than estimates from other aquatic CH4 hotspots (e.g. polar regions, freshwater). Finally, we found the detection limit of the air–sea CH4 flux by eddy covariance to be 20 µmole m−2 d−1 over hourly timescales (4 µmole m−2 d−1 over 24 h).

Atmospheric sulfur dioxide (SO2) was measured continuously from the Penlee Point Atmospheric Observatory (PPAO) near Plymouth, United Kingdom, between May 2014 and November 2015. This coastal site is exposed to marine air across a wide wind sector. The predominant southwesterly winds carry relatively clean background Atlantic air. In contrast, air from the southeast is heavily influenced by exhaust plumes from ships in the English Channel as well as near Plymouth Sound. A new International Maritime Organization (IMO) regulation came into force in January 2015 to reduce the maximum allowed sulfur content in ships' fuel 10-fold in sulfur emission control areas such as the English Channel. Our observations suggest a 3-fold reduction in ship-emitted SO2 from 2014 to 2015. Apparent fuel sulfur content calculated from coincidental SO2 and carbon dioxide (CO2) peaks from local ship plumes show a high level of compliance to the IMO regulation (> 95 %) in both years (∼ 70 % of ships in 2014 were already emitting at levels below the 2015 cap). Dimethyl sulfide (DMS) is an important source of atmospheric SO2 even in this semi-polluted region. The relative contribution of DMS oxidation to the SO2 burden over the English Channel increased from about one-third in 2014 to about one-half in 2015 due to the reduction in ship sulfur emissions. Our diel analysis suggests that SO2 is removed from the marine atmospheric boundary layer in about half a day, with dry deposition to the ocean accounting for a quarter of the total loss.

Air-water CH4 and CO2 fluxes were directly measured using the eddy covariance technique at the Penlee Point Atmospheric Observatory on the southwest coast of the United Kingdom from September 2015 to August 2016. The high frequency, year-long measurements provide unprecedented detail into the variability of these Greenhouse Gas fluxes from seasonal to diurnal and to semi-diurnal timescales. Depending on the wind sector, fluxes measured at this site are indicative of air-water exchange in coastal seas as well as in an outer estuary. For the open water sector when winds were off the Atlantic Ocean, annual CH4 emission averaged ~ 0.05 mmol m−2 d−1. Open water CH4 flux was near zero in December and January, probably due to reduced biological production of CH4. At times of high rainfall and river flow rate, CH4 emission from the estuarine-influenced Plymouth Sound sector was several times higher than emission from the open water sector. The implied CH4 saturation, derived from the measured fluxes and a wind speed dependent gas transfer velocity parameterization, of over 1000 % in the Plymouth Sound is within range of in situ dissolved CH4 measurements near the mouth of the river Tamar. CO2 flux from the open water sector was generally from sea-to-air in autumn and winter and from air-to-sea in late spring and summer, with an annual mean flux of near zero. CO2 flux from the Plymouth Sound sector was more positive, consistent with a higher dissolved CO2 concentration in the estuarine waters. A diurnal signal in CO2 flux and implied dissolved pCO2 are clearly observed for the Plymouth Sound sector and also evident for the open water sector during biologically productive periods. These observations suggest that coastal CO2 efflux may be underestimated if the sampling strategy is limited to daytime only. Combining the fluxes with in situ dissolved pCO2 measurements within the flux footprints allows us to estimate the CO2 transfer velocity. The gas transfer velocity vs. wind speed relationship at this coastal location agrees reasonably well with previous open water parameterizations in the mean, but demonstrates considerable variability. We discuss the influences of biological productivity and bottom-driven turbulence on coastal air-water gas exchange.

The nearshore coastal ocean is one of the most dynamic and biologically productive regions on our planet, supporting a wide range of ecosystem services. It is also one of the most vulnerable regions, increasingly exposed to anthropogenic pressure. In the context of climate change, monitoring changes in nearshore coastal waters requires systematic and sustained observations of key essential climate variables (ECV), one of which is sea surface temperature (SST). As temperature influences physical, chemical and biological processes within coastal systems, accurate monitoring is crucial for detecting change. SST is an ECV that can be measured systematically from satellites. Yet, owing to a lack of adequate in situ data, the accuracy and precision of satellite SST at the coastline are not well known. In a prior study, we attempted to address this by taking advantage of in situ SST measurements collected by a group of surfers. Here, we make use of a three year time-series (2014–2017) of in situ water temperature measurements collected using a temperature logger (recording every 30 min) deployed within a kelp forest (∼3 m below chart datum) at a subtidal rocky reef site near Plymouth, UK. We compared the temperature measurements with three other independent in situ SST datasets in the region, from two autonomous buoys located ∼7 km and ∼33 km from the coastline, and from a group of surfers at two beaches near the kelp site. The three datasets showed good agreement, with discrepancies consistent with the spatial separation of the sites. The in situ SST measurements collected from the kelp site and the two autonomous buoys were matched with operational Advanced Very High Resolution Radiometer (AVHRR) EO SST passes, all within 1 h of the in situ data. By extracting data from the closest satellite pixel to the three sites, we observed a significant reduction in the performance of AVHRR at retrieving SST at the coastline, with root mean square differences at the kelp site over twice that observed at the two offshore buoys. Comparing the in situ water temperature data with pixels surrounding the kelp site revealed the performance of the satellite data improves when moving two to three pixels offshore and that this improvement was better when using an SST algorithm that treats each pixel independently in the retrieval process. At the three sites, we related differences between satellite and in situ SST data with a suite of atmospheric variables, collected from a nearby atmospheric observatory, and a high temporal resolution land surface temperature (LST) dataset. We found that differences between satellite and in situ SST at the coastline (kelp site) were well correlated with LST and solar zenith angle; implying contamination of the pixel by land is the principal cause of these larger differences at the coastline, as opposed to issues with atmospheric correction. This contamination could be either from land directly within the pixel, potentially impacted by errors in geo-location, or possibly through thermal adjacency effects. Our results demonstrate the value of using benthic temperature loggers for evaluating satellite SST data in coastal regions, and highlight issues with retrievals at the coastline that may inform future improvements in operational products.

© 2015 Published by Elsevier Ltd. Primary productivity and subsequent carbon cycling in the coastal zone have a significant impact on the global carbon budget. It is currently unclear how anthropogenic activity could alter these budgets but long term coastal time series of hydrological, biogeochemical and biological measurements represent a key means to better understand past drivers, and hence to predicting future seasonal and inter-annual variability in carbon fixation in coastal ecosystems. An 8-year time series of primary production from 2003 to 2010, estimated using a recently developed absorption-based algorithm, was used to determine the nature and extent of change in primary production at a coastal station (L4) in the Western English Channel (WEC). Analysis of the seasonal and inter-annual variability in production demonstrated that on average, nano- and pico-phytoplankton account for 48% of the total carbon fixation and micro-phytoplankton for 52%. A recent decline in the primary production of nano- and pico-phytoplankton from 2005 to 2010 was observed, corresponding with a decrease in winter nutrient concentrations and a decrease in the biomass of Phaeocystis sp. Micro-phytoplankton primary production (PPM) remained relatively constant over the time series and was enhanced in summer during periods of high precipitation. Increases in sea surface temperature, and decreases in wind speeds and salinity were associated with later spring maxima in PPM. Together these trends indicate that predicted increases in temperature and decrease in wind speeds in future would drive later spring production whilst predicted increases in precipitation would also continue these blooms throughout the summer at this site.

Characterization of chlorophyll and sea surface temperature (SST) structural heterogeneity using their scaling properties can provide a useful tool to estimate the relative importance of key physical and biological drivers. Seasonal, annual, and also instantaneous spatial distributions of chlorophyll and SST, determined from satellite measurements, in seven different coastal and shelf-sea regions around the UK have been studied. It is shown that multifractals provide a very good approximation to the scaling properties of the data: in fact, the multifractal scaling function is well approximated by universal multifractal theory. The consequence is that all of the statistical information about data structure can be reduced to being described by two parameters. It is further shown that also bathymetry scales in the studied regions as multifractal. The SST and chlorophyll multifractal structures are then explained as an effect of bathymetry and turbulence.

Satellite-derived remote-sensing reflectance (Rrs) can be used for mapping biogeochemically relevant variables, such as the chlorophyll concentration and the Inherent Optical Properties (IOPs) of the water, at global scale for use in climate-change studies. Prior to generating such products, suitable algorithms have to be selected that are appropriate for the purpose. Algorithm selection needs to account for both qualitative and quantitative requirements. In this paper we develop an objective methodology designed to rank the quantitative performance of a suite of bio-optical models. The objective classification is applied using the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Using in situRrs as input to the models, the performance of eleven semi-analytical models, as well as five empirical chlorophyll algorithms and an empirical diffuse attenuation coefficient algorithm, is ranked for spectrally-resolved IOPs, chlorophyll concentration and the diffuse attenuation coefficient at 489 nm. The sensitivity of the objective classification and the uncertainty in the ranking are tested using a Monte-Carlo approach (bootstrapping). Results indicate that the performance of the semi-analytical models varies depending on the product and wavelength of interest. For chlorophyll retrieval, empirical algorithms perform better than semi-analytical models, in general. The performance of these empirical models reflects either their immunity to scale errors or instrument noise in Rrs data, or simply that the data used for model parameterisation were not independent of NOMAD. Nonetheless, uncertainty in the classification suggests that the performance of some semi-analytical algorithms at retrieving chlorophyll is comparable with the empirical algorithms. For phytoplankton absorption at 443 nm, some semi-analytical models also perform with similar accuracy to an empirical model. We discuss the potential biases, limitations and uncertainty in the approach, as well as additional qualitative considerations for algorithm selection for climate-change studies. Our classification has the potential to be routinely implemented, such that the performance of emerging algorithms can be compared with existing algorithms as they become available. In the long-term, such an approach will further aid algorithm development for ocean-colour studies.

We performed an annual study of oxygenated volatile organic compound (OVOC) seawater concentrations at a site off Plymouth, UK in the Western English Channel over the period of February 2011–March 2012. Acetone concentrations ranged from 2–10 nM (nanomole/L) in surface waters with a maximum observed in summer. Concentrations correlated positively with net shortwave radiation and UV light, suggestive of photochemically linked acetone production. We observed a clear decline in acetone concentrations below the mixed layer. Acetaldehyde varied between 4–37 nM in surface waters with higher values observed in autumn and winter. Surface concentrations of methanol ranged from 16–78 nM, but no clear annual cycle was observed. Methanol concentrations exhibited considerable inter-annual variability. We estimate consistent deposition to the sea surface for acetone and methanol but that the direction of the acetaldehyde flux varies during the year.

The Atlantic Meridional Transect (AMT) series of twenty-five cruises over the past twenty years has produced a rich depth-resolved biogeochemical in situ data resource consisting of a wealth of core variables. These multiple core datasets, key to the operation of AMT, such as temperature, salinity, oxygen and inorganic nutrients, are often only used as ancillary measurements for contextualising hypothesis-driven process studies. In this paper these core in situ variables, alongside data drawn from satellite Earth Observation (EO) and modelling, have been analysed to determine characteristic oceanic province variations encountered over the last twenty years on the AMT through the Atlantic Ocean. The EO and modelling analysis shows the variations of key environmental variables in each province, such as surface currents, the net heat flux and subsequent large scale biological responses, such as primary production. The in situ core dataset analysis allows the variation in features such as the tropical oxygen minimum zone to be quantified as well as showing clear contrasts between the provinces in nutrient stoichiometry. Such observations and relationships can be used within basin scale biogeochemical models to set realistic variation ranges.

Most satellite models of production have been designed and calibrated for use in the open ocean. Coastal waters are optically more complex, and the use of chlorophyll a (chl a) as a first-order predictor of primary production may lead to substantial errors due to significant quantities of coloured dissolved organic matter (CDOM) and total suspended material (TSM) within the first optical depth. We demonstrate the use of phytoplankton absorption as a proxy to estimate primary production in the coastal waters of the North Sea and Western English Channel for both total, micro- and nano+pico-phytoplankton production. The method is implemented to extrapolate the absorption coefficient of phytoplankton and production at the sea surface to depth to give integrated fields of total and micro- and nano+pico-phytoplankton primary production using the peak in absorption coefficient at red wavelengths. The model is accurate to 8% in the Western English Channel and 22% in this region and the North Sea. By comparison, the accuracy of similar chl a based production models was >250%. The applicability of the method to autonomous optical sensors and remotely sensed aircraft data in both coastal and estuarine environments is discussed. © Inter-Research 2014.

Depth-resolved flow cytometric observations have been used to determine the size distribution and refractive index (RI) of picoplankton throughout the Atlantic Ocean. Prochlorococcus frequently showed double size distribution peaks centered on ${0.75 \pm 0.25}$0.75±0.25 and ${1.75 \pm 0.25}\,\,{\rm \unicode{x00B5}{\rm m}}$1.75±0.25µm; the smallest peak diameters were ${\le}{0.65}\,\,{\rm \unicode{x00B5}{\rm m}}$≤0.65µm in the equatorial upwelling with larger cells (${\sim}{0.95}\,\,{\rm \unicode{x00B5}{\rm m}}$∼0.95µm) in the surface layers of the tropical gyres. Synechococcus was strongly monodispersed: the smallest (${\sim}{1.5}\,\,{\rm \unicode{x00B5}{\rm m}}$∼1.5µm) and largest cells (${\sim}{2.25{-}2.50}\,\,{\rm \unicode{x00B5}{\rm m}}$∼2.25-2.50µm) were encountered in the lowest and highest abundance regions, respectively. Typical RI for Prochlorococcus was found to be ${\sim}{1.06}$∼1.06, whereas for Synechococcus surface RI varied between 1.04-1.08 at high and low abundances, respectively.

We present here vertical fluxes of oxygenated volatile organic compounds (OVOCs) measured with eddy covariance (EC) during the period of March to July 2012 near the southwest coast of the United Kingdom. The performance of the proton-transfer-reaction mass spectrometer (PTR-MS) for flux measurement is characterized, with additional considerations given to the homogeneity and stationarity assumptions required by EC. Observed mixing ratios and fluxes of OVOCs (specifically methanol, acetaldehyde, and acetone) vary significantly with time of day and wind direction. Higher mixing ratios and fluxes of acetaldehyde and acetone are found in the daytime and from the direction of a forested park, most likely due to light-driven emissions from terrestrial plants. Methanol mixing ratio and flux do not demonstrate consistent diel variability, suggesting sources in addition to plants. We estimate air–sea exchange and photochemical rates of these compounds, which are compared to measured vertical fluxes. For acetaldehyde, the mean (1σ) mixing ratio of 0.13 (0.02) ppb at night may be maintained by oceanic emission, while photochemical destruction outpaces production during the day. Air–sea exchange and photochemistry are probably net sinks of methanol and acetone in this region. Their nighttime mixing ratios of 0.46 (0.20) and 0.39 (0.08) ppb appear to be affected more by terrestrial emissions and long-distance transport, respectively.

Atmospheric sulfur dioxide (SO2) was measured continuously from the Penlee Point Atmospheric Observatory(PPAO) near Plymouth, United Kingdom between May 2014 and November 2015. This coastal site is exposed to marine air across a wide wind sector. The predominant southwesterly winds carry relatively clean background Atlantic air. In contrast, air from the southeast is heavily influenced by exhaust plumes from ships in the English Channel as well as near the Plymouth Sound. New International Maritime Organization (IMO) regulation came into force in January 2015 to reduce sulfur emissions tenfold in Sulfur Emission Control Areas such as the English Channel. Our observations suggest a three-fold reduction from 2014 to 2015 in ship-emitted SO2 from that direction. Apparent fuel sulfur content calculated from coincidental SO2 and carbon dioxide (CO2) peaks from local ship plum es show a high level of compliance to the IMO regulation (> 95 %) in both years. Dimethylsulfide (DMS) is an important source of atmospheric SO2 even in this semi-polluted region. The relative contribution of DMS oxidation to the SO2 burden over the English Channel increased from ~ 1/3 in 2014 to ~ 1/2 in 2015 due to the reduction in ship sulfur emissions. Our diel analysis suggests that SO2 is removed from the marine atmospheric boundary layer in about half a day, with dry deposition to the ocean accounting for a quarter of the total loss.

This chapter discusses past and ongoing change in the following physical variables within the North Sea: temperature, salinity and stratification; currents and circulation; mean sea level; and extreme sea levels. Also considered are carbon dioxide; pH and nutrients; oxygen; suspended particulate matter and turbidity; coastal erosion, sedimentation and morphology; and sea ice. The distinctive character of the Wadden Sea is addressed, with a particular focus on nutrients and sediments. This chapter covers the past 200 years and focuses on the historical development of evidence (measurements, process understanding and models), the form, duration and accuracy of the evidence available, and what the evidence shows in terms of the state and trends in the respective variables. Much work has focused on detecting long-term change in the North Sea region, either from measurements or with models. Attempts to attribute such changes to, for example, anthropogenic forcing are still missing for the North Sea. Studies are urgently needed to assess consistency between observed changes and current expectations, in order to increase the level of confidence in projections of expected future conditions.

A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GeP&CO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594/PANGAEA.854832 (Valente et al., 2015).

The European Skynet Radiometers network (EuroSkyRad or ESR) has been recently established as a research network of European PREDE sun-sky radiometers. Moreover, ESR is federated with SKYNET, an international network of PREDE sun-sky radiometers mostly present in East Asia. In contrast to SKYNET, the European network also integrates users of the CIMEL CE318 sky–sun photometer. Keeping instrumental duality in mind, a set of open source algorithms has been developed consisting of two modules for (1) the retrieval of direct sun products (aerosol optical depth, wavelength exponent and water vapor) from the sun extinction measurements; and (2) the inversion of the sky radiance to derive other aerosol optical properties such as size distribution, single scattering albedo or refractive index. In this study we evaluate the ESR direct sun products in comparison with the AERosol RObotic NETwork (AERONET) products. Specifically, we have applied the ESR algorithm to a CIMEL CE318 and PREDE POM simultaneously for a 4-yr database measured at the Burjassot site (Valencia, Spain), and compared the resultant products with the AERONET direct sun measurements obtained with the same CIMEL CE318 sky–sun photometer. The comparison shows that aerosol optical depth differences are mostly within the nominal uncertainty of 0.003 for a standard calibration instrument, and fall within the nominal AERONET uncertainty of 0.01–0.02 for a field instrument in the spectral range 340 to 1020 nm. In the cases of the Ångström exponent and the columnar water vapor, the differences are lower than 0.02 and 0.15 cm, respectively. Therefore, we present an open source code program that can be used with both CIMEL and PREDE sky radiometers and whose results are equivalent to AERONET and SKYNET retrievals.

A buoy system has been developed to continually monitor the operationally demanding coastal and open-shelf environment of the western English Channel. The buoys measure a range of physical and biogeochemical parameters on an hourly basis at two established long-term monitoring sites and the data are relayed to shore in near–real time using radio communications. This paper describes the technological challenges faced in such long-term marine deployments including the mooring design, warning systems, command and control, and radio communications, and how each were overcome. The fine temporal frequency data are used within an operational oceanography context, will underpin the long-term sustained observations in the western English Channel, and will form the basis of improvements to finescale ecosystem modeling to better predict any changes in the U.K. shelf seas.

The marine laboratories in Plymouth have sampled at two principle sites in the western English Channel for over a century in open-shelf (station E1; 508 020N, 48 220W) and coastal (station L4; 508 150N, 48 130W) waters. These stations are seasonally stratified from late-April until September, and the variable biological response is regulated by subtle variations in temperature, light, nutrients and meteorology. Station L4 is characterized by summer nutrient depletion, although intense summer precipitation, increasing riverine input to the system, results in pulses of increased nitrate concentration and surface freshening. The winter nutrient concentrations at E1 are consistent with an open-shelf site. Both stations have a spring and autumn phytoplankton bloom; at station E1, the autumn bloom tends to dominate in terms of chlorophyll concentration. The last two decades have seen a warming of around 0.68C per decade, and this is superimposed on several periods of warming and cooling over the past century. In general, over the western English Channel domain, the end of the 20th century was around 0.58C warmer than the first half of the century. The warming magnitude and trend is consistent with other stations across the north-west European Shelf and occurred during a period of reduced wind stress and increased levels of insolation (þ20%); these are both correlated with the larger scale climatic forcing of the North Atlantic Oscillation.

Shelf and coastal seas are regions of exceptionally high biological productivity, high rates of biogeochemical cycling and immense socio-economic importance. They are, however, poorly represented by the present generation of Earth system models, both in terms of resolution and process representation. Hence, these models cannot be used to elucidate the role of the coastal ocean in global biogeochemical cycles and the effects global change (both direct anthropogenic and climatic) are having on them. Here, we present a system for simulating all the coastal regions around the world (the Global Coastal Ocean Modelling System) in a systematic and practical fashion. It is based on automatically generating multiple nested model domains, using the Proudman Oceanographic Laboratory Coastal Ocean Modelling System coupled to the European Regional Seas Ecosystem Model. Preliminary results from the system are presented. These demonstrate the viability of the concept, and we discuss the prospects for using the system to explore key areas of global change in shelf seas, such as their role in the carbon cycle and climate change effects on fisheries.

We review the concept of phytoplankton functional types (PFTs) in marine ecosystems as a means of advancing bio-mechanistic models that can be coupled to the global carbon cycle and the Earth's climate system. Conventional classification of phytoplankton by size may seem arbitrary, but there appears clear links between size and environmental characteristics (availability of essential nutrients and light) that regulate photosynthesis, phytoplankton selection and succession. Taking a minimalist approach, small phytoplankton (picoplankton) survive in permanently stratified systems with low nutrients, high surface light and low light in deep clines, whereas large phytoplankton (microplankton) thrive in high nutrient, turbulent, high light, near surface systems. Nutrient-light environmental conditions are characteristic properties of globally, latitudinal-dispersed biogeochemical provinces. These contrasting nutrient-light regimes define the extreme ends of the bio-energetic scale of photosynthesis and set the end points of the primary range of phytoplankton functional processes. To determine PFTs from remotely sensed ocean colour data, there must be a specific bio-optical trait (BOT) that can be associated with the phytoplankton species or taxa. We investigate the connection of the bio-energetic scale to phytoplankton types and their BOTs, which is the first, but crucial step for classifying PFTs on the basis of functional processes, from which refinements and further partitioning can be developed.

The AMT (www.amt-uk.org) is a multidisciplinary programme which undertakes biological, chemical, and physical oceanographic research during an annual voyage between the UK and a destination in the South Atlantic such as the Falkland Islands, South Africa, or Chile. This transect of >12,000 km crosses a range of ecosystems from subpolar to tropical, from euphotic shelf seas and upwelling systems, to oligotrophic mid-ocean gyres. The year 2015 has seen two milestones in the history of the AMT: the achievement of 20 years of this unique ocean going programme and the departure of the 25th cruise on the 15th of September. Both of these events were celebrated in June this year with an open science conference hosted by the Plymouth Marine Laboratory (PML) and will be further documented in a special issue of Progress in Oceanography which is planned for publication in 2016. Since 1995, the 25 research cruises have involved 242 sea-going scientists from 66 institutes representing 22 countries. AMT was designed from the outset to be a collaborative programme. It was originally conceived by Jim Aiken, Patrick Holligan, Roger Harris, and Dave Robins with Chuck McClain and Chuck Trees at NASA to test and ground truth satellite algorithms of ocean color. The opportunities offered by this initiative meant that this series of repeated biannual cruises rapidly developed into a coordinated study of ocean biodiversity, biogeochemistry, and ocean/atmosphere interactions.

We investigated 32 net primary productivity (NPP) models by assessing skills to reproduce integrated NPP in the Arctic Ocean. The models were provided with two sources each of surface chlorophyll‐a concentration (chlorophyll), photosynthetically available radiation (PAR), sea surface temperature (SST), and mixed‐layer depth (MLD). The models were most sensitive to uncertainties in surface chlorophyll, generally performing better with in situ chlorophyll than with satellite‐derived values. They were much less sensitive to uncertainties in PAR, SST, and MLD, possibly due to relatively narrow ranges of input data and/or relatively little difference between input data sources. Regardless of type or complexity, most of the models were not able to fully reproduce the variability of in situ NPP, whereas some of them exhibited almost no bias (i.e., reproduced the mean of in situ NPP). The models performed relatively well in low‐productivity seasons as well as in sea ice‐covered/deep‐water regions. Depth‐resolved models correlated more with in situ NPP than other model types, but had a greater tendency to overestimate mean NPP whereas absorption‐based models exhibited the lowest bias associated with weaker correlation. The models performed better when a subsurface chlorophyll‐a maximum (SCM) was absent. As a group, the models overestimated mean NPP, however this was partly offset by some models underestimating NPP when a SCM was present. Our study suggests that NPP models need to be carefully tuned for the Arctic Ocean because most of the models performing relatively well were those that used Arctic‐relevant parameters., Key Points The models reproduced primary productivity better using in situ chlorophyll‐a than satellite valuesThe models performed well in low‐productivity seasons and in sea ice‐covered/deep‐water regionsNet primary productivity models need to be carefully tuned for the Arctic Ocean

An autonomous underwater vehicle (Seaglider) has been used to estimate marine primary production (PP) using a combination of irradiance and fluorescence vertical profiles. This method provides estimates for depth-resolved and temporally evolving PP on fine spatial scales in the absence of ship-based calibrations. We describe techniques to correct for known issues associated with long autonomous deployments such as sensor calibration drift and fluorescence quenching. Comparisons were made between the Seaglider, stable isotope (13C) and satellite estimates of PP. The Seaglider-based PP estimates were comparable to both satellite estimates and stable isotope measurements.