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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.

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.

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.

Since 1995 the Atlantic Meridional Transect program (AMT - www.amt-uk.org) has undertaken extensive measurements of oceanographic and atmospheric variables on a passage between the UK and destinations in the South Atlantic (Falkland Islands, Chile, Uruguay and South Africa). This program, which spans more than 100° of latitude, crosses a range of ecosystems from sub-polar to tropical, from eutrophic shelf seas and upwelling systems, to oligotrophic mid-ocean gyres (Fig. 1). The AMT was originally conceived to utilise the bi-annual passage of the RRS James Clark Ross (JCR) between its home-base in the UK and its field-base in the Falklands. This initial phase, from 1995 to 2000 was largely funded by the Plymouth Marine Laboratory (PML) and the Natural Environment Research Council (NERC) with additional support from NASA in order to test and ground-truth satellite algorithms of ocean colour (Aiken & Bale, 2000). The opportunities offered by this initiative meant that this series of repeated bi-annual cruises rapidly developed into a coordinated study of ocean biodiversity, biogeochemistry and ocean/atmosphere interactions. The second phase, between 2002 and 2006 was funded by a NERC consortium grant which is introduced and summarised in two manuscripts by Robinson (Robinson et al., 2009, Robinson et al., 2006) which form the introduction to special issues of Deep-Sea Research II. This phase utilised a hypothesis-led approach concerning the biogeochemistry of the different Atlantic Ocean provinces. In the third phase, from 2008 to present, funding from NERC was directed through the OCEANS2025 program and latterly through UK National Capability. During this phase, cruises switched from bi-annual to annual, taking place during the boreal autumn (austral spring). A summary of the annual and seasonal coverage of AMT cruises is given in Figure 2. Throughout the lifetime of the AMT program the objectives have evolved to address topical research questions whilst enabling the maintenance of a continuous set of observations relevant to global issues that are raised throughout the most recent IPCC assessment (Rhein et al., 2013) and UK environmental strategy.

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.

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.

Using satellite maps this paper offers a complex analysis of chlorophyll & SST heterogeneity in the shelf seas around the southwest of the UK. The heterogeneity scaling follows a simple power law and is consequently parametrized by two parameters. It is shown that in most cases these two parameters vary only relatively little with time. The paper offers a detailed comparison of field heterogeneity between different regions. How much heterogeneity is in each region preserved in the annual median data is also determined. The paper explicitly demonstrates how one can use these results to calculate representative measurement area for in situ networks.

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.

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.

Primary production (PP) was determined using 14C uptake at 117 stations in the Atlantic Ocean to validate three PP satellite algorithms of varying complexity. An empirical satellite algorithm based on log chlorophyll-a had the highest bias and root-mean square error compared with measured 14C PP and tended to under-estimate PP. The vertical generalised production model improved PP estimates and was the most accurate algorithm in the Eastern Tropical Atlantic (ETRA) and Western Tropical Atlantic (WTRA), but tended to over-estimate PP in eutrophic provinces. A photosynthesis-light wavelength-resolved model was the most accurate over the Atlantic basin, having the lowest mean log-difference error, root-mean square error and bias, and exhibited a superior performance in six out of the nine ecological provinces surveyed. Using this algorithm and mean monthly SeaWiFS fields, a PP time series was generated for the Atlantic Ocean from 1998 to 2005 which was compared with Advanced Very High Resolution Radiometer (AVHRR) sea-surface temperature (SST) data. There was a significant negative correlation between SST and PP in the North Atlantic Subtropical Gyre Province (NAST), North Atlantic Tropical Gyre (NATR), and WTRA suggesting that recent warming trends in these provinces are coupled with a decrease in phytoplankton production.

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).

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

Changes in the net heat flux (NHF) into the ocean have profound impacts on global climate. We analyse a long-term plankton time-series and show that the NHF is a critical indicator of ecosystem dynamics. We show that phytoplankton abundance and diversity patterns are tightly bounded by the switches between negative and positive NHF over an annual cycle. Zooplankton increase before the transition to positive NHF in the spring but are constrained by the negative NHF switch in autumn. By contrast bacterial diversity is decoupled from either NHF switch, but is inversely correlated (r =20.920) with the magnitude of the NHF. We show that the NHF is a robust mechanistic tool for predicting climate change indicators such as spring phytoplankton bloom timing and length of the growing season.

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. The MAN archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we investigate correlations between ship-borne aerosol optical depth (AOD) and near-surface wind speed, either measured (onboard or from satellite) or modeled (NCEP). According to our analysis, wind speed influences columnar aerosol optical depth, although the slope of the linear regression between AOD and wind speed is not steep (~0.004–0.005), even for strong winds over 10 m s−1. The relationships show significant scatter (correlation coefficients typically in the range 0.3–0.5); the majority of this scatter can be explained by the uncertainty on the input data. The various wind speed sources considered yield similar patterns. Results are in good agreement with the majority of previously published relationships between surface wind speed and ship-based or satellite-based AOD measurements. The basic relationships are similar for all the wind speed sources considered; however, the gradient of the relationship varies by around a factor of two depending on the wind data used.

We examine the trends and variability in temperature of the northwest European shelf seas over the period 1960–2004 using four approaches: a regional model simulation (using the Proudman Oceanographic Laboratory Coastal Ocean Modelling System; POLCOMS), in situ multi-annual timeseries observations, satellite remote sensed (AVHRR) sea surface temperature (SST), and an analysis of data held in an international database at the International Council for the Exploration of the Sea (ICES). We focus on variability for the full period and trends from 1985 to 2004, being limited by the length of model simulation and the availability of satellite data. We find that all data sources give a consistent picture, with both trends and variability being intensified on-shelf and north of ∼48°N. The model and AVHRR SST show statistically significant warming trends in large areas of this region that are clearly distinguishable from both model/observation error and natural variability on these timescales. This ‘signal to noise ratio’ is substantially reduced when near bottom temperatures are considered in the model. The long timeseries at Port Erin (Isle of Man) shows that the variation in trend is well represented by the model and that the warming trend in the period 1985–2004 is substantially larger and of longer duration than previous peaks in 20-year trends since 1914. We find that the SST trends are greater in the model and satellite observations than the air temperature trends in the ERA40 re-analysis used for forcing; the net sea to air heat flux is ∼20% less in 1985–2004 than 1960–1984 (including shortwave, longwave, sensible and latent components). This is partly compensated by a ∼9% reduction in advective warming. The model shows the trends in seasonally stratified regions are greater at the surface than at depth, indicating an increase in this stratification. While this pattern is also seen in the annual trends from the ICES data analysis, the lack of seasonal resolution hampers a quantitative corroboration. The model is seen to have good skill in reproducing both the trends and variability, but tends to underestimate the trends. The modelled variability is overestimated in some coastal and open ocean regions and underestimated elsewhere, while the phase of this variability is generally well represented. Generally the model performance is better on-shelf than in the open ocean.

Made available in DSpace on 2013-08-28T14:13:50Z (GMT). No. of bitstreams: 1 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) Made available in DSpace on 2013-09-30T19:22:54Z (GMT). No. of bitstreams: 2 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) WOS000287796800018.pdf.txt: 74870 bytes, checksum: b4ae21f33d5d23b3ff5f0482dfbc34ee (MD5) Previous issue date: 2011-01-01 Submitted by Vitor Silverio Rodrigues (vitorsrodrigues@reitoria.unesp.br) on 2014-05-20T15:34:00Z No. of bitstreams: 2 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) WOS000287796800018.pdf.txt: 74870 bytes, checksum: b4ae21f33d5d23b3ff5f0482dfbc34ee (MD5) Made available in DSpace on 2014-05-20T15:34:00Z (GMT). No. of bitstreams: 2 WOS000287796800018.pdf: 4189122 bytes, checksum: 57872b9405eca4911ea4efd9756f160c (MD5) WOS000287796800018.pdf.txt: 74870 bytes, checksum: b4ae21f33d5d23b3ff5f0482dfbc34ee (MD5) Previous issue date: 2011-01-01 National Aeronautics and Space Agency Nearly half of the earth's photosynthetically fixed carbon derives from the oceans. To determine global and region specific rates, we rely on models that estimate marine net primary productivity (NPP) thus it is essential that these models are evaluated to determine their accuracy. Here we assessed the skill of 21 ocean color models by comparing their estimates of depth-integrated NPP to 1156 in situ C-14 measurements encompassing ten marine regions including the Sargasso Sea, pelagic North Atlantic, coastal Northeast Atlantic, Black Sea, Mediterranean Sea, Arabian Sea, subtropical North Pacific, Ross Sea, West Antarctic Peninsula, and the Antarctic Polar Frontal Zone. Average model skill, as determined by root-mean square difference calculations, was lowest in the Black and Mediterranean Seas, highest in the pelagic North Atlantic and the Antarctic Polar Frontal Zone, and intermediate in the other six regions. The maximum fraction of model skill that may be attributable to uncertainties in both the input variables and in situ NPP measurements was nearly 72%. on average, the simplest depth/wavelength integrated models performed no worse than the more complex depth/wavelength resolved models. Ocean color models were not highly challenged in extreme conditions of surface chlorophyll-a and sea surface temperature, nor in high-nitrate low-chlorophyll waters. Water column depth was the primary influence on ocean color model performance such that average skill was significantly higher at depths greater than 250 m, suggesting that ocean color models are more challenged in Case-2 waters (coastal) than in Case-1 (pelagic) waters. Given that in situ chlorophyll-a data was used as input data, algorithm improvement is required to eliminate the poor performance of ocean color NPP models in Case-2 waters that are close to coastlines. Finally, ocean color chlorophyll-a algorithms are challenged by optically complex Case-2 waters, thus using satellite-derived chlorophyll-a to estimate NPP in coastal areas would likely further reduce the skill of ocean color models. Virginia Inst Marine Sci, Coll William & Mary, Gloucester Point, VA 23062 USA CNRS, LOV, Villefranche Sur Mer, France Univ Paris 06, UMR 7093, Villefranche Sur Mer, France SUNY Stony Brook, Sch Marine & Atmospher Sci, Stony Brook, NY 11794 USA Tokyo Univ Informat Sci, Chiba 2658501, Japan Oregon State Univ, Dept Bot & Plant Pathol, Corvallis, OR 97331 USA Univ Estadual Paulista, BR-11330900 São Paulo, Brazil European Commiss, Joint Res Ctr, I-21027 Ispra, Italy NOAA, NMFS, Narragansett Lab, Narragansett, RI 02882 USA Nagoya Univ, Hydrospher Atmospher Res Ctr, Nagoya, Aichi 4648601, Japan Seikai Natl Fisheries Res Inst, Ishigaki Trop Stn, Okinawa 9070451, Japan CUNY, Brooklyn Coll, Dept Geol, Brooklyn, NY 11210 USA Univ Roma Tor Vergata, Dept Biol, I-00173 Rome, Italy Plymouth Marine Lab, Plymouth PL1 3DH, Devon, England Fisheries & Oceans Canada, Inst Freshwater, Winnipeg, MB R3T 2N6, Canada Univ Calif San Diego, Scripps Inst Oceanog, La Jolla, CA 92093 USA NOAA, Coastal Serv Ctr, Charleston, SC 29405 USA Univ Estadual Paulista, BR-11330900 São Paulo, Brazil NASA: NNG06GA03G

The Maritime Aerosol Network (MAN) has been collecting data over the oceans since November 2006. Over 80 cruises were completed through early 2010 with deployments continuing. Measurements areas included various parts of the Atlantic Ocean, the Northern and Southern Pacific Ocean, the South Indian Ocean, the Southern Ocean, the Arctic Ocean and inland seas. MAN deploys Microtops hand-held sunphotometers and utilizes a calibration procedure and data processing traceable to AERONET. Data collection included areas that previously had no aerosol optical depth (AOD) coverage at all, particularly vast areas of the Southern Ocean. The MAN data archive provides a valuable resource for aerosol studies in maritime environments. In the current paper we present results of AOD measurements over the oceans, and make a comparison with satellite AOD retrievals and model simulations. © Author(s) 2011.

The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.

International audience; The paper presents the current status of the Maritime Aerosol Network (MAN), which has been developed as a component of the Aerosol Robotic Network (AERONET). MAN deploys Microtops handheld Sun photometers and utilizes the calibration procedure and data processing (Version 2) traceable to AERONET. A web site dedicated to the MAN activity is described. A brief historical perspective is given to aerosol optical depth (AOD) measurements over the oceans. A short summary of the existing data, collected on board ships of opportunity during the NASA Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) Project is presented. Globally averaged oceanic aerosol optical depth (derived from island‐based AERONET measurements) at 500 nm is ∼0.11 and Angstrom parameter (computed within spectral range 440–870 nm) is calculated to be ∼0.6. First results from the cruises contributing to the Maritime Aerosol Network are shown. MAN ship‐based aerosol optical depth compares well to simultaneous island and near‐coastal AERONET site AOD.

International audience; The third primary production algorithm round robin (PPARR3) compares output from 24 models that estimate depth-integrated primary production from satellite measurements of ocean color, as well as seven general circulation models (GCMs) coupled with ecosystem or biogeochemical models. Here we compare the global primary production fields corresponding to eight months of 1998 and 1999 as estimated from common input fields of photosynthetically-available radiation (PAR), sea-surface temperature (SST), mixed-layer depth, and chlorophyll concentration. We also quantify the sensitivity of the ocean-color-based models to perturbations in their input variables. The pair-wise correlation between ocean-color models was used to cluster them into groups or related output, which reflect the regions and environmental conditions under which they respond differently. The groups do not follow model complexity with regards to wavelength or depth dependence, though they are related to the manner in which temperature is used to parameterize photosynthesis. Global average PP varies by a factor of two between models. The models diverged the most for the Southern Ocean, SST under 10 degrees C, and chlorophyll concentration exceeding 1 mg Chlm(-3). Based on the conditions under which the model results diverge most, we conclude that current ocean-color-based models are challenged by high-nutrient low-chlorophyll conditions, and extreme temperatures or chlorophyll concentrations. The GCM-based models predict comparable primary production to those based on ocean color: they estimate higher values in the Southern Ocean, at low SST, and in the equatorial band, while they estimate lower values in eutrophic regions (probably because the area of high chlorophyll concentrations is smaller in the GCMs). Further progress in primary production modeling requires improved understanding of the effect of temperature on photosynthesis and better parameterization of the maximum photosynthetic rate. (c) 2006 Elsevier Ltd. All rights reserved.

Spawning temperature preferences for sardine (Sardina pilchardus) in the eastern North Atlantic were determined from egg survey data. These were compared with climatological temperature cycles (1986–2002) derived from satellite observations, by geographical region, to predict spawning seasons. Optimum spawning temperatures were determined as 14.0–15.0°C from the English Channel to Portugal and 16.0–18.0°C for all north-west African regions. Spawning seasons were closely related to the general latitudinal trend of the annual temperature cycle, with modification by upwelling in the western Iberian and north-west African regions. Some differences between temperature-based spawning season predictions and field observations were related to variations in seasonal plankton production. Correlations in the annual time-series of favourable spawning temperatures suggested relatively strong linkages between the southern areas from Portugal to Senegal. There was no consistent relationship between annual variations in extent of temperature-predicted spawning seasons and observed field abundance of eggs.

In this paper we evaluate whether the assimilation of remotely-sensed optical data into a marine ecosystem model improves the simulation of biogeochemistry in a shelf sea. A localized Ensemble Kalman filter was used to assimilate weekly diffuse light attenuation coefficient data, Kd(443) from SeaWiFs, into an ecosystem model of the western English Channel. The spatial distributions of (unassimilated) surface chlorophyll from satellite, and a multivariate time series of eighteen biogeochemical and optical variables measured in situ at one long-term monitoring site were used to evaluate the system performance for the year 2006. Assimilation reduced the root mean square error and improved the correlation with the assimilated Kd(443) observations, for both the analysis and, to a lesser extent, the forecast estimates, when compared to the reference model simulation. Improvements in the simulation of (unassimilated) ocean colour chlorophyll were less evident, and in some parts of the Channel the simulation of this data deteriorated. The estimation errors for the (unassimilated) in situ data were reduced for most variables with some exceptions, e.g. dissolved nitrogen. Importantly, the assimilation adjusted the balance of ecosystem processes by shifting the simulated food web towards the microbial loop, thus improving the estimation of some properties, e.g. total particulate carbon. Assimilation of Kd(443) outperformed a comparative chlorophyll assimilation experiment, in both the estimation of ocean colour data and in the simulation of independent in situ data. These results are related to relatively low error in Kd(443) data, and because it is a bulk optical property of marine ecosystems. Assimilation of remotely-sensed optical properties is a promising approach to improve the simulation of biogeochemical and optical variables that are relevant for ecosystem functioning and climate change studies.