Internal Waves at the UK Continental Shelf: Automatic Mapping Using the ENVISAT ASAR Sensor

Oceanic internal waves occur within stratified water along the boundary between water layers of different density and are generated when strong tidal currents flow over seabed topography. Their amplitude can exceed 50 m and they transport energy over long distances and cause vertical mixing when the waves break. This study presents the first fully automated methodology for the mapping of internal waves using satellite synthetic aperture radar (SAR) data and applies this to explore their spatial and temporal distribution within UK shelf seas. The new algorithm includes enhanced edge detection and spatial processing to target the appearance of these features on satellite images. We acquired and processed over 7000 ENVISAT ASAR scenes covering the UK continental shelfbetween2006and2012,toautomaticallygeneratedetailedmapsofinternalwaves. Monthlyand annual internal wave climatology maps of the continental shelf were produced showing spatial and temporal variability, which can be used to predict where internal waves have the most impact on the seabed environment and ecology in UK shelf seas. These observations revealed correlations between thetemporalpatternsofinternalwavesand theseasonswhenthecontinentalshelfwatersweremore stratified. The maps were validated using well-known seabed topographic features. Concentrations of internal waves were automatically identified at Wyville-Thomson Ridge in June 2008, at the continental shelf break to the east of Rosemary Bank in January 2010 and in the Faroe-Shetland Channel in June 2011. This new automated methodology has been shown to be robust for mapping internalwavesusingalargeSARdatasetandisrecommendedforstudiesinotherregionsworldwide and for SAR data acquired by other sensors

A sensitivity analysis of the impact of rain on regional and global sea-air fluxes of CO2 (dataset)

Directories containing the results from several different runs of the FluxEngine software (see Shutler et al 2015 http://www.oceanflux-ghg.org). These directories are named according o the parameterisation used to derive the results within. 'SOCAT' or 'takahashi' refers to the source of pCO2 climatology used in the software. 'Nonlinear raink' or 'raink' refer to the parameterisation used for estimating rain enhancement of gas transfer velocity (Harrison et al 2012 & Ho et al. 2004 respectively). 'wetdep' and 'wet deposition' refer to the direct deposition of carbon to the surface ocean by rain. 'reference' data sets do not include the effects of rain. Within the directories, results are in netCDF files within sub-directories for year and month. Net Fluxes and summary statistics have been calculated and are provided as text files. The names are again according to the parameterisation used to derive them. More details are in the associated paper References: Shutler JD, Land PE, Piolle J-F, Woolf DK, Goddijn-Murphy L, Paul F, et al. FluxEngine: A flexible processing system for calculating atmosphere-ocean carbon dioxide gas fluxes and climatologies. Journal of Atmospheric and Oceanic Technology. 2015; (Early release). doi: 10.1175/JTECH-D-14-00204.1. Harrison EL, Vernon F, Ho DT, Reid MR, Orton P, McGillis WR. Nonlinear interaction between rain- and wind-induced air-water gas exchange. Journal of Geophysical Research. 2012;117(C03034). doi: 10.1029/2011JC007693. Ho DT, Zappa CJ, McGillis WR, Bliven LF, Ward B, Dacey JWH, et al. Influence of rain on air-sea gas exchange: Lessons from a model ocean. Journal of Geophysical Research. 2004;109(C08S18). doi: 10.1029/2003JC001806.The article associated with this dataset is available in ORE at http://hdl.handle.net/10871/22888Data sets calculated using the FluxEngine software to examine the sensitivity of global estimates of CO2 exchange between ocean and atmosphere to rainfall. These data contribute to the publication 'A sensitivity analysis of the impact of rain on regional and global sea-air fluxes of CO2', accepted for publication by PlosOneThis work was funded by the European Space Agency (ESA) Support to Science Element (STSE) through the OceanFlux Greenhouse Gases project (contract 4000104762/11/I-AM) and the OceanFlux Greenhouse Gases Evolution project (contract 4000112091/14/I-LG). http://due.esrin.esa.int/stse

Spatial assessment of intertidal seagrass meadows using optical imaging systems and a lightweight drone

Seagrass ecosystems are highly sensitive to environmental change. They are also in global decline and under threat from a variety of anthropogenic factors. There is now an urgency to establish robust monitoring methodologies so that changes in seagrass abundance and distribution in these sensitive coastal environments can be understood. Typical monitoring approaches have included remote sensing from satellites and airborne platforms, ground based ecological surveys and snorkel/scuba surveys. These techniques can suffer from temporal and spatial inconsistency, or are very localised making it hard to assess seagrass meadows in a structured manner. Here we present a novel technique using a lightweight (sub 7 kg) drone and consumer grade cameras to produce very high spatial resolution (∼4 mm pixel−1) mosaics of two intertidal sites in Wales, UK. We present a full data collection methodology followed by a selection of classification techniques to produce coverage estimates at each site. We trialled three classification approaches of varying complexity to investigate and illustrate the differing performance and capabilities of each. Our results show that unsupervised classifications perform better than object-based methods in classifying seagrass cover. We also found that the more sparsely vegetated of the two meadows studied was more accurately classified - it had lower root mean squared deviation (RMSD) between observed and classified coverage (9–9.5%) compared to a more densely vegetated meadow (RMSD 16–22%). Furthermore, we examine the potential to detect other biotic features, finding that lugworm mounds can be detected visually at coarser resolutions such as 43 mm pixel−1, whereas smaller features such as cockle shells within seagrass require finer grained data (<17 mm pixel−1)

On the calculation of air-sea fluxes of CO2 in the presence of temperature and salinity gradients

The presence of vertical temperature and salinity gradients in the upper ocean and the occur- rence of variations in temperature and salinity on time scales from hours to many years complicate the calculation of the flux of carbon dioxide (CO2) across the sea surface. Temperature and salinity affect the interfacial concentration of aqueous CO2 primarily through their effect on solubility with lesser effects related to saturated vapor pressure and the relationship between fugacity and partial pressure. The effects of temperature and salinity profiles in the water column and changes in the aqueous concentration act primarily through the partitioning of the carbonate system. Climatological calculations of flux require atten- tion to variability in the upper ocean and to the limited validity of assuming ‘‘constant chemistry’’ in trans- forming measurements to climatological values. Contrary to some recent analysis, it is shown that the effect on CO2 fluxes of a cool skin on the sea surface is large and ubiquitous. An opposing effect on calculated fluxes is related to the occurrence of warm layers near the surface; this effect can be locally large but will usually coincide with periods of low exchange. A salty skin and salinity anomalies in the upper ocean also affect CO2 flux calculations, though these haline effects are generally weaker than the thermal effects

The OceanFlux Greenhouse Gases methodology for deriving a sea surface climatology of CO2 fugacity in support of air–sea gas flux studies

Climatologies, or long-term averages, of essential climate variables are useful for evaluating models and providing a baseline for studying anomalies. The Surface Ocean CO2 Atlas (SOCAT) has made millions of global underway sea surface measurements of CO2 publicly available, all in a uniform format and presented as fugacity, fCO2. As fCO2 is highly sensitive to temperature, the measurements are only valid for the instantaneous sea surface temperature (SST) that is measured concurrently with the in-water CO2 measurement. To create a climatology of fCO2 data suitable for calculating air–sea CO2 fluxes, it is therefore desirable to calculate fCO2 valid for a more consistent and averaged SST. This paper presents the OceanFlux Greenhouse Gases methodology for creating such a climatology. We recomputed SOCAT's fCO2 values for their respective measurement month and year using monthly composite SST data on a 1° × 1° grid from satellite Earth observation and then extrapolated the resulting fCO2 values to reference year 2010. The data were then spatially interpolated onto a 1° × 1° grid of the global oceans to produce 12 monthly fCO2 distributions for 2010, including the prediction errors of fCO2 produced by the spatial interpolation technique. The partial pressure of CO2 (pCO2) is also provided for those who prefer to use pCO2. The CO2 concentration difference between ocean and atmosphere is the thermodynamic driving force of the air–sea CO2 flux, and hence the presented fCO2 distributions can be used in air–sea gas flux calculations together with climatologies of other climate variables

Exploiting satellite earth observation to quantify current global oceanic DMS flux and its future climate sensitivity

We used coincident Envisat RA2 and AATSR temperature and wind speed data from 2008/2009 to calculate the global net sea-air flux of dimethyl sulfide (DMS), which we estimate to be 19.6 Tg S a21. Our monthly flux calculations are compared to open ocean eddy correlation measurements of DMS flux from 10 recent cruises, with a root mean square difference of 3.1 lmol m22 day21. In a sensitivity analysis, we varied temperature, salinity, surface wind speed, and aqueous DMS concentration, using fixed global changes as well as CMIP5 model output. The range of DMS flux in future climate scenarios is discussed. The CMIP5 model predicts a reduction in surface wind speed and we estimate that this will decrease the global annual sea-air flux of DMS by 22% over 25 years. Concurrent changes in temperature, salinity, and DMS concentration increase the global flux by much smaller amounts. The net effect of all CMIP5 modelled 25 year predictions was a 19% reduction in global DMS flux. 25 year DMS concentration changes had significant regional effects, some positive (Southern Ocean, North Atlantic, Northwest Pacific) and some negative (isolated regions along the Equator and in the Indian Ocean). Using satellite-detected coverage of coccolithophore blooms, our estimate of their contribution to North Atlantic DMS emissions suggests that the coccolithophores contribute only a small percentage of the North Atlantic annual flux estimate, but may be more important in the summertime and in the northeast Atlantic

Satellite observations are needed to understand ocean acidification and multi-stressor impacts on fish stocks in a changing Arctic Ocean

This is the final version. Available from Frontiers Media via the DOI in this record. It is widely projected that under future climate scenarios the economic importance of Arctic Ocean fish stocks will increase. The Arctic Ocean is especially vulnerable to ocean acidification and already experiences low pH levels not projected to occur on a global scale until 2100. This paper outlines how ocean acidification must be considered with other potential stressors to accurately predict movement of fish stocks toward, and within, the Arctic and to inform future fish stock management strategies. First, we review the literature on ocean acidification impacts on fish, next we identify the main obstacles that currently preclude ocean acidification from Arctic fish stock projections. Finally, we provide a roadmap to describe how satellite observations can be used to address these gaps: improve knowledge, inform experimental studies, provide regional assessments of vulnerabilities, and implement appropriate management strategies. This roadmap sets out three inter-linked research priorities: (1) Establish organisms and ecosystem physiochemical baselines by increasing the coverage of Arctic physicochemical observations in both space and time; (2) Understand the variability of all stressors in space and time; (3) Map life histories and fish stocks against satellite-derived observations of stressors.European Space AgencyAXA XL Ocean Risk Scholarshi

FluxEngine: A Flexible Processing System for Calculating Atmosphere–Ocean Carbon Dioxide Gas Fluxes and Climatologies

The air–sea flux of greenhouse gases [e.g., carbon dioxide (CO2)] is a critical part of the climate system and a major factor in the biogeochemical development of the oceans. More accurate and higher-resolution calcu- lations of these gas fluxes are required if researchers are to fully understand and predict future climate. Satellite Earth observation is able to provide large spatial-scale datasets that can be used to study gas fluxes. However, the large storage requirements needed to host such data can restrict its use by the scientific com- munity. Fortunately, the development of cloud computing can provide a solution. This paper describes an open-source air–sea CO2 flux processing toolbox called the ‘‘FluxEngine,’’ designed for use on a cloud- computing infrastructure. The toolbox allows users to easily generate global and regional air–sea CO2 flux data from model, in situ, and Earth observation data, and its air–sea gas flux calculation is user configurable. Its current installation on the Nephalae Cloud allows users to easily exploit more than 8 TB of climate-quality Earth observation data for the derivation of gas fluxes. The resultant netCDF data output files contain .20 data layers containing the various stages of the flux calculation along with process indicator layers to aid interpretation of the data. This paper describes the toolbox design, which verifies the air–sea CO2 flux calculations; demon- strates the use of the tools for studying global and shelf sea air–sea fluxes; and describes future developments

Observing temporally varying synoptic‐scale total alkalinity and dissolved inorganic carbon in the Arctic Ocean

This is the final version. Available from Wiley via the DOI in this record. Data Availability Statement: The matchup database “OceanSODA-MDB” which was used in the algorithm evaluation is available at https:// data-cersat.ifremer.fr/data/ocean-carbonate/oceansoda-mmdb/ (Land et al., 2023; Land & Piollé, 2022). The python code used to run the analysis can be found at https://doi.org/10.5281/zenodo.10067204 (Green et al., 2023) and was adapted from DOI: https://doi.org/10.5281/zenodo.10069611 (Sims et al., 2022).The long-term absorption by the oceans of atmospheric carbon dioxide is leading to the slow decline of ocean pH, a process termed ocean acidification (OA). The Arctic is a challenging region to gather enough data to examine the changes in carbonate chemistry over sufficient scales. However, algorithms that calculate carbonate chemistry parameters from more frequently measured parameters, such as temperature and salinity, can be used to fill in data gaps. Here, these published algorithms were evaluated against in situ measurements using different data input types (data from satellites or in situ re-analysis climatologies) across the Arctic Ocean. With the lowest uncertainties in the Atlantic influenced Seas (AiS), where re-analysis inputs achieved total alkalinity estimates with Root Mean Squared Deviation (RMSD) of 21 μmol kg−1 and a bias of 2 μmol kg−1 (n = 162) and dissolved inorganic carbon RMSD of 24 μmol kg−1 and bias of −14 μmol kg−1 (n = 262). AiS results using satellite observation inputs show similar bias but larger RMSD, although due to the shorter time span of available satellite observations, more contemporary in situ data would provide further assessment and improvement. Synoptic-scale observations of surface water carbonate conditions in the Arctic are now possible to monitor OA, but targeted in situ data collection is needed to enable the full exploitation of satellite observation-based approaches.European Space AgencyAXA XLJoint Transnational Call on Next Generation Climate Science in Europe for the Ocea

Threshold indicators of primary production in the north-east Atlantic for assessing environmental disturbances using 21 years of satellite ocean colour

Primary production (PP) is highly sensitive to changes in the ecosystem and can be used as an early warning indicator for disturbance in the marine environment. Historic indicators of good environmental status of the north-east (NE) Atlantic and north-west (NW) European Seas suggested that daily PP should not exceed 2–3gCm−2 d−1 during phytoplankton blooms and that annual rates should be <300 g C m−2 yr−1 . We use 21 years of Copernicus Marine Service (CMEMS) Ocean Colour data from September 1997 to December 2018 to assess areas in the NE Atlantic with similar peak, climatology, phenology and annual PP values. Daily and annual thresholds of the 90th percentile (P90) of PP are defined for these areas and PP values above these thresholds indicate disturbances, both natural and anthropogenic, in the marine environment. Two case studies are used to test the validity and accuracy of these thresholds. The first is the eruption of the volcano Eyjafjallajökull, which deposited large volumes of volcanic dust (and therefore iron) into the NE Atlantic during April and May 2010. A clear signature in both PP and chlorophyll-a (Chl a) was evident from 28th April to 6th May and from 18th to 27th May 2010, when PP exceeded the PP P90 threshold for the region, which was comparatively more sensitive than Chl a P90 as an indicator of this disturbance. The second case study was for the riverine input of total nitrogen and phosphorus, along the Wadden Sea coast in the North Sea. During years when total nitrogen and phosphorus were above the climatology maximum, there was a lag signature in both PP and Chl a when PP exceeded the PP P90 threshold defined for the study area which was slightly more sensitive than Chl a P90. This technique represents an accurate means of determining disturbances in the environment both in the coastal and offshore waters in the NE Atlantic using remotely sensed ocean colour data