Operational monitoring and forecasting of bathing water quality through exploiting satellite Earth observation and models: The AlgaRisk demonstration service

Coastal zones and shelf-seas are important for tourism, commercial fishing and aquaculture. As a result the importance of good water quality within these regions to support life is recognised worldwide and a number of international directives for monitoring them now exist. This paper describes the AlgaRisk water quality monitoring demonstration service that was developed and operated for the UK Environment Agency in response to the microbiological monitoring needs within the revised European Union Bathing Waters Directive. The AlgaRisk approach used satellite Earth observation to provide a near-real time monitoring of microbiological water quality and a series of nested operational models (atmospheric and hydrodynamic-ecosystem) provided a forecast capability. For the period of the demonstration service (2008–2013) all monitoring and forecast datasets were processed in near-real time on a daily basis and disseminated through a dedicated web portal, with extracted data automatically emailed to agency staff. Near-real time data processing was achieved using a series of supercomputers and an Open Grid approach. The novel web portal and java-based viewer enabled users to visualise and interrogate current and historical data. The system description, the algorithms employed and example results focussing on a case study of an incidence of the harmful algal bloom Karenia mikimotoi are presented. Recommendations and the potential exploitation of web services for future water quality monitoring services are discussed.

Satellite estimates of net community production indicate predominance of net autotrophy in the Atlantic Ocean

There is ongoing debate as to whether the oligotrophic ocean is predominantly net autotrophic and acts as a CO2 sink, or net heterotrophic and therefore acts as a CO2 source to the atmosphere. This quantification is challenging, both spatially and temporally, due to the sparseness of measurements. There has been a concerted effort to derive accurate estimates of phytoplankton photosynthesis and primary production from satellite data to fill these gaps; however there have been few satellite estimates of net community production (NCP). In this paper, we compare a number of empirical approaches to estimate NCP from satellite data with in vitro measurements of changes in dissolved O2 concentration at 295 stations in the N and S Atlantic Ocean (including the Antarctic), Greenland and Mediterranean Seas. Algorithms based on power laws between NCP and particulate organic carbon production (POC) derived from 14C uptake tend to overestimate NCP at negative values and underestimate at positive values. An algorithm that includes sea surface temperature (SST) in the power function of NCP and 14C POC has the lowest bias and root-mean square error compared with in vitro measured NCP and is the most accurate algorithm for the Atlantic Ocean. Nearly a 13 year time series of NCP was generated using this algorithm with SeaWiFS data to assess changes over time in different regions and in relation to climate variability. The North Atlantic subtropical and tropical Gyres (NATL) were predominantly net autotrophic from 1998 to 2010 except for boreal autumn/winter, suggesting that the northern hemisphere has remained a net sink for CO2 during this period. The South Atlantic subtropical Gyre (SATL) fluctuated from being net autotrophic in austral spring-summer, to net heterotrophic in austral autumn–winter. Recent decadal trends suggest that the SATL is becoming more of a CO2 source. Over the Atlantic basin, the percentage of satellite pixels with negative NCP was 27%, with the largest contributions from the NATL and SATL during boreal and austral autumn–winter, respectively. Variations in NCP in the northern and southern hemispheres were correlated with climate indices. Negative correlations between NCP and the multivariate ENSO index (MEI) occurred in the SATL, which explained up to 60% of the variability in NCP. Similarly there was a negative correlation between NCP and the North Atlantic Oscillation (NAO) in the Southern Sub-Tropical Convergence Zone (SSTC),which explained 90% of the variability. There were also positive correlations with NAO in the Canary Current Coastal Upwelling (CNRY) and Western Tropical Atlantic (WTRA)which explained 80% and 60% of the variability in each province, respectively. MEI and NAO seem to play a role in modifying phases of net autotrophy and heterotrophy in the Atlantic Ocean.

Seasonal shelf-sea front mapping using satellite ocean colour and temperature to support development of a marine protected area network

Front detection and aggregation techniques were applied to 300m resolution MERIS satellite ocean colour data for the first time, to describe frequently occurring shelf-sea fronts near to the Scottish coast. Medium resolution (1km) thermal and colour data have previously been used to analyse the distribution of surface fronts, though these cannot capture smaller frontal zones or those in close proximity to the coast, particularly where the coastline is convoluted. Seasonal frequent front maps, derived from both chlorophyll and SST data, revealed a number of key frontal zones, a subset of which were based on new insights into the sediment and plankton dynamics provided exclusively by the higher-resolution chlorophyll fronts. The methodology is described for applying colour and thermal front data to the task of identifying zones of ecological importance that could assist the process of defining marine protected areas. Each key frontal zone is analysed to describe its spatial and temporal extent and variability, and possible mechanisms. It is hoped that these tools can provide guidance on the dynamic habitats of marine fauna towards aspects of marine spatial planning and conservation.

Dynamics of air–sea CO2 fluxes in the northwestern European shelf based on voluntary observing ship and satellite observations

From January 2011 to December 2013, we constructed a comprehensive pCO2 data set based on voluntary observing ship (VOS) measurements in the western English Channel (WEC). We subsequently estimated surface pCO2 and air–sea CO2 fluxes in northwestern European continental shelf waters using multiple linear regressions (MLRs) from remotely sensed sea surface temperature (SST), chlorophyll a concentration (Chl a), wind speed (WND), photosynthetically active radiation (PAR) and modeled mixed layer depth (MLD). We developed specific MLRs for the seasonally stratified northern WEC (nWEC) and the permanently well-mixed southern WEC (sWEC) and calculated surface pCO2 with uncertainties of 17 and 16 μatm, respectively. We extrapolated the relationships obtained for the WEC based on the 2011–2013 data set (1) temporally over a decade and (2) spatially in the adjacent Celtic and Irish seas (CS and IS), two regions which exhibit hydrographical and biogeochemical characteristics similar to those of WEC waters. We validated these extrapolations with pCO2 data from the SOCAT and LDEO databases and obtained good agreement between modeled and observed data. On an annual scale, seasonally stratified systems acted as a sink of CO2 from the atmosphere of −0.6 ± 0.3, −0.9 ± 0.3 and −0.5 ± 0.3 mol C m−2 yr−1 in the northern Celtic Sea, southern Celtic sea and nWEC, respectively, whereas permanently well-mixed systems acted as source of CO2 to the atmosphere of 0.2 ± 0.2 and 0.3 ± 0.2 mol C m−2 yr−1 in the sWEC and IS, respectively. Air–sea CO2 fluxes showed important inter-annual variability resulting in significant differences in the intensity and/or direction of annual fluxes. We scaled the mean annual fluxes over these provinces for the last decade and obtained the first annual average uptake of −1.11 ± 0.32 Tg C yr−1 for this part of the northwestern European continental shelf. Our study showed that combining VOS data with satellite observations can be a powerful tool to estimate and extrapolate air–sea CO2 fluxes in sparsely sampled area.

Applications of Satellite Earth Observations section - NEODAAS: Providing satellite data for efficient research

The NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS) provides a central point of Earth Observation (EO) satellite data access and expertise for UK researchers. The service is tailored to individual users’ requirements to ensure that researchers can focus effort on their science, rather than struggling with correct use of unfamiliar satellite data.

Satellite monitoring of harmful algal blooms (HABs) to protect the aquaculture industry

Harmful algal blooms (HABs) can cause sudden and considerable losses to fish farms, for example 500,000 salmon during one bloom in Shetland, and also present a threat to human health. Early warning allows the industry to take protective measures. PML's satellite monitoring of HABs is now funded by the Scottish aquaculture industry. The service involves processing EO ocean colour data from NASA and ESA in near-real time, and applying novel techniques for discriminating certain harmful blooms from harmless algae. Within the AQUA-USERS project we are extending this capability to further HAB species within several European countries.

NEODAAS: Providing satellite data for efficient research

The NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS) provides a central point of Earth Observation (EO) satellite data access and expertise for UK researchers. The service is tailored to individual users’ requirements to ensure that researchers can focus effort on their science, rather than struggling with correct use of unfamiliar satellite data.

An assessment of phytoplankton primary productivity in the Arctic Ocean from satellite ocean color/in situ chlorophyll-abased models

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.

Uncertainty estimates of remote sensing reflectance derived from comparison of ocean color satellite data sets

Assigning uncertainty to ocean-color satellite products is a requirement to allow informed use of these data. Here, uncertainty estimates are derived using the comparison on a 12th-degree grid of coincident daily records of the remote-sensing reflectance RRS obtained with the same processing chain from three satellite missions, MERIS, MODIS and SeaWiFS. The approach is spatially resolved and produces σ, the part of the RRS uncertainty budget associated with random effects. The global average of σ decreases with wavelength from approximately 0.7– 0.9 10−3 sr−1 at 412 nm to 0.05–0.1 10−3 sr−1 at the red band, with uncertainties on σ evaluated as 20–30% between 412 and 555 nm, and 30–40% at 670 nm. The distribution of σ shows a restricted spatial variability and small variations with season, which makes the multi-annual global distribution of σ an estimate applicable to all retrievals of the considered missions. The comparison of σ with other uncertainty estimates derived from field data or with the support of algorithms provides a consistent picture. When translated in relative terms, and assuming a relatively low bias, the distribution of σ suggests that the objective of a 5% uncertainty is fulfilled between 412 and 490 nm for oligotrophic waters (chlorophyll-a concentration below 0.1 mg m−3). This study also provides comparison statistics. Spectrally, the mean absolute relative difference between RRS from different missions shows a characteristic U-shape with both ends at blue and red wavelengths inversely related to the amplitude of RRS. On average and for the considered data sets, SeaWiFS RRS tend to be slightly higher than MODIS RRS, which in turn appear higher than MERIS RRS. Biases between mission-specific RRS may exhibit a seasonal dependence, particularly in the subtropical belt.

Exploring multi-sensor satellite synergies to provide direction to high-resolution along-track altimtery currents

A new approach to compute along-track velocity components by combining altimetry-based across-track components and front directions from remote sensing maps of surface chlorophyll concentration is proposed. The analysis focuses on the South Madagascar region characterized by the strong East Madagascar Current and sharp gradients of surface tracers. The results are compared against in-situ observations from three moorings along the Jason-1 track 196. Accurate information on the total velocity direction is the key factor for obtaining accurate estimates of along-track velocities. Although with some limitations, surface tracer fronts can be successfully used to retrieve such information.

Progress in satellite remote sensing for studying physical processes at the ocean surface and its borders with the atmosphere and sea-ice

Physical oceanography is the study of physical conditions, processes and variables within the ocean, including temperature-salinity distributions, mixing of the water column, waves, tides, currents, and air-sea interaction processes. Here we provide a critical review of how satellite sensors are being used to study physical oceanography processes at the ocean surface and its borders with the atmosphere and sea-ice. The paper begins by describing the main sensor types that are used to observe the oceans (visible, thermal infrared and microwave) and the specific observations that each of these sensor types can provide. We then present a critical review of how these sensors and observations are being used to study i) ocean surface currents, ii) storm surges, iii) sea-ice, iv) atmosphere-ocean gas exchange and v) surface heat fluxes via phytoplankton. Exciting advances include the use of multiple sensors in synergy to observe temporally varying Arctic sea-ice volume, atmosphere- ocean gas fluxes, and the potential for 4 dimensional water circulation observations. For each of these applications we explain their relevance to society, review recent advances and capability, and provide a forward look at future prospects and opportunities. We then more generally discuss future opportunities for oceanography-focussed remote-sensing, which includes the unique European Union Copernicus programme, the potential of the International Space Station and commercial miniature satellites. The increasing availability of global satellite remote-sensing observations means that we are now entering an exciting period for oceanography. The easy access to these high quality data and the continued development of novel platforms is likely to drive further advances in remote sensing of the ocean and atmospheric systems.

Quantum manifestations of scattering orbits in the scaled spectrum of a non-hydrogenic atom in crossed fields

Evidence for scattering closed orbits for the Rydberg electron of the singly excited helium atom in crossed electric and magnetic fields at constant scaled energy and constant scaled electric field strength has been found through a quantum calculation of the photo-excitation spectrum. A particular 3D scattering orbit in a mixed regular and chaotic region has been investigated and the hydrogenic 3D closed orbits composing it identified. To the best of our knowledge, this letter reports the first quantum calculation of the scaled spectrum of a non- hydrogenic atom in crossed fields.

Quantum manifestations of closed orbits in the photoexcitation scaled spectrum of the hydrogen atom in crossed fields

The scaled photoexcitation spectrum of the hydrogen atom in crossed electric and magnetic fields has been obtained by means of accurate quantum mechanical calculation using a new algorithm. Closed orbits in the corresponding classical system have also been obtained, using a new, efficient and practical searching procedure. Two new classes of closed orbit have been identified. Fourier transforming each photoexcitation quantum spectrum to yield a plot against scaled action has allowed direct comparison between peaks in such plots and the scaled action values of closed orbits, Excellent agreement has been found with all peaks assigned.

The closed orbits and the photo-excitation scaled spectrum of the hydrogen atom in crossed fields

In a recent Letter to the Editor (J Rao, D Delande and K T Taylor 2001 J. Phys. B: At. Mol. Opt. Phys. 34 L391-9) we made a brief first report of our quantal and classical calculations for the hydrogen atom in crossed electric and magnetic fields at constant scaled energy and constant scaled electric field strength. A principal point of that communication was our statement that each and every peak in the Fourier transform of the scaled quantum photo-excitation spectrum for scaled energy value epsilon = -0.586 538 871028 43 and scaled electric value (f) over tilde = 0.068 537 846 207 618 71 could be identified with a scaled action value of a found and mapped-out closed orbit up to a scaled action of 20. In this follow-up paper, besides presenting full details of our quantum and classical methods, we set out the scaled action values of all 317 closed orbits involved, together with the geometries of many.