Coccolithophore bloom detection in the north east Atlantic using SeaWiFS: Algorithm description, application and sensitivity analysis

Coccolithophores are the largest source of calcium carbonate in the oceans and are considered to play an important role in oceanic carbon cycles. Current methods to detect the presence of coccolithophore blooms from Earth observation data often produce high numbers of false positives in shelf seas and coastal zones due to the spectral similarity between coccolithophores and other suspended particulates. Current methods are therefore unable to characterise the bloom events in shelf seas and coastal zones, despite the importance of these phytoplankton in the global carbon cycle. A novel approach to detect the presence of coccolithophore blooms from Earth observation data is presented. The method builds upon previous optical work and uses a statistical framework to combine spectral, spatial and temporal information to produce maps of coccolithophore bloom extent. Validation and verification results for an area of the north east Atlantic are presented using an in situ database (N = 432) and all available SeaWiFS data for 2003 and 2004. Verification results show that the approach produces a temporal seasonal signal consistent with biological studies of these phytoplankton. Validation using the in situ coccolithophore cell count database shows a high correct recognition rate of 80% and a low false-positive rate of 0.14 (in comparison to 63% and 0.34 respectively for the established, purely spectral approach). To guide its broader use, a full sensitivity analysis for the algorithm parameters is presented.

ALES: a multi-mission adaptive sub-waveform retracker for coastal and open ocean altimetry

Satellite altimetry has revolutionized our understanding of ocean dynamics thanks to frequent sampling and global coverage. Nevertheless, coastal data have been flagged as unreliable due to land and calm water interference in the altimeter and radiometer footprint and uncertainty in the modelling of high-frequency tidal and atmospheric forcing. Our study addresses the first issue, i.e. altimeter footprint contamination, via retracking, presenting ALES, the Adaptive Leading Edge Subwaveform retracker. ALES is potentially applicable to all the pulse-limited altimetry missions and its aim is to retrack both open ocean and coastal data with the same accuracy using just one algorithm. ALES selects part of each returned echo and models it with a classic ”open ocean” Brown functional form, by means of least square estimation whose convergence is found through the Nelder-Mead nonlinear optimization technique. By avoiding echoes from bright targets along the trailing edge, it is capable of retrieving more coastal waveforms than the standard processing. By adapting the width of the estimation window according to the significant wave height, it aims at maintaining the accuracy of the standard processing in both the open ocean and the coastal strip. This innovative retracker is validated against tide gauges in the Adriatic Sea and in the Greater Agulhas System for three different missions: Envisat, Jason-1 and Jason-2. Considerations of noise and biases provide a further verification of the strategy. The results show that ALES is able to provide more reliable 20-Hz data for all three missions in areas where even 1-Hz averages are flagged as unreliable in standard products. Application of the ALES retracker led to roughly a half of the analysed tracks showing a marked improvement in correlation with the tide gauge records, with the rms difference being reduced by a factor of 1.5 for Jason-1 and Jason-2 and over 4 for Envisat in the Adriatic Sea (at the closest point to the tide gauge).

Monitoring of a quasi-stationary eddy in the Bay of Biscay by means of satellite, in situ and model results

The presence of a quasi-stationary anticyclonic eddy within the southeastern Bay of Biscay (centred around 44°30′N-4°W) has been reported on various occasions in the bibliography. The analysis made in this study for the period 2003–2010, by using in situ and remote sensing measurements and model results shows that this mesoscale coherent structure is present almost every year from the end of winter-beginning of spring, to the beginning of fall. During this period it remains in an area limited to the east by the Landes Plateau, to the west by Le Danois Bank and Torrelavega canyon and to the northwest by the Jovellanos seamount. All the observations and analysis made in this contribution, suggest that this structure is generated between Capbreton and Torrelavega canyons. Detailed monitoring from in situ and remote sensing data of an anticyclonic quasi-stationary eddy, in 2008, shows the origin of this structure from a warm water current located around 43°42′N-3°30′W in mid-January. This coherent structure is monitored until August around the same area, where it has a marked influence on the Sea Level Anomaly, Sea Surface Temperature and surface Chlorophyll-a concentration. An eddy tracking method, applied to the outputs of a numerical model, shows that the model is able to reproduce this type of eddy, with similar 2D characteristics and lifetimes to that suggested by the observations and previous works. This is the case, for instance, of the simulated MAY04 eddy, which was generated in May 2004 around Torrelavega canyon and remained quasi-stationary in the area for 4 months. The diameter of this eddy ranged from 40 to 60 km, its azimuthal velocity was less than 20 cm s−1, its vertical extension reached 3000–3500 m depth during April and May and it was observed to interact with other coherent structures.

Data processing of remotely sensed airborne hyperspectral data using the Airborne Processing Library (APL): Geocorrection algorithm descriptions and spatial accuracy assessment

Remote sensing airborne hyperspectral data are routinely used for applications including algorithm development for satellite sensors, environmental monitoring and atmospheric studies. Single flight lines of airborne hyperspectral data are often in the region of tens of gigabytes in size. This means that a single aircraft can collect terabytes of remotely sensed hyperspectral data during a single year. Before these data can be used for scientific analyses, they need to be radiometrically calibrated, synchronised with the aircraft's position and attitude and then geocorrected. To enable efficient processing of these large datasets the UK Airborne Research and Survey Facility has recently developed a software suite, the Airborne Processing Library (APL), for processing airborne hyperspectral data acquired from the Specim AISA Eagle and Hawk instruments. The APL toolbox allows users to radiometrically calibrate, geocorrect, reproject and resample airborne data. Each stage of the toolbox outputs data in the common Band Interleaved Lines (BILs) format, which allows its integration with other standard remote sensing software packages. APL was developed to be user-friendly and suitable for use on a workstation PC as well as for the automated processing of the facility; to this end APL can be used under both Windows and Linux environments on a single desktop machine or through a Grid engine. A graphical user interface also exists. In this paper we describe the Airborne Processing Library software, its algorithms and approach. We present example results from using APL with an AISA Eagle sensor and we assess its spatial accuracy using data from multiple flight lines collected during a campaign in 2008 together with in situ surveyed ground control points.

Plankton indicators and ocean observing systems: support to the marine ecosystem state assessment

Ecological indicators are used extensively as tools to manage environmental resources. In the oceans, indicators of plankton can be measured using a variety of observing systems including: mooring stations, ships, autonomous floats and ocean colour remote sensing. Given the broad range of temporal and spatial sampling resolutions of these different observing systems, as well as discrepancies in measurements obtained from different sensors, the estimation and interpretation of plankton indicators can present significant challenges. To provide support to the assessment of the state of the marine ecosystem, we propose a suite of plankton indicators and subsequently classify them in an ecological framework that characterizes key attributes of the ecosystem. We present two case studies dealing with plankton indicators of biomass, size structure and phenology, estimated using the most spatially extensive and longest in situ and remote-sensing observations. Discussion of these studies illustrates how some of the challenges in estimating and interpreting plankton indicators may be addressed by using for example relative measurement thresholds, interpolation procedures and delineation of biogeochemical provinces. We demonstrate that one of the benefits attained, when analyzing a suite of plankton indicators classified in an ecological framework, is the elucidation of non-trivial changes in composition, structure and functioning of the marine ecosystem.

Global assessment of ocean carbon export by combining satellite observations and food-web models

The export of organic carbon from the surface ocean by sinking particles is an important, yet highly uncertain, component of the global carbon cycle. Here we introduce a mechanistic assessment of the global ocean carbon export using satellite observations, including determinations of net primary production and the slope of the particle size spectrum, to drive a food-web model that estimates the production of sinking zooplankton feces and algal aggregates comprising the sinking particle flux at the base of the euphotic zone. The synthesis of observations and models reveals fundamentally different and ecologically consistent regional-scale patterns in export and export efficiency not found in previous global carbon export assessments. The model reproduces regional-scale particle export field observations and predicts a climatological mean global carbon export from the euphotic zone of ~6 Pg C yr−1. Global export estimates show small variation (typically < 10%) to factor of 2 changes in model parameter values. The model is also robust to the choices of the satellite data products used and enables interannual changes to be quantified. The present synthesis of observations and models provides a path for quantifying the ocean's biological pump.

Absorption-based algorithm of primary production for total and size-fractionated phytoplankton in coastal waters

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