A Novel Integration of an Ultraviolet Nitrate Sensor On Board a Towed Vehicle for Mapping Open-Ocean Submesoscale Nitrate Variability

Pidcock, Rosalind; Srokosz, Meric; Allen, John T.; Hartman, M.C.; Painter, Stuart C.; Mowlem, Matthew C.; Hydes, D.J.; Martin, Adrian P.

doi:10.1175/2010jtecho780.1

Cited by 24 publications

(26 citation statements)

References 30 publications

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“…The depth of the nitracline might be weakly modulated by the presence of eddies (as found by Pidcock et al . []); thus, mesoscale structures might influence the DCM indirectly, but such an effect is not clearly seen in Figure . The DCM is not visible in the OPC data, which suggests that it is dominated by different phytoplankton species to those forming the surface bloom.…”

Section: Discussionsupporting

confidence: 88%

The Madagascar Bloom: A serendipitous study

Srokosz

Quartly

2013

JGR Oceans

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[1] The late austral summer (February-April) phytoplankton bloom that occurs east of Madagascar exhibits significant interannual variability and at its largest extent covers~1% of the world's ocean surface area. The bloom raises many intriguing questions about how it begins, is sustained, propagates to the east, exports carbon, and ends. It has been observed and studied using satellite ocean color observations, but the lack of in situ data makes it difficult to address these questions. Here we describe observations that were made serendipitously on a cruise in February 2005. These show clearly for the first time the simultaneous existence of a deep chlorophyll maximum at~70-110 m depths (seen in SeaSoar fluorimeter data) and a surface chlorophyll signature [seen in Sea-viewing Wide Field-of-view Sensor (SeaWiFS) satellite ocean color data]. The observations also show the modulation of the biological signature at the surface by the eddy field but not of the deep chlorophyll maximum. Trichodesmium dominates the bloom nearer to Madagascar, while the diatom Rhizosolenia clevei (and its symbiont Richelia intracellularis) dominates further from the island. The surface bloom seen in the SeaWiFS data is confined to the shallow (~30 m) mixed layer. It is hypothesized that the interannual variability in bloom intensity may be due to variations in coastal upwelling and thus the supply of iron, which is a micronutrient that can limit diazotroph growth.

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Section: Discussionsupporting

confidence: 88%

The Madagascar Bloom: A serendipitous study

Srokosz

Quartly

2013

JGR Oceans

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“…Over much of the ocean, phytoplankton growth is constrained by the availability of nutrients, which are abundant beneath the euphotic zone. The upward component of the submesoscale vertical circulation enhances the nutrient flux into the euphotic layer, stimulating phytoplankton growth (Figure 2a) [ Mahadevan and Archer , 2000; Lévy et al , 2001; Allen et al , 2005; Lapeyre and Klein , 2006; Nagai et al , 2008; Johnson et al , 2010; Pidcock et al , 2010]. Submesoscale upwelling can also drive deep phytoplankton biomass upward, alleviating light limitation of growth [ Lévy et al , 2001].…”

Section: Response Of Phytoplankton To Submesoscale Dynamicsmentioning

confidence: 99%

“…Returning to in situ observations, it has long been a problem that very few biogeochemical properties can be accurately measured using compact autonomous sensors. It is only recently that ultraviolet‐based sensors capable of robust measurements of nitrate with a sensitivity suitable for open ocean biogeochemistry have been developed [ Pidcock et al , 2010; Johnson et al , 2010]. The most exciting development for submesoscale studies, perhaps, is the emergence of lab‐on‐chip technology; the ability to use advanced engineering techniques to build low energy, sophisticated but small sensors, with obvious potential for deployment on any of the platforms discussed above.…”

Section: Observational Considerationsmentioning

confidence: 99%

Bringing physics to life at the submesoscale

Lévy¹,

Ferrari²,

Franks³

et al. 2012

Geophysical Research Letters

403

339

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International audienceA common dynamical paradigm is that turbulence in the upper ocean is dominated by three classes of motion: mesoscale geostrophic eddies, internal waves and microscale three-dimensional turbulence. Close to the ocean surface, however, a fourth class of turbulent motion is important: submesoscale frontal dynamics. These have a horizontal scale of O(1-10) km, a vertical scale of O(100) m, and a time scale of O(1) day. Here we review the physical-chemical-biological dynamics of submesoscale features, and discuss strategies for sampling them. Submesoscale fronts arise dynamically through nonlinear instabilities of the mesoscale currents. They are ephemeral, lasting only a few days after they are formed. Strong submesoscale vertical velocities can drive episodic nutrient pulses to the euphotic zone, and subduct organic carbon into the ocean's interior. The reduction of vertical mixing at submesoscale fronts can locally increase the mean time that photosynthetic organisms spend in the well-lit euphotic layer and promote primary production. Horizontal stirring can create intense patchiness in planktonic species. Submesoscale dynamics therefore can change not only primary and export production, but also the structure and the functioning of the planktonic ecosystem. Because of their short time and space scales, sampling of submesoscale features requires new technologies and approaches. This paper presents a critical overview of current knowledge to focus attention and hopefully interest on the pressing scientific questions concerning these dynamics

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“…At the above ship speed there is a profile roughly every 3–4 km. In addition to standard hydrographic parameters, and of more direct relevance to this study, the vehicle was equipped with a fluorometer (as a proxy for phytoplankton biomass [e.g., Allen et al ., ] and cruises D227 and D321 described below), the National Oceanography Centre developed SUV‐6 nitrate sensor (cruise D321 [ Pidcock et al ., ]), and/or an optical plankton counter (OPC) which can be used to estimate zooplankton abundance (cruise D227 [ Srokosz et al ., ]). Surface values are not used because there is evidence of quenching affecting fluorescence measurements on D321 above 25 m. Details can be found in van Gennip [].…”

Section: Datamentioning

confidence: 99%

“…Cruise D321 [ Allen , ] simultaneously mapped nitrate and phytoplankton using the SUV‐6 and fluorometer mounted on the SeaSoar vehicle, respectively. The SUV‐6 nitrate data were calibrated against bottle samples collected from conductivity‐temperature‐depth casts [ Pidcock et al ., ]. The fluorescence data were uncalibrated, but we assume a linear relationship between fluorescence and phytoplankton biomass.…”

Section: Datamentioning

confidence: 99%

An observational assessment of the influence of mesoscale and submesoscale heterogeneity on ocean biogeochemical reactions

Martin

Lévy

Gennip

et al. 2015

Global Biogeochemical Cycles

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Numerous observations demonstrate that considerable spatial variability exists in components of the marine planktonic ecosystem at the mesoscale and submesoscale (100 km-1 km). The causes and consequences of physical processes at these scales ("eddy advection") influencing biogeochemistry have received much attention. Less studied, the nonlinear nature of most ecological and biogeochemical interactions means that such spatial variability has consequences for regional estimates of processes including primary production and grazing, independent of the physical processes. This effect has been termed "eddy reactions." Models remain our most powerful tools for extrapolating hypotheses for biogeochemistry to global scales and to permit future projections. The spatial resolution of most climate and global biogeochemical models means that processes at the mesoscale and submesoscale are poorly resolved. Modeling work has previously suggested that the neglected eddy reactions may be almost as large as the mean field estimates in some cases. This study seeks to quantify the relative size of eddy and mean reactions observationally, using in situ and satellite data. For primary production, grazing, and zooplankton mortality the eddy reactions are between 7% and 15% of the mean reactions. These should be regarded as preliminary estimates to encourage further observational estimates and not taken as a justification for ignoring eddy reactions. Compared to modeling estimates, there are inconsistencies in the relative magnitude of eddy reactions and in correlations which are a major control on their magnitude. One possibility is that models exhibit much stronger spatial correlations than are found in reality, effectively amplifying the magnitude of eddy reactions.

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A Novel Integration of an Ultraviolet Nitrate Sensor On Board a Towed Vehicle for Mapping Open-Ocean Submesoscale Nitrate Variability

Cited by 24 publications

References 30 publications

The Madagascar Bloom: A serendipitous study

The Madagascar Bloom: A serendipitous study

Bringing physics to life at the submesoscale

An observational assessment of the influence of mesoscale and submesoscale heterogeneity on ocean biogeochemical reactions

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