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Powerful new tools for working with Argo data

Posted by mmaheigan

· Thursday, June 9th, 2022

No single program has been as transformative for ocean science over the past two decades as Argo: the fleet of robotic instruments that collect measurements of temperature and salinity in the upper 2 km of the ocean around the globe. The Argo program has been instrumental in revealing changes to ocean heat content, global sea level, and patterns of ice melt and precipitation. In addition, Biogeochemical Argo—the branch of the Argo program focused on floats with additional biological and chemical sensors—has recently shed light on topics such as regional patterns of carbon production and export, the magnitude of carbon dioxide air-sea flux in the Southern Ocean (thanks to the SOCCOM project), and the dynamics modulating ocean oxygen concentrations and oxygen minimum zones. While Argo data are publicly available in near-real-time via two Global Data Assembly Centers, there tends to be a steep learning curve for new users seeking to access and utilize the data.

To address this issue, a team led by scientists at NOAA’s Pacific Marine Environmental Laboratory developed a software toolbox available in two programming languages for accessing and visualizing Argo data— OneArgo-Mat for MATLAB and OneArgo-R for R. The toolbox includes functions to identify and download float data that adhere to user-defined time and space constraints, and other optional requirements like sensor type and data mode; plot float trajectories and their current positions; filter and manipulate float data based on quality flags and additional metadata; and create figures (profiles, time series, and sections) displaying physical, biological, and chemical properties measured by floats. Examples of figures created using the OneArgo-Mat toolbox are given below (Figure 1).

Figure 1. Example figures created using the OneArgo-Mat toolbox: (A) the trajectory of a float deployed in the North Atlantic from the R/V Johan Hjort in May of 2019, (B) a time series of dissolved oxygen at 80 dbars from that float, and (C) a vertical section plot of nitrate concentrations along the float track from the surface to 300 dbars. The black contour line in panel C denotes the mixed layer depth (MLD) based on a temperature criterion and the red line denotes the depth of the time series shown in panel B. The effects of seasonal phytoplankton blooms are evident in panel C, with mixed layer shoaling in the spring followed by drawdown of nitrate in the surface ocean. Panel B shows that, as the mixed layer deepens through the winter, the oxygen concentration at 80 dbars increases as a result of the oxygenated surface waters reaching that depth. The MATLAB code to download the required data and create all of these plots is shown (D).

The OneArgo-Mat and OneArgo-R toolboxes are intended for newcomers to Argo data, seasoned users, data managers, and everyone in between. For this reason, toolbox functions are equipped with options to streamline float selection, data processing, and figure creation with minimal user coding, if desired. Alternatively, the toolbox also provides rapid and straightforward access to the entire Argo database for experienced users who simply want to download up-to-date profile data for further processing and analysis. The authors hope these new tools will empower current Argo data users and entrain new users, especially as the US GO-BGC Project and US and international Argo partners move toward a global biogeochemical Argo fleet, which will create myriad new opportunities for novel studies of ocean biogeochemistry.

Authors
Jonathan Sharp – Cooperative Institute for Climate, Ocean, and Ecosystem Studies (CICOES) & NOAA Pacific Marine Environmental Laboratory (PMEL)
Hartmut Frenzel – CICOES & NOAA PMEL
Marin Cornec – University of Washington & NOAA PMEL
Yibin Huang – University of California Santa Cruz & NOAA PMEL
Andrea Fassbender – NOAA PMEL

The ephemeral and elusive COVID blip in ocean carbon

Posted by mmaheigan

· Monday, September 20th, 2021

The global pandemic of the last nearly two years has affected all of us on a daily and long-term basis. Our planet is not exempt from these impacts. Can we see a signal of COVID-related CO₂ emissions reductions in the ocean? In a recent study, Lovenduski et al. apply detection and attribution analysis to output from an ensemble of COVID-like simulations of an Earth system model to answer this question. While it is nearly impossible to detect a COVID-related change in ocean pH, the model produces a unique fingerprint in air-sea DpCO₂ that is attributable to COVID. Challengingly, the large interannual variability in the climate system makes this fingerprint difficult to detect at open ocean buoy sites.

This study highlights the challenges associated with detecting statistically meaningful changes in ocean carbon and acidity following CO₂ emissions reductions, and reminds the reader that it may be difficult to observe intentional emissions reductions — such as those that we may enact to meet the Paris Climate Agreement – in the ocean carbon system.

Figure caption: The fingerprint (pink line) of COVID-related CO2 emissions reductions in global-mean surface ocean pH and air-sea DpCO2, as estimated by an ensemble of COVID-like simulations in an Earth system model. While the pH fingerprint is not particularly exciting, the air-sea DpCO2 fingerprint displays a temporary weakening of the ocean carbon sink in 2021 due to COVID emissions reductions.

Authors:
Nikki Lovenduski (University of Colorado Boulder)
Neil Swart (Canadian Centre for Climate Modeling and Analysis)
Adrienne Sutton (NOAA Pacific Marine Environmental Laboratory)
John Fyfe (Canadian Centre for Climate Modeling and Analysis)
Galen McKinley (Columbia University and Lamont Doherty Earth Observatory)
Chris Sabine (University of Hawai’i at Manoa)
Nancy Williams (University of South Florida)

Bacterial fingerprints as a tool for large-scale functional ecology

Posted by Dina Pandya

· Monday, September 20th, 2021

Unravelling the relationship between biological diversity and ecosystem functions is a timeless question which dates back to the expeditions of Alexander von Humboldt in the early 1800’. At the base of the marine foodweb, marine prokaryotes are essential for ecosystem functioning. Measuring their biogeography and functional traits therefore merits investigation as alterations in their alpha and beta diversities could lead to changes in the fluxes of oceanic biogeochemical cycles that sustain the life on Earth.

In a new article, published in Nature Communications, the authors used the genetic fingerprint of marine bacteria to predict their metabolic profiles from the ice edge to the equator in the Pacific Ocean. Their research showed that low-cost, high-throughput bacterial marker gene data can be used as a tool for large-scale functional ecology. They tackled five hypotheses and show how biological diversity influences functional diversity, and how these are related to energy production in the ocean. The authors, furthermore, highlight how - can be nicely integrated with the physical and chemical sampling programs during global ocean monitoring campaigns such as GO-SHIP and GEOTRACES.

Increasing our understanding how bacterial diversity impacts the functional diversity of ecosystems has also broader implications. For example, bacterial fingerprints can help us to improve marine ecosystem monitoring programs, especially in coastal zones and estuaries where the input of nitrogen is predicted to increase. Assessing the changes in the bacterial diversity can also help to assess the environmental footprint of aquaculture cages, which are a source of nutrients such as carbon, nitrogen and phosphorus and have been shown to deteriorate the water quality and life higher up the food chain.

Figure caption: The P15S GO-SHIP line from the ice-edge to the equator along 170o W in the South Pacific Ocean (a). Sea surface temperatures and salinity (b) and a conceptual picture of the functional prokaryotic and microbial-eukaryotic biogeography (c). In winter heterotrophic prokaryotes (blue rods) recycle the organic matter produced in the summer and autumn months in the high nutrient low chlorophyll (HNLC) region of the Southern Ocean (SO). Turbulence and mixing (curved arrows) in the sub-tropical front (STF) results in high primary productivity (PP) driven by phytoplankton rich in chlorophyll-a (green discs). The South Pacific Subtropical Gyre Province (SPSG) is characterized by nutrient co-limitation, low PP, and higher abundances of photosynthetic prokaryotes (yellow circles). The Pacific Equatorial Divergence (PED) is characterized by equatorial upwelling which results in an increase of the N:P ratio in the mixed layer (MLD) relative to the SPSG (d), and results in increased chlorophyll-a concentrations and PP. The MLD is shown as a thick white line. CTD stations (small gray dots), sampling stations for 16S rRNA data (large gray circles) and shotgun metagenome samples (yellow stars) are shown on panel d.

Authors:
Eric J. Raes (CSIRO Oceans and Atmosphere, Australia; Dalhousie University, Canada)
Kristen Karsh (CSIRO Oceans and Atmosphere, Australia)
Swan L. S. Sow (CSIRO Oceans and Atmosphere, Australia; University of Tasmania, Hobart; NIOZ Royal Netherlands Institute for Sea Research, The Netherlands)
Martin Ostrowski (University of Technology Sydney, Australia)
Mark V. Brown (The University of Newcastle, Australia)
Jodie van de Kamp (CSIRO Oceans and Atmosphere, Australia)
Rita M. Franco-Santos (University of Tasmania, Australia)
Levente Bodrossy (CSIRO Oceans and Atmosphere, Australia)
Anya M. Waite (Dalhousie University, Canada)

Want to read more about the P15S line?

Raes, E. J., Bodrossy, L., Van De Kamp, J., Bissett, A., Ostrowski, M., Brown, M. V., ... & Waite, A. M. (2018). Oceanographic boundaries constrain microbial diversity gradients in the South Pacific Ocean. Proceedings of the National Academy of Sciences, 115(35), E8266-E8275.

Raes, E. J., van de Kamp, J., Bodrossy, L., Fong, A. A., Riekenberg, J., Holmes, B. H., ... & Waite, A. M. (2020). N2 fixation and new insights into nitrification from the ice-edge to the equator in the South Pacific Ocean. Frontiers in Marine Science, 7, 389.

Sow, S. L., Trull, T. W., & Bodrossy, L. (2020). Oceanographic Fronts Shape Phaeocystis Assemblages: A High-Resolution 18S rRNA Gene Survey From the Ice-Edge to the Equator of the South Pacific. Frontiers in microbiology, 11, 1847.

Exploiting phytoplankton as a biosensor for nutrient limitation

Posted by mmaheigan

· Wednesday, September 15th, 2021

In the surface ocean, phytoplankton growth is often limited by a scarcity of key nutrients such as nitrogen, phosphorus, and iron. While this is important, there are methodological and conceptual difficulties in characterizing these nutrient limitations.

A recent paper published in Science Magazine leveraged a global metagenomic dataset from Bio-GO-SHIP to address these challenges. The authors characterized the abundance of genes that confer adaptations to nutrient limitation within the picocyanobacteria Prochlorococcus. Using the relative abundance of these genes as an indicator of nutrient limitation allowed the authors to capture expected regions of nutrient limitation, and novel regions that had not previously been studied. This gene-derived indicator of nutrient limitation matched previous methods of assessing nutrient limitation, such as bottle incubation experiments.

These findings have important implications for the global ocean. Characterizing the impact of nutrient limitation on primary production is especially critical in light of future stratification driven by climate change. In addition, this novel methodological approach allows scientists to use microbial communities as an eco-genomic biosensor of adaptation to changing nutrient regimes. For instance, future studies of coastal microbes or other ecosystems may help communities and environmental managers better understand how local microbial populations are adapting to climate change.

Watch an illustrated video overview of this research

Authors:
Lucas J. Ustick, Alyse A. Larkin, Catherine A. Garcia, Nathan S. Garcia, Melissa L. Brock, Jenna A. Lee, Nicola A. Wiseman, J. Keith Moore, Adam C. Martiny
(all University of California, Irvine)

Using BGC-Argo to obtain depth-resolved net primary production

Posted by mmaheigan

· Friday, July 23rd, 2021

Net primary production (NPP)—the organic carbon produced by the phytoplankton minus the organic carbon respired by phytoplankton themselves—serves as a major energy source of the marine ecosystem. Traditional methods for measuring NPP rely on ship-based discrete sampling and bottle incubations (e.g., ¹⁴C incubation), which introduce potential artifacts and limit the spatial and temporal data coverage of the global ocean. The global distribution of NPP has been estimated using satellite observations, but the satellite remote sensing approach cannot provide direct information at depth.

Figure 1. Panel A. Trajectories of 5 BGC-Argo and 1 SOS-Argo with the initial float deployment locations denoted by filled symbols. The dash-line at 47° N divided the research area into the northern (temperate) and southern (subtropical) regions. Stars indicate ship stations where ¹⁴C NPP values were measured during NAAMES cruises and compared with NPP from nearby Argo floats. Panels B and C. Monthly climatologies of net primary production (NPP, mmol m^-3 d^-1) profiles in the northern and southern regions of the research area, derived from BGC-Argo measurements using the PPM model. The shadings indicate one standard deviation. The red dotted line indicates mixed layer depth (MLD, m), and the yellow dashed line shows euphotic depth (Z_1%, m).

To fill this niche, a recent study in Journal of Geophysical Research: Biogeosciences, applied bio-optical measurements from Argo profiling floats to study the year-round depth-resolved NPP of the western North Atlantic Ocean (39° N to 54° N). The authors calculated NPP with two bio-optical models (Carbon-based Productivity Model, CbPM; and Photoacclimation Productivity Model, PPM). A comparison with NPP profiles from ¹⁴C incubation measurements showed advantages and limitations of both models. CbPM reproduced the magnitude of NPP in most cases, but had artifacts in the summer (a large NPP peak in the subsurface) due to the subsurface chlorophyll maximum caused by photoacclimation. PPM avoided the artifacts in the summer from photoacclimation, but the magnitude of PPM-derived NPP was smaller than the ¹⁴C result. Latitudinally varying NPP were observed, including higher winter NPP/lower summer NPP in the south, timing differences in NPP seasonal phenology, and different NPP depth distribution patterns in the summer months. With a 6-month record of concurrent oxygen and bio-optical measurements from two Argo floats, the authors also demonstrated the ability of Argo profiling floats to obtain estimates of the net community production (NCP) to NPP ratio (f-ratio), ranging from 0.3 in July to -1.0 in December 2016.

This work highlights the utility of float bio-optical profiles in comparison to traditional measurements and indicates that environmental conditions (e.g. light availability, nutrient supply) are major factors controlling the seasonality and spatial (horizontal and vertical) distributions of NPP in the western North Atlantic Ocean.

Authors:
Bo Yang (University of Virginia, UM CIMAS/NOAA AOML)
James Fox (Oregon State University)
Michael J. Behrenfeld (Oregon State University)
Emmanuel S. Boss (University of Maine)
Nils Haëntjens (University of Maine)
Kimberly H. Halsey (Oregon State University)
Steven R. Emerson (University of Washington)
Scott C. Doney (University of Virginia)

When GEOTRACES‐based synthesis efforts improve global iron-cycling understanding

Posted by mmaheigan

· Friday, December 18th, 2020

Authors of a recent paper published in Global Biogeochemical Cycles conducted a detailed study of the residence times of total and dissolved iron (Fe) in the upper layers (0-250m) of the global ocean. Using historical (1980-2007) and recent GEOTRACES data, they compiled an impressive data set comprising dissolved, filtered and trap-collected particulate Fe spanning different biogeochemical oceanographic provinces. They also used indirect isotopic approaches to calculate Fe export from the surface layers (e.g., based on thorium-234-uranium-238 disequilibrium). The study revealed that upper ocean residence times of total Fe consistently fell between 10 and 100 days, despite a broad range of total Fe inventories and ocean biogeochemical settings. Conversely, dissolved Fe residences times were longer and more variable, cycling on sub annual to annual time scales. In addition to these detailed insights on upper ocean Fe cycling, these new data sets will help constrain the rate constant for total Fe export, an important term for exploring links between ocean Fe cycling and the global carbon cycle in ocean biogeochemical models.

Figure Caption: In-situ iron concentration and export (F_tot) estimates from numerous GEOTRACES efforts were combined with prior study results to constrain the residence time of iron in the upper ocean (diagonal lines, lower panel). Broad patterns in iron residence times emerged when contrasting coastal and open regions (pink vs. white), as well as with high and low latitude zones (black vs. white). Despite clear regional differences, however, the majority of residence times for total iron fell into a small range between 10 and 100 days.

Authors:
E. E. Black (former WHOI, current Dalhousie University, Lamont Doherty Earth Observatory)
S. S. Kienast (Dalhousie University)
N. Lemaitre (Institute of Geochemistry and Petrology, Zürich, Switzerland)
P. J. Lam (University of California, Santa Cruz)
R. F. Anderson (Lamont Doherty Earth Observatory)
H. Planquette (University Brest)
F. Planchon (University Brest)
K. O. Buesseler (WHOI)

This is a joint highlight with GEOTRACES

How zooplankton control carbon export in the Southern Ocean

Posted by mmaheigan

· Thursday, December 3rd, 2020

The Southern Ocean exhibits an inverse relationship between surface primary production and export flux out of the euphotic zone. The causes of this production-export decoupling are still under debate. A recently published mini review in Frontiers in Marine Science focused on zooplankton, an important component of Southern Ocean food webs and the biological pump. The authors compared carbon export regimes from the naturally iron-fertilised Kerguelen Plateau (high surface production, but generally low export) with the iron-limited and less productive high nutrient, low chlorophyll (HNLC) waters south of Australia, where carbon export is relatively high.

Figure 1: The role of zooplankton in establishing the characteristic export regimes at two sites in the Southern Ocean, (a) the highly productive northern Kerguelen Plateau, which exhibits low export, and (b) the iron-limited waters south of Australia with low production, but relatively high carbon export.

Size structure and zooplankton grazing pressure are found to shape carbon export at both sites. On the Kerguelen Plateau, a large size spectrum of zooplankton acts as “gate-keeper” to the mesopelagic by significantly reducing the sinking flux of phytoaggregates, which establishes the characteristic low export regime. In the HNLC waters, however, the zooplankton community is low in biomass and grazes predominantly on smaller particles, which leaves the larger particles for export and leads to relatively high export flux.

Gaps in knowledge related to insufficient seasonal data coverage, understudied carbon flux pathways, and associated mesopelagic processes limit our current understanding of carbon transfer through the water column and export. More integrated data collection efforts, including the use of autonomous profiling floats (e.g., BGC-Argo), stationary moorings, etc., will improve seasonal carbon flux data coverage, thus enabling more reliable estimation of carbon export and storage in the Southern Ocean and improved projection of future changes in carbon uptake and atmospheric carbon dioxide levels.

Authors:
Svenja Halfter (University of Tasmania)
Emma Cavan (Imperial College London)
Ruth Eriksen (CSIRO)
Kerrie Swadling (University of Tasmania)
Philip Boyd (University of Tasmania)

Water clarity impacts temperature and biogeochemistry in Chesapeake Bay

Posted by mmaheigan

· Thursday, December 3rd, 2020

Estuarine water clarity is determined by suspended materials in the water, including colored dissolved organic matter, phytoplankton, sediment, and detritus. These constituents directly affect temperature because when water is opaque, sunlight heats only the shallowest layers near the surface, but when water is clear, sunlight can penetrate deeper, warming the waters below the surface. Despite the importance of accurately predicting temperature variability, many numerical modeling studies do not adequately parameterize this fundamental relationship between water clarity and temperature.

In a recent study published in Estuaries and Coasts, the authors quantified the impact of a more realistic representation of water clarity in a hydrodynamic-biogeochemical model of the Chesapeake Bay by comparing two simulations: (1) water clarity is constant in space and time for the calculation of solar heating vs. (2) water clarity varies with modeled concentrations of light-attenuating materials. In the variable water clarity simulation (2), the water is more opaque, particularly in the northern region of the Bay. During the spring and summer months, the lower water clarity in the northern Bay is associated with warmer surface temperatures and colder bottom temperatures. Warmer surface temperatures encourage phytoplankton growth and nutrient uptake near the head of the Bay, thus fewer nutrients are transported downstream. These conditions are exacerbated during high-river flow years, when differences in temperature, nutrients, phytoplankton, and zooplankton extend further seaward.

Figure 1: Top row: Difference in the light attenuation coefficient for shortwave heating, kh[m-1] (variable minus constant light attenuation simulation). June, July, and August average for (A) 2001, (B) average of 2001-2005, and (C) 2003; difference in bottom temperatures [oC] (variable minus constant). Bottom row: Difference in June, July, and August average bottom temperature for (D) 2001, (E) average of 2001-2005, and (F) 2003. Data for 2001 are representative of low river discharge, and 2003 are representative high river discharge years.

This work demonstrates that a constant light attenuation scheme for heating calculations in coupled hydrodynamic-biogeochemical models underestimates temperature variability, both temporally and spatially. This is an important finding for researchers who use models to predict future temperature variability and associated impacts on biogeochemistry and species habitability.

Authors:
Grace E. Kim (NASA, Goddard Space Flight Center)
Pierre St-Laurent (VIMS, William & Mary)
Marjorie A.M. Friedrichs (VIMS, William & Mary)
Antonio Mannino (NASA, Goddard Space Flight Center)

Tiny phytoplankton seen from space

Posted by mmaheigan

· Thursday, November 19th, 2020

Picophytoplankton, the smallest phytoplankton on Earth, are dominant in over half of the global surface ocean, growing in low-nutrient “ocean deserts” where diatoms and other large phytoplankton have difficult to thrive. Despite their small size, picophytoplankton collectively account for well over 50% of primary production in oligotrophic waters, thus playing a major role in sustaining marine food webs.

In a recent paper published in Optics Express, the authors use satellite-detected ocean color (namely remote-sensing reflectance, R_rs(λ)) and sea surface temperature to estimate the abundance of the three picophytoplankton groups—the cyanobacteria Prochlorococcus and Synechococcus, and autotrophic picoeukaryotes. The authors analysed R_rs(λ) spectra using principal component analysis, and principal component scores and SST were used in the predictive models. Then, they trained and independently evaluated the models with in-situ data from the Atlantic Ocean (Atlantic Meridional Transect cruises). This approach allows for the satellite detection of the succession of species across ocean oligotrophic ecosystem boundaries, where these cells are most abundant (Figure 1).

Figure 1. Cell abundances of the three major picophytoplankton groups (the cyanobacteria Prochlorococcus and Synechococcus, and a collective group of autotrophic picoeukaryotes) in surface waters of the Atlantic Ocean. Abundances are shown for the dominant group in terms of total biovolume (converted from cell abundance).

Since these organisms can be used as proxies for marine ecosystem boundaries, this method can be used in studies of climate and ecosystem change, as it allows a synoptic observation of changes in picophytoplankton distributions over time and space. For exploring spectral features in hyperspectral R_rs(λ) data, the implementation of this model using data from future hyperspectral satellite instruments such as NASA PACE’s Ocean Color Instrument (OCI) will extend our knowledge about the distribution of these ecologically relevant phytoplankton taxa. These observations are crucial for broad comprehension of the effects of climate change in the expansion or shifts in ocean ecosystems.

Authors:
Priscila K. Lange (NASA Goddard Space Flight Center / Universities Space Research Association / Blue Marble Space Institute of Science)
Jeremy Werdell (NASA Goddard Space Flight Center)
Zachary K. Erickson (NASA Goddard Space Flight Center)
Giorgio Dall’Olmo (Plymouth Marine Laboratory)
Robert J. W. Brewin (University of Exeter)
Mikhail V. Zubkov (Scottish Association for Marine Science)
Glen A. Tarran (Plymouth Marine Laboratory)
Heather A. Bouman (University of Oxford)
Wayne H. Slade (Sequoia Scientific, Inc)
Susanne E. Craig (NASA Goddard Space Flight Center / Universities Space Research Association)
Nicole J. Poulton (Bigelow Laboratory for Ocean Sciences)
Astrid Bracher (Alfred-Wegener-Institute Helmholtz Center for Polar and Marine Research / University of Bremen)
Michael W. Lomas (Bigelow Laboratory for Ocean Sciences)
Ivona Cetinić (NASA Goddard Space Flight Center / Universities Space Research Association)

Timing matters: Correcting float-based measurements of diurnal oxygen variability

Posted by mmaheigan

· Friday, November 6th, 2020

Despite its fundamental importance to the global carbon cycle, climate, and marine ecosystems, oceanic primary production is grossly under-sampled. Autonomous platforms represent an important frontier for expanding measurements of marine primary productivity in time and space, but this requires the establishment of robust, standardized methods to obtain reliable data from these platforms. Using data from profiling floats deployed in the northern Gulf of Mexico, authors of a recent study published in Biogeosciences demonstrated, for the first time, that daily cycles of dissolved oxygen can be observed with Argo-type profiling floats. The floats were instructed to profile continuously, resulting in about one profile every three hours. The floats recorded data both on the ascent (upcast) and the descent (downcast). Adjacent casts showed hysteresis in gradient areas, i.e. a lag in the concentration measurement, due to the slow response time of oxygen sensors.

Figure 1: Example of raw oxygen measurements from a downcast (dark purple line) and an upcast (dark green line) and corrected profiles (lighter purple and green lines) in (a) density and (b) pressure coordinates. (c) Upcasts and downcasts (top 150 m) plotted against each other with raw data (purple) and data corrected according to the new method (red). (d) The root-mean-square difference (RMSD) between the upcast and downcast after correcting casts for a range of time constants (τ), showing an optimal τ value in this case of 76 s (red dot).

To correct for these measurement errors, the authors developed a method to determine sensor response time in situ, using an established process for correcting sensor response time errors. This method requires a timestamp associated with each observation. The response time parameter (τ) was determined by correcting consecutive profiles taken in opposite directions using a range of possible values and finding the minimum root-mean-square-difference between them (Figure 1). In light of these findings, future oxygen measurements from Argo floats should be transmitted with time stamps for a calibration period during which up- and downcasts are recorded to facilitate response time correction. The method developed here will contribute to more accurate measurement of dissolved oxygen, thus improving the quality of derived quantities such as primary productivity.

Authors
Christopher Gordon (Dalhousie University)
Katja Fennel (Dalhousie University)
Clark Richards (Fisheries and Oceans Canada)
Nick Shay (University of Miami)
Jodi Brewster (University of Miami)

Funding for the Ocean Carbon & Biogeochemistry Project Office is provided by the National Science Foundation (NSF) and the National Aeronautics and Space Administration (NASA). The OCB Project Office is housed at the Woods Hole Oceanographic Institution.

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