The Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) program has begun deploying a large array of biogeochemical sensors on profiling floats in the Southern Ocean. As of February 2016, 86 floats have been deployed. Here the focus is on 56 floats with quality‐controlled and adjusted data that have been in the water at least 6 months. The floats carry oxygen, nitrate, pH, chlorophyll fluorescence, and optical backscatter sensors. The raw data generated by these sensors can suffer from inaccurate initial calibrations and from sensor drift over time. Procedures to correct the data are defined. The initial accuracy of the adjusted concentrations is assessed by comparing the corrected data to laboratory measurements made on samples collected by a hydrographic cast with a rosette sampler at the float deployment station. The long‐term accuracy of the corrected data is compared to the GLODAPv2 data set whenever a float made a profile within 20 km of a GLODAPv2 station. Based on these assessments, the fleet average oxygen data are accurate to 1 ± 1%, nitrate to within 0.5 ± 0.5 µmol kg−1, and pH to 0.005 ± 0.007, where the error limit is 1 standard deviation of the fleet data. The bio‐optical measurements of chlorophyll fluorescence and optical backscatter are used to estimate chlorophyll a and particulate organic carbon concentration. The particulate organic carbon concentrations inferred from optical backscatter appear accurate to with 35 mg C m−3 or 20%, whichever is larger. Factors affecting the accuracy of the estimated chlorophyll a concentrations are evaluated.
In nearly a dozen open‐ocean fertilization experiments conducted by more than 100 researchers from nearly 20 countries, adding iron at the sea surface has led to distinct increases in photosynthesis rates and biomass. These experiments confirmed the hypothesis proposed by the late John Martin [Martin, 1990] that dissolved iron concentration is a key variable that controls phytoplankton processes in ocean surface waters However, the measurement of dissolved iron concentration in seawater remains a difficult task [Bruland and Rue, 2001] with significant interlaboratory differences apparent at times. The availability of a seawater reference solution with well‐known dissolved iron (Fe) concentrations similar to open‐ocean values, which could be used for the calibration of equipment or other tasks, would greatly alleviate these problems [National Research Council (NRC), 2002[.
Recently, measurements of oxygen concentration in the ocean-one of the most classical parameters in chemical oceanography-are experiencing a revival. This is not surprising, given the key role of oxygen for assessing the status of the marine carbon cycle and feeling the pulse of the biological pump. The revival, however, has to a large extent been driven by the availability of robust optical oxygen sensors and their painstakingly thorough characterization. For autonomous observations, oxygen optodes are the sensors of choice: They are used abundantly on Biogeochemical-Argo floats, gliders and other autonomous oceanographic observation platforms. Still, data quality and accuracy are often suboptimal, in some part because sensor and data treatment are not always straightforward and/or sensor characteristics are not adequately taken into account. Here, we want to summarize the current knowledge about oxygen optodes, their working principle as well as their behavior with respect to oxygen, temperature, hydrostatic pressure, and response time. The focus will lie on the most widely used and accepted optodes made by Aanderaa and Sea-Bird. We revisit the essentials and caveats of in-situ in air calibration as well as of time response correction for profiling applications, and provide requirements for a successful field deployment. In addition, all required steps to post-correct oxygen optode data will be discussed. We hope this summary will serve as a comprehensive, yet concise reference to help people get started with oxygen observations, ensure successful sensor deployments and acquisition of highest quality data, and facilitate post-treatment of oxygen data. In the end, we hope that this will lead to more and higher-quality oxygen observations and help to advance our understanding of ocean biogeochemistry in a changing ocean.
Abstract. Nitrite (NOwithin the PNM ranged from 18 to 470 days at the mesotrophic station and was 40 days at the oligotrophic station. Our results suggest the PNM is a dynamic, rather than relict, feature with a source term dominated by ammonia oxidation.
Six profiling floats equipped with nitrate and oxygen sensors were deployed at Ocean Station P in the Gulf of Alaska. The resulting six calendar years and 10 float years of nitrate and oxygen data were used to determine an average annual cycle for net community production (NCP) in the top 35 m of the water column. NCP became positive in February as soon as the mixing activity in the surface layer began to weaken, but nearly 3 months before the traditionally defined mixed layer began to shoal from its winter time maximum. NCP displayed two maxima, one toward the end of May and another in August with a summertime minimum in June corresponding to the historical peak in mesozooplankton biomass. The average annual NCP was determined to be 1.5 ± 0.6 mol C m À2 yr À1 using nitrate and 1.5 ± 0.7 mol C m À2 yr À1 using oxygen. The results from oxygen data proved to be quite sensitive to the gas exchange model used as well as the accuracy of the oxygen measurement. Gas exchange models optimized for carbon dioxide flux generally ignore transport due to gas exchange through the injection of bubbles, and these models yield NCP values that are two to three time higher than the nitrate-based estimates. If nitrate and oxygen NCP rates are assumed to be related by the Redfield model, we show that the oxygen gas exchange model can be optimized by tuning the exchange terms to reproduce the nitrate NCP annual cycle.
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