Search

Global estimates of mesoscale vertical velocity remain poorly constrained due to a historical lack of adequate observations on the spatial and temporal scales needed to measure these small magnitude velocities. However, with the wide‐spread and frequent observations collected by the Argo array of autonomous profiling floats, we can now better quantify mesoscale vertical velocities throughout the global ocean. We use the underutilized trajectory data files from the Argo array to estimate the time evolution of isotherm displacement around a float as it drifts at 1,000 m, allowing us to quantify vertical velocity averaged over approximately 4.5 days for that depth level. The resulting estimates have a non‐normal, high‐peak, and heavy‐tail distribution. The vertical velocity distribution has a mean value of (1.9 ± 0.02) × 10−6m s−1and a median value of (1.3 ± 0.2) × 10−7m s−1, but the high‐magnitude events can be up to the order of 10−4m s−1. We find that vertical velocity is highly spatially variable and is largely associated with a combination of topographic features and horizontal flow. These are some of the first observational estimates of mesoscale vertical velocity to be taken across such large swaths of the ocean without assumptions of uniformity or reliance on horizontal divergence. Vertical velocity in the ocean is a fundamental part of how water circulates throughout the globe. This impacts the temperature, salt, nutrients, and currents that make up the ocean. However, vertical velocities are very small and are, therefore, difficult to measure. In particular, the vertical velocities of ocean events that occur on roughly a weekly to monthly time scale (mesoscale) are poorly understood. We have developed a method for estimating these mesoscale vertical velocities across the globe using an array of autonomous robots called Argo floats. Our results show that vertical velocities vary greatly depending on location, with the largest values occurring where there is a combination of relatively shallow ocean depths and larger horizontal velocities. These estimates are some of the first of their kind to be made from observations across such large swaths of the ocean. Five‐day averaged vertical velocities from Argo observations near 1,000 m are non‐normally distributed, with a high peak and heavy tailsMesoscale vertical velocities are on the order of centimeters per day, but high‐magnitude events can be on the order of meters per dayVertical velocities estimated from Argo floats are spatially variable and correlated with topographic features and horizontal surface flow Five‐day averaged vertical velocities from Argo observations near 1,000 m are non‐normally distributed, with a high peak and heavy tails Mesoscale vertical velocities are on the order of centimeters per day, but high‐magnitude events can be on the order of meters per day Vertical velocities estimated from Argo floats are spatially variable and correlated with topographic features and horizontal surface flow

Despite its importance for the global cycling of carbon, there are still large gaps in our understanding of the processes driving annual and seasonal carbon fluxes in the high‐latitude Southern Ocean. This is due in part to a historical paucity of observations in this remote, turbulent, and seasonally ice‐covered region. Here, we use autonomous biogeochemical float data spanning 6 full seasonal cycles and with circumpolar coverage of the Southern Ocean, complemented by atmospheric reanalysis, to construct a monthly climatology of the mixed layer budget of dissolved inorganic carbon (DIC). We investigate the processes that determine the annual mean and seasonal cycle of DIC fluxes in two different zones of the Southern Ocean—the Sea Ice Zone (SIZ) and Antarctic Southern Zone (ASZ). We find that, annually, mixing with carbon‐rich waters at the base of the mixed layer supplies DIC which is, in the ASZ, either used for net biological production or outgassed to the atmosphere. In contrast, in the SIZ, where carbon outgassing and the biological pump are weaker, the surplus of DIC is instead advected northward to the ASZ. In other words, carbon outgassing in the southern Antarctic Circumpolar Current (ACC), which has been attributed to remineralized carbon from deep water upwelled in the ACC, is also due to the wind‐driven transport of DIC from the SIZ. These results stem from the first observation‐based carbon budget of the circumpolar Southern Ocean and thus provide a useful benchmark to evaluate climate models, which have significant biases in this region. The ocean surrounding the frozen continent of Antarctica plays an important role in the global cycling of carbon and is important for the climate of our planet. Despite its importance, there are gaps in our knowledge due to the difficulties involved in collecting data from a remote, seasonally ice‐covered ocean. In this study, we use year‐round data collected by autonomous instruments that can even measure under sea ice. We build a budget of carbon in the surface layer of the ocean, quantifying the different sources and sinks of inorganic carbon. We find that carbon mostly enters the surface layer through mixing with carbon‐rich waters below. In the more stormy, northern part of our study area, this carbon is then either consumed by photosynthesis in the ocean or it is transferred to the atmosphere. In the southernmost region, biological activity and gas transfer at the ocean‐atmosphere interface is hindered by the presence of sea ice and the surplus of carbon is instead transferred north by wind‐driven circulation. Our results show that year‐round measurements of carbon are necessary to understand carbon cycling in the region and we provide a useful product to compare to global simulations of the Earth system. We build a Southern Ocean observation‐based mixed layer inorganic carbon budget with circumpolar coverage and a full seasonal cycleBiological activity and circulation dominate the seasonal variations in mixed layer dissolved inorganic carbonWind‐driven transport from the seasonal ice zone contributes to carbon outgassing in the Antarctic Circumpolar Current We build a Southern Ocean observation‐based mixed layer inorganic carbon budget with circumpolar coverage and a full seasonal cycle Biological activity and circulation dominate the seasonal variations in mixed layer dissolved inorganic carbon Wind‐driven transport from the seasonal ice zone contributes to carbon outgassing in the Antarctic Circumpolar Current

Oceanographic conditions on the continental shelf of the Ross Sea, Antarctica, affect sea ice production, Antarctic Bottom Water formation, mass loss from the Ross Ice Shelf, and ecosystems. Since ship access to the Ross Sea is restricted by sea ice in winter, most upper ocean measurements have been acquired in summer. We report the first multiyear time series of temperature and salinity throughout the water column, obtained with autonomous profiling floats. Seven Apex floats were deployed in 2013 on the midcontinental shelf, and six Air‐Launched Autonomous Micro Observer floats were deployed in late 2016, mostly near the ice shelf front. Between profiles, most floats were parked on the seabed to minimize lateral motion. Surface mixed layer temperatures, salinities, and depths, in winter were −1.8 °C, 34.34, and 250–500 m, respectively. Freshwater from sea ice melt in early December formed a shallow (20 m) surface mixed layer, which deepened to 50–80 m and usually warmed to above −0.5 °C by late January. Upper‐ocean freshening continued throughout the summer, especially in the eastern Ross Sea and along the ice shelf front. This freshening requires substantial lateral advection that is dominated by inflow from melting of sea ice and ice shelves in the Amundsen Sea and by inputs from the Ross Ice Shelf. Changes in upper‐ocean freshwater and heat content along the ice shelf front in summer affect cross‐ice front advection, ice shelf melting, and calving processes that determine the rate of mass loss from the grounded Antarctic Ice Sheet in this sector. Measurements of temperature and salinity in coastal Antarctic waters are generally restricted to summer when sea ice disappears so that ships can operate there. Moored sensors can collect data through winter but are usually deployed below 200–300 m to minimize risk of damage from drifting icebergs. We describe a novel approach, using autonomous profilers deployed by ship and aircraft, to collect data from the seabed to the ocean surface throughout the year. We deployed 13 profilers in the Ross Sea, Antarctica. Most profilers were programmed to sit on the seabed between profiles to minimize drift and to continue profiling even when ice cover prevented their ascent to the surface. As expected, annual changes in upper‐ocean temperature and salinity were closely related to seasonal changes in sea ice. However, the upper ocean continued to freshen even after the sea ice had all melted, suggesting that substantial amounts of freshwater must be coming from ice melting in the adjacent Amundsen Sea. Increasing our understanding of sources of freshwater in the Ross Sea will improve our predictions of this region's changing role in Antarctic sea ice formation, ice loss from the Antarctic Ice Sheet, and Southern Ocean ecosystems. First aircraft deployments of profiling floats near an ice shelf front document heat and freshwater evolution in spring and summerMultiyear time series of Ross Sea upper‐ocean hydrography under sea ice reveal annual cycle and interannual variabilitySummer upper‐ocean freshwater budgets require substantial lateral fluxes of ice melt from the Amundsen Sea, and from the Ross Ice Shelf

Argo‐type profiling floats do not receive satellite positioning while under sea ice. Common practice is to approximate unknown positions by linearly interpolating latitude‐longitude between known positions before and after ice cover, although it has been suggested that some improvement may be obtained by interpolating along contours of planetary‐geostrophic potential vorticity. Profiles with linearly interpolated positions represent 16% of the Southern Ocean Argo data set; consequences arising from this approximation have not been quantified. Using three distinct data sets from the Weddell Gyre—10‐day satellite‐tracked Argo floats, daily‐tracked RAFOS‐enabled floats, and a particle release simulation in the Southern Ocean State Estimate—we perform a data withholding experiment to assess position uncertainty in latitude‐longitude and potential vorticity coordinates as a function of time since last fix. A spatial correlation analysis using the float data provides temperature and salinity uncertainty estimates as a function of distance error. Combining the spatial correlation scales and the position uncertainty, we estimate uncertainty in temperature and salinity as a function of duration of position loss. Maximum position uncertainty for interpolation during 8 months without position data is 116 ± 148 km for latitude‐longitude and 92 ± 121 km for potential vorticity coordinates. The estimated maximum uncertainty in local temperature and salinity over the entire 2,000‐m profiles during 8 months without position data is 0.66 ∘C and 0.15 psu in the upper 300 m and 0.16 ∘C and 0.01 psu below 300 m. Argo‐type profiling floats do not receive GPS positioning while under sea ice. Current common practice is to approximate the unknown position by linearly interpolating between the known positions before and after ice cover. This linear interpolation is not the true path that these floats follow with under the ice. What is the uncertainty of this linear approximation? Float position and velocity decorrelate with time—meaning the linear approximation of position tends to be worse as time increases. In our paper, we address the question of measurement uncertainty as a function of time by breaking the problem into two pieces: the position uncertainty as a function of time and the measurement uncertainty as a function of position. Combining these statistics, we estimate uncertainty as a function of time of position loss for temperature and salinity as well as surface fluxes derived from the Southern Ocean State Estimate. Argo float position uncertainty when lost under sea ice for 8 months was found to be on the order of 100 kmMapping error in salinity and temperature due to 8 months of position loss was found to be 0.15 psu and 0.66 degrees C in the upper oceanMean RMS difference of surface heat and salinity flux between true and interpolated float trajectories was 28.5 W/m2and 1.8 × 10−3kg·m−2·s−1

We report on profiling float technology used in the Southern Ocean Carbon and Climate Observations and Models (SOCCOM) program, a 6 year study of the interaction of ocean physics and the carbon cycle in the Southern Ocean. A central part of this program is to produce and deploy 200 profiling floats equipped with CTD units and chemical sensors capable of measuring dissolved oxygen, nitrate, pH, chlorophyll fluorescence, and particulate backscatter. The performance of the first 63 floats deployed in SOCCOM is examined, and examples of the design criteria used in producing these floats are shown. Some of the sensors require surface measurements to be made in the dark at regular intervals, and the probability of ascending to the sea surface in the dark is estimated as a function of year‐day and latitude. An energy budget derived from laboratory measurements shows that only about 25% of the total energy stored in the batteries is used by the biogeochemical sensors, which bodes well for the long‐term survivability of the floats. The ice‐avoidance algorithm is discussed in detail, and it is shown that it is working as designed and allowing unprecedented numbers of profiles to be collected beneath the wintertime ice cover. The overall reliability of the first group of SOCCOM floats is compared with a much larger ensemble of Argo floats; the results show that the SOCCOM floats are surviving at a rate similar to the Argo floats, which have been shown to have lifetimes in excess of 5 years. SOCCOM is deploying biogeochemical profiling floats in the Southern OceanThe SOCCOM ensemble is surviving at roughly the same rate as a larger group of Argo floats

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 aand particulate organic carbon concentration. The particulate organic carbon concentrations inferred from optical backscatter appear accurate to with 35 mg C m−3or 20%, whichever is larger. Factors affecting the accuracy of the estimated chlorophyll aconcentrations are evaluated. The ocean science community must move toward greater use of autonomous platforms and sensors if we are to extend our knowledge of the effects of climate driven change within the ocean. Essential to this shift in observing strategies is an understanding of the performance that can be obtained from biogeochemical sensors on platforms deployed for years and the procedures used to process data. This is the subject of the manuscript. We show the performance of oxygen, nitrate, pH, and bio‐optical sensors that have been deployed on robotic profiling floats in the Southern Ocean for time periods up to 32 months. Biogeochemical sensors on profiling floats require careful adjustments for sensor calibration error and driftAfter adjustment, biogeochemical sensor data can approach the accuracy found in large data sets such as GLODAPAdjusted sensor data accuracy has relatively little degradation over the many years a profiling float operates

Measurements of pH and nitrate from the Southern Ocean Carbon and Climate Observations and Modeling array of profiling floats were used to assess the ratios of dissolved inorganic carbon (DIC) and nitrate (NO3) uptake during the spring to summer bloom period throughout the Southern Ocean. Two hundred and forty‐three bloom periods were observed by 115 floats from 30°S to 70°S. Similar calculations were made using the Takahashi surface DIC and nitrate climatology. To separate the effects of atmospheric CO2exchange and mixing from phytoplankton uptake, the ratios of changes in DIC to nitrate of surface waters (ΔDIC/ΔNO3) were computed in the Biogeochemical Southern Ocean State Estimate (B‐SOSE) model. Phytoplankton uptake of DIC and nitrate are fixed in B‐SOSE at the Redfield Ratio (RR; 6.6 mol C/mol N). Deviations in the B‐SOSE ΔDIC/ΔNO3must be due to non‐biological effects of CO2gas exchange and mixing. ΔDIC/ΔNO3values observed by floats and in the Takahashi climatology were corrected for the non‐biological effects using B‐SOSE. The corrected, in situ biological uptake ratio (C:N) occurs at values similar to the RR, with two major exceptions. North of 40°S biological DIC uptake is observed with little or no change in nitrate giving high C:N. In the latitude band at 55°S, the Takahashi data give a low C:N value, while floats are high. This may be due to a change in CO2air‐sea exchange in this region from uptake during the Takahashi reference year of 2005 to outgassing of CO2during the years sampled by floats. Phytoplankton take up dissolved inorganic carbon (DIC) and nitrate as they grow. This results in a decrease in DIC and nitrate during the spring through summer bloom periods each year. The ratio of DIC to nitrate uptake is typically near 6.6 mol C/mol N, a value termed the Redfield Ratio (RR). Here, we used sensor data from an array of profiling floats deployed by the Southern Ocean Carbon and Climate Observations and Modeling program in the Southern Ocean to examine the ratio of C:N uptake by phytoplankton during 243 bloom periods from October through February. We find uptake occurred at values near the RR throughout the Southern Ocean, with two exceptions. North of 40°S, C:N ratios exceed the Redfield value, most likely due to phytoplankton production of a gel‐like organic matter deficient in nitrogen. Near 55°S in the Antarctic Southern Zone, an apparent increase in the C:N ratio over the past decade may reflect a change from an air‐sea flux of CO2into the ocean to a flux out of the ocean. Carbon:nitrate uptake ratios by phytoplankton are near the Redfield Ratio in Southern Ocean waters south of 40°SCarbon:nitrate uptake ratios north of 40°S are much higher, likely due to production of dissolved organic matter with little nitrogenA change in air‐sea CO2flux during October to February from a sink in 2005 to a source in recent years may have occurred near 55°S Carbon:nitrate uptake ratios by phytoplankton are near the Redfield Ratio in Southern Ocean waters south of 40°S Carbon:nitrate uptake ratios north of 40°S are much higher, likely due to production of dissolved organic matter with little nitrogen A change in air‐sea CO2flux during October to February from a sink in 2005 to a source in recent years may have occurred near 55°S

This study presents an optimal analysis method for estimating the large‐ and small‐scale components of a field from observations. This technique relies on an iterative generalized least squares procedure to determine the statistics of the small‐scale fluctuations directly from the data and is thus especially valuable when such information is not known a priori. The use of spherical radial basis functions in fitting the large‐scale signal is suggested, particularly when the domain is sufficiently large. Two test cases illustrate several of the properties of this procedure, demonstrate its utility, and provide practical guidelines for its use. This method is then applied to observations collected by the Argo array of profiling floats to produce global gridded absolute geostrophic velocity estimates. Data statistics computed objectively with iterative processLarge‐scale signal fit with spherical radial basis functionsApplication to Argo data to estimate global absolute geostrophic velocities

Over 450 Argo profiling floats equipped with oxygen sensors have been deployed, but no quality control (QC) protocols have been adopted by the oceanographic community for use by Argo data centers. As a consequence, the growing float oxygen data set as a whole is not readily utilized for many types of biogeochemical studies. Here we present a simple procedure that can be used to correct first‐order errors (offset and drift) in profiling float oxygen data by comparing float data to a monthly climatology (World Ocean Atlas 2009). Float specific correction terms for the entire array were calculated. This QC procedure was evaluated by (1) comparing the climatology‐derived correction coefficients to those derived from discrete samples for 14 floats and (2) comparing correction coefficients for seven floats that had been calibrated twice prior to deployment (once in the factory and once in‐house), with the second calibration ostensibly more accurate than the first. The corrections presented here constrain most float oxygen measurements to better than 3% at the surface. A QC procedure for profiling float oxygen data is presented.