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Fulfilling Observing System Implementation Requirements with the Global Drifter ArrayAbstract
The Global Ocean Observing System (GOOS) requirements for in situ surface temperature and velocity measurements call for observations at 5° × 5° resolution. A key component of the GOOS that measures these essential climate variables is the global array of surface drifters. In this study, statistical observing system sampling experiments are performed to evaluate how many drifters are required to achieve the GOOS requirements, both with and without the presence of a completed global tropical moored buoy array at 5°S–5°N. The statistics for these simulations are derived from the evolution of the actual global drifter array. It is concluded that drifters should be deployed within the near-equatorial band even though that band is also in principle covered by the tropical moored array, as the benefits of not doing so are marginal. It is also concluded that an optimal design half-life for the drifters is ~450 days, neglecting external sources of death, such as running aground or being picked up. Finally, it is concluded that comparing the drifter array size to the number of static 5° × 5° open-ocean bins is not an ideal performance indicator for system evaluation; a better performance indicator is the fraction of 5° × 5° open-ocean bins sampled, neglecting bins with high drifter death rates.
Abstract
The Global Ocean Observing System (GOOS) requirements for in situ surface temperature and velocity measurements call for observations at 5° × 5° resolution. A key component of the GOOS that measures these essential climate variables is the global array of surface drifters. In this study, statistical observing system sampling experiments are performed to evaluate how many drifters are required to achieve the GOOS requirements, both with and without the presence of a completed global tropical moored buoy array at 5°S–5°N. The statistics for these simulations are derived from the evolution of the actual global drifter array. It is concluded that drifters should be deployed within the near-equatorial band even though that band is also in principle covered by the tropical moored array, as the benefits of not doing so are marginal. It is also concluded that an optimal design half-life for the drifters is ~450 days, neglecting external sources of death, such as running aground or being picked up. Finally, it is concluded that comparing the drifter array size to the number of static 5° × 5° open-ocean bins is not an ideal performance indicator for system evaluation; a better performance indicator is the fraction of 5° × 5° open-ocean bins sampled, neglecting bins with high drifter death rates.
Abstract
Salinity measurements from drifters constitute an important in situ dataset for the calibration and validation of the sea surface salinity satellite missions. A total of 114 satellite-tracked salinity drifters were deployed within the framework of the first Salinity Processes in the Upper Ocean Regional Study (SPURS) experiment in the subtropical North Atlantic focusing on the period August 2012–April 2014. In this study, a subset of 83 drifters, which provided useful salinity measurements in the central SPURS region from a few weeks to more than one year, is evaluated and an ad hoc quality-control procedure based on previously published work and the new observations is described. It was found that the sampling algorithm of the drifters introduces a predominantly fresh bias in the noise level of the salinity data, probably caused by the presence of air bubbles within the measuring cell. Since such noise is difficult to eliminate using statistical methods, extensive editing was done manually instead. Such quality-control procedures cannot be routinely applied to the real-time data stream from the drifters. Therefore, a revision of the sampling algorithm of the drifter’s salinity sensor is needed. Comparisons of the drifter’s salinity measurements with independent datasets further indicate that the sensor can provide reliable observations for up to one year. Finally, little evidence was found that the quality of the drifter’s salinity measurements depends on the presence of the drogue.
Abstract
Salinity measurements from drifters constitute an important in situ dataset for the calibration and validation of the sea surface salinity satellite missions. A total of 114 satellite-tracked salinity drifters were deployed within the framework of the first Salinity Processes in the Upper Ocean Regional Study (SPURS) experiment in the subtropical North Atlantic focusing on the period August 2012–April 2014. In this study, a subset of 83 drifters, which provided useful salinity measurements in the central SPURS region from a few weeks to more than one year, is evaluated and an ad hoc quality-control procedure based on previously published work and the new observations is described. It was found that the sampling algorithm of the drifters introduces a predominantly fresh bias in the noise level of the salinity data, probably caused by the presence of air bubbles within the measuring cell. Since such noise is difficult to eliminate using statistical methods, extensive editing was done manually instead. Such quality-control procedures cannot be routinely applied to the real-time data stream from the drifters. Therefore, a revision of the sampling algorithm of the drifter’s salinity sensor is needed. Comparisons of the drifter’s salinity measurements with independent datasets further indicate that the sensor can provide reliable observations for up to one year. Finally, little evidence was found that the quality of the drifter’s salinity measurements depends on the presence of the drogue.
On Characterizing Ocean Kinematics from Surface DriftersAbstract
Horizontal kinematic properties, such as vorticity, divergence, and lateral strain rate, are estimated from drifter clusters using three approaches. At submesoscale horizontal length scales
Significance Statement
The purpose of this study is to provide insights and guidance for computing horizontal velocity gradients from clusters (i.e., three or more) of Lagrangian surface ocean drifters. The uncertainty in velocity gradient estimates depends strongly on the shape deformation of drifter clusters by the ocean currents. We propose criteria for drifter cluster length scales and aspect ratios to reduce uncertainties and develop ways of estimating the magnitude of the resulting errors. The findings are applied to a real ocean dataset from the Bay of Bengal.
Abstract
Horizontal kinematic properties, such as vorticity, divergence, and lateral strain rate, are estimated from drifter clusters using three approaches. At submesoscale horizontal length scales
Significance Statement
The purpose of this study is to provide insights and guidance for computing horizontal velocity gradients from clusters (i.e., three or more) of Lagrangian surface ocean drifters. The uncertainty in velocity gradient estimates depends strongly on the shape deformation of drifter clusters by the ocean currents. We propose criteria for drifter cluster length scales and aspect ratios to reduce uncertainties and develop ways of estimating the magnitude of the resulting errors. The findings are applied to a real ocean dataset from the Bay of Bengal.
Abstract
Since 1994 the U.S. Global Drifter Program (GDP) and its international partners cooperating within the Data Buoy Cooperation Panel (DBCP) of the World Meteorological Organization (WMO) and the United Nations Education, Scientific and Cultural Organization (UNESCO) have been deploying drifters equipped with barometers primarily in the extratropical regions of the world’s oceans in support of operational weather forecasting. To date, the impact of the drifter data isolated from other sources has never been studied. This essay quantifies and discusses the effect and the impact of in situ sea level atmospheric pressure (SLP) data from the global drifter array on numerical weather prediction using observing system experiments and forecast sensitivity observation impact studies. The in situ drifter SLP observations are extremely valuable for anchoring the global surface pressure field and significantly contributing to accurate marine weather forecasts, especially in regions where no other in situ observations are available, for example, the Southern Ocean. Furthermore, the forecast sensitivity observation impact analysis indicates that the SLP drifter data are the most valuable per-observation contributor of the Global Observing System (GOS). All these results give evidence that surface pressure observations of drifting buoys are essential ingredients of the GOS and that their quantity, quality, and distribution should be preserved as much as possible in order to avoid any analysis and forecast degradations. The barometer upgrade program offered by the GDP, under which GDP-funded drifters can be equipped with partner-funded accurate air pressure sensors, is a practical example of how the DBCP collaboration is executed. Interested parties are encouraged to contact the GDP to discuss upgrade opportunities.
Abstract
Since 1994 the U.S. Global Drifter Program (GDP) and its international partners cooperating within the Data Buoy Cooperation Panel (DBCP) of the World Meteorological Organization (WMO) and the United Nations Education, Scientific and Cultural Organization (UNESCO) have been deploying drifters equipped with barometers primarily in the extratropical regions of the world’s oceans in support of operational weather forecasting. To date, the impact of the drifter data isolated from other sources has never been studied. This essay quantifies and discusses the effect and the impact of in situ sea level atmospheric pressure (SLP) data from the global drifter array on numerical weather prediction using observing system experiments and forecast sensitivity observation impact studies. The in situ drifter SLP observations are extremely valuable for anchoring the global surface pressure field and significantly contributing to accurate marine weather forecasts, especially in regions where no other in situ observations are available, for example, the Southern Ocean. Furthermore, the forecast sensitivity observation impact analysis indicates that the SLP drifter data are the most valuable per-observation contributor of the Global Observing System (GOS). All these results give evidence that surface pressure observations of drifting buoys are essential ingredients of the GOS and that their quantity, quality, and distribution should be preserved as much as possible in order to avoid any analysis and forecast degradations. The barometer upgrade program offered by the GDP, under which GDP-funded drifters can be equipped with partner-funded accurate air pressure sensors, is a practical example of how the DBCP collaboration is executed. Interested parties are encouraged to contact the GDP to discuss upgrade opportunities.
Abstract
A cluster of 45 drifters deployed in the Bay of Bengal is tracked for a period of four months. Pair dispersion statistics, from observed drifter trajectories and simulated trajectories based on surface geostrophic velocity, are analyzed as a function of drifter separation and time. Pair dispersion suggests nonlocal dynamics at submesoscales of 1–20 km, likely controlled by the energetic mesoscale eddies present during the observations. Second-order velocity structure functions and their Helmholtz decomposition, however, suggest local dispersion and divergent horizontal flow at scales below 20 km. This inconsistency cannot be explained by inertial oscillations alone, as has been reported in recent studies, and is likely related to other nondispersive processes that impact structure functions but do not enter pair dispersion statistics. At scales comparable to the deformation radius L D , which is approximately 60 km, we find dynamics in agreement with Richardson’s law and observe local dispersion in both pair dispersion statistics and second-order velocity structure functions.
Abstract
A cluster of 45 drifters deployed in the Bay of Bengal is tracked for a period of four months. Pair dispersion statistics, from observed drifter trajectories and simulated trajectories based on surface geostrophic velocity, are analyzed as a function of drifter separation and time. Pair dispersion suggests nonlocal dynamics at submesoscales of 1–20 km, likely controlled by the energetic mesoscale eddies present during the observations. Second-order velocity structure functions and their Helmholtz decomposition, however, suggest local dispersion and divergent horizontal flow at scales below 20 km. This inconsistency cannot be explained by inertial oscillations alone, as has been reported in recent studies, and is likely related to other nondispersive processes that impact structure functions but do not enter pair dispersion statistics. At scales comparable to the deformation radius L D , which is approximately 60 km, we find dynamics in agreement with Richardson’s law and observe local dispersion in both pair dispersion statistics and second-order velocity structure functions.
Abstract
Velocity observations near the surface made with Argos satellite-tracked drifters between 1989 and 2002 provide evidence of seasonal currents entering the South China Sea from the Philippine Sea through the Luzon Strait. The drifters cross the strait and reach the interior of the South China Sea only between October and January, with ensemble mean speeds of 0.7 ± 0.4 m s−1 and daily mean westward speeds that can exceed 1.65 m s−1. The majority of the drifters that continued to reside in the South China Sea made the entry within a westward current system located at ∼20°N that crossed the prevailing northward Kuroshio path. In other seasons, the drifters looped across the strait within the Kuroshio and exited along the south coast of Taiwan. During one intrusion event, satellite altimeters indicated that, directly west of the strait, anticyclonic and cyclonic eddies resided, respectively, north and south of the entering drifter track. The surface currents measured by the crossing drifters were much larger than the Ekman currents that would be produced by an 8–10 m s−1 northeast monsoon, suggesting that a deeper westward current system, as seen in historical watermass analyses, was present.
Abstract
Velocity observations near the surface made with Argos satellite-tracked drifters between 1989 and 2002 provide evidence of seasonal currents entering the South China Sea from the Philippine Sea through the Luzon Strait. The drifters cross the strait and reach the interior of the South China Sea only between October and January, with ensemble mean speeds of 0.7 ± 0.4 m s−1 and daily mean westward speeds that can exceed 1.65 m s−1. The majority of the drifters that continued to reside in the South China Sea made the entry within a westward current system located at ∼20°N that crossed the prevailing northward Kuroshio path. In other seasons, the drifters looped across the strait within the Kuroshio and exited along the south coast of Taiwan. During one intrusion event, satellite altimeters indicated that, directly west of the strait, anticyclonic and cyclonic eddies resided, respectively, north and south of the entering drifter track. The surface currents measured by the crossing drifters were much larger than the Ekman currents that would be produced by an 8–10 m s−1 northeast monsoon, suggesting that a deeper westward current system, as seen in historical watermass analyses, was present.
Abstract
Satellite-tracked drifting buoys of the Global Drifter Program have drogues, centered at 15-m depth, to minimize direct wind forcing and Stokes drift. Drogue presence has historically been determined from submergence or tether strain records. However, recent studies have revealed that a significant fraction of drifters believed to be drogued have actually lost their drogues, a problem that peaked in the mid-2000s before the majority of drifters in the global array switched from submergence to tether strain sensors. In this study, a methodology is applied to the data to automatically reanalyze drogue presence based on anomalous downwind ageostrophic motion. Results indicate that the downwind slip of undrogued drifters is approximately 50% higher than previously believed. The reanalyzed results no longer exhibit the dramatic and spurious interannual variations seen in the original data. These results, along with information from submergence/tether strain and transmission frequency variations, are now being used to conduct a systematic manual reevaluation of drogue presence for each drifter in the post-1992 dataset.
Abstract
Satellite-tracked drifting buoys of the Global Drifter Program have drogues, centered at 15-m depth, to minimize direct wind forcing and Stokes drift. Drogue presence has historically been determined from submergence or tether strain records. However, recent studies have revealed that a significant fraction of drifters believed to be drogued have actually lost their drogues, a problem that peaked in the mid-2000s before the majority of drifters in the global array switched from submergence to tether strain sensors. In this study, a methodology is applied to the data to automatically reanalyze drogue presence based on anomalous downwind ageostrophic motion. Results indicate that the downwind slip of undrogued drifters is approximately 50% higher than previously believed. The reanalyzed results no longer exhibit the dramatic and spurious interannual variations seen in the original data. These results, along with information from submergence/tether strain and transmission frequency variations, are now being used to conduct a systematic manual reevaluation of drogue presence for each drifter in the post-1992 dataset.
Conditions for Reliable Divergence Estimates from Drifter TripletsAbstract
Horizontal velocity gradients of a flow field and the related kinematic properties (KPs) of divergence, vorticity, and strain rate can be estimated from dense drifter deployments, e.g., the spatiotemporal average divergence (and other KPs) over a triangular area defined by three drifters and over a given time interval can be computed from the initial and final areas of said triangle. Unfortunately, this computation can be subject to large errors, especially when the triangle shape is far from equilateral. Therefore, samples with small aspect ratios are generally discarded. Here we derive the thresholds on two shape metrics that optimize the balance between retention of good and removal of bad divergence estimates. The primary tool is a high-resolution regional ocean model simulation, where a baseline for the average divergence can be established, so that actual errors are available. A value of 0.2 for the scaled aspect ratio Λ and a value of 0.86π for the largest interior angle θ are found to be equally effective thresholds, especially at scales of 5 km and below. While discarding samples with low Λ or high θ values necessarily biases the distribution of divergence estimates slightly toward positive values, this bias is small compared to (and in the opposite direction of) the Lagrangian sampling bias due to drifters preferably sampling convergence regions. Errors due to position uncertainty are suppressed by the shape-based subsampling. The subsampling also improves the identification of the areas of extreme divergence or convergence. An application to an observational dataset demonstrates that these model-derived thresholds can be effectively used on actual drifter data.
Significance Statement
Divergence in the ocean indicates how fast floating objects in the ocean spread apart, while convergence (negative divergence) captures how fast they accumulate. Measuring divergence in the ocean, however, remains challenging. One method is to estimate divergence from the trajectories of drifting buoys. This study provides guidance under what circumstances these estimates should be discarded because they are too likely to have large errors. The criteria proposed here are less stringent than some of the ad hoc criteria previously used. This will allow users to retain more of their estimates. We consider how position uncertainty affects the reliability of the divergence estimates. An observational dataset collected in the Mediterranean is used to illustrate an application of these reliability criteria.
Abstract
Horizontal velocity gradients of a flow field and the related kinematic properties (KPs) of divergence, vorticity, and strain rate can be estimated from dense drifter deployments, e.g., the spatiotemporal average divergence (and other KPs) over a triangular area defined by three drifters and over a given time interval can be computed from the initial and final areas of said triangle. Unfortunately, this computation can be subject to large errors, especially when the triangle shape is far from equilateral. Therefore, samples with small aspect ratios are generally discarded. Here we derive the thresholds on two shape metrics that optimize the balance between retention of good and removal of bad divergence estimates. The primary tool is a high-resolution regional ocean model simulation, where a baseline for the average divergence can be established, so that actual errors are available. A value of 0.2 for the scaled aspect ratio Λ and a value of 0.86π for the largest interior angle θ are found to be equally effective thresholds, especially at scales of 5 km and below. While discarding samples with low Λ or high θ values necessarily biases the distribution of divergence estimates slightly toward positive values, this bias is small compared to (and in the opposite direction of) the Lagrangian sampling bias due to drifters preferably sampling convergence regions. Errors due to position uncertainty are suppressed by the shape-based subsampling. The subsampling also improves the identification of the areas of extreme divergence or convergence. An application to an observational dataset demonstrates that these model-derived thresholds can be effectively used on actual drifter data.
Significance Statement
Divergence in the ocean indicates how fast floating objects in the ocean spread apart, while convergence (negative divergence) captures how fast they accumulate. Measuring divergence in the ocean, however, remains challenging. One method is to estimate divergence from the trajectories of drifting buoys. This study provides guidance under what circumstances these estimates should be discarded because they are too likely to have large errors. The criteria proposed here are less stringent than some of the ad hoc criteria previously used. This will allow users to retain more of their estimates. We consider how position uncertainty affects the reliability of the divergence estimates. An observational dataset collected in the Mediterranean is used to illustrate an application of these reliability criteria.
Abstract
Wake eddies are important to physical oceanographers because they tend to dominate current variability in the lee of islands. However, their generation and evolution has been difficult to study due to their intermittency. In this study, 2 years of observations from Surface Velocity Program (SVP) drifters are used to calculate relative vorticity (ζ) and diffusivity (κ) in the wake generated by westward flow past the archipelago of Palau. Over 2 years, 19 clusters of five SVP drifters ∼5 km in scale were released from the north end of the archipelago. Out of these, 15 were entrained in the wake. We compare estimates of ζ from both velocity spatial gradients (least squares fitting) and velocity time series (wavelet analysis). Drifters in the wake were entrained in either energetic submesoscale eddies with initial ζ up to 6f, or island-scale recirculation and large-scale lateral shear with ζ ∼ 0.1f. Here f is the local Coriolis frequency. Mean wake vorticity is initially 1.5f but decreases inversely with time (t), while mean cluster scale (L) increases as L ∝ t. Kinetic energy measured by the drifters is comparatively constant. This suggests ζ is predominantly a function of scale, confirmed by binning enstrophy (ζ 2) by inverse scale. We find κ ∝ L 4/3 and upper and lower bounds for L(t) are given by t 3/2 and t 1/2, respectively. These trends are predicted by a model of dispersion due to lateral shear. We argue the observed time dependence of cluster scale and vorticity suggest island-scale shear controls eddy growth in the wake of Palau.
Abstract
Wake eddies are important to physical oceanographers because they tend to dominate current variability in the lee of islands. However, their generation and evolution has been difficult to study due to their intermittency. In this study, 2 years of observations from Surface Velocity Program (SVP) drifters are used to calculate relative vorticity (ζ) and diffusivity (κ) in the wake generated by westward flow past the archipelago of Palau. Over 2 years, 19 clusters of five SVP drifters ∼5 km in scale were released from the north end of the archipelago. Out of these, 15 were entrained in the wake. We compare estimates of ζ from both velocity spatial gradients (least squares fitting) and velocity time series (wavelet analysis). Drifters in the wake were entrained in either energetic submesoscale eddies with initial ζ up to 6f, or island-scale recirculation and large-scale lateral shear with ζ ∼ 0.1f. Here f is the local Coriolis frequency. Mean wake vorticity is initially 1.5f but decreases inversely with time (t), while mean cluster scale (L) increases as L ∝ t. Kinetic energy measured by the drifters is comparatively constant. This suggests ζ is predominantly a function of scale, confirmed by binning enstrophy (ζ 2) by inverse scale. We find κ ∝ L 4/3 and upper and lower bounds for L(t) are given by t 3/2 and t 1/2, respectively. These trends are predicted by a model of dispersion due to lateral shear. We argue the observed time dependence of cluster scale and vorticity suggest island-scale shear controls eddy growth in the wake of Palau.
Abstract
The Minimet is a Lagrangian surface drifter measuring near-surface winds in situ. Ten Minimets were deployed in the Iceland Basin over the course of two field seasons in 2018 and 2019. We compared Minimet wind measurements to coincident ship winds from the R/V Armstrong meteorology package and to hourly ERA5 reanalysis winds and found that the Minimets accurately captured wind variability across a variety of time scales. Comparisons between the ship, Minimets, and ERA5 winds point to significant discrepancies between the in situ wind measurements and ERA5, with the most reasonable explanation being related to spatial offsets of small-scale storm structures in the reanalysis model. After a general assessment of the Minimet performance, we compare estimates of wind power input in the near-inertial band using the Minimet winds and their measured drift to those using ERA5 winds and the Minimet drift. Minimet-derived near-inertial wind power estimates exceed those from Minimet drift combined with ERA5 winds by about 42%. The results highlight the importance of accurately capturing small-scale, high-frequency wind events and suggest that in situ Minimet measurements are beneficial for accurately quantifying near-inertial wind work on the ocean.
Significance Statement
In this study we introduce a novel, freely drifting wind measurement platform, the Minimet. After an initial validation of Minimet sea surface wind measurements against independent wind measurements from a nearby research vessel, we investigate their utility in context of the near-inertial work done by the wind on the ocean, which is important for the ocean’s energy budget. We find Minimet near-inertial wind work estimates exceed those estimated using winds from a state-of-the-art wind product by 42%. Our results indicate that capturing storm events happening on time scales less than 12 h is crucial for accurately quantifying near-inertial wind work on the ocean, making wind measurements from platforms such as the Minimet invaluable for these analyses.
Abstract
The Minimet is a Lagrangian surface drifter measuring near-surface winds in situ. Ten Minimets were deployed in the Iceland Basin over the course of two field seasons in 2018 and 2019. We compared Minimet wind measurements to coincident ship winds from the R/V Armstrong meteorology package and to hourly ERA5 reanalysis winds and found that the Minimets accurately captured wind variability across a variety of time scales. Comparisons between the ship, Minimets, and ERA5 winds point to significant discrepancies between the in situ wind measurements and ERA5, with the most reasonable explanation being related to spatial offsets of small-scale storm structures in the reanalysis model. After a general assessment of the Minimet performance, we compare estimates of wind power input in the near-inertial band using the Minimet winds and their measured drift to those using ERA5 winds and the Minimet drift. Minimet-derived near-inertial wind power estimates exceed those from Minimet drift combined with ERA5 winds by about 42%. The results highlight the importance of accurately capturing small-scale, high-frequency wind events and suggest that in situ Minimet measurements are beneficial for accurately quantifying near-inertial wind work on the ocean.
Significance Statement
In this study we introduce a novel, freely drifting wind measurement platform, the Minimet. After an initial validation of Minimet sea surface wind measurements against independent wind measurements from a nearby research vessel, we investigate their utility in context of the near-inertial work done by the wind on the ocean, which is important for the ocean’s energy budget. We find Minimet near-inertial wind work estimates exceed those estimated using winds from a state-of-the-art wind product by 42%. Our results indicate that capturing storm events happening on time scales less than 12 h is crucial for accurately quantifying near-inertial wind work on the ocean, making wind measurements from platforms such as the Minimet invaluable for these analyses.
