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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.
Longwave Radiation Corrections for the OMNI Buoy NetworkAbstract
The inception of a moored buoy network in the northern Indian Ocean in 1997 paved the way for systematic collection of long-term time series observations of meteorological and oceanographic parameters. This buoy network was revamped in 2011 with Ocean Moored buoy Network for north Indian Ocean (OMNI) buoys fitted with additional sensors to better quantify the air–sea fluxes. An intercomparison of OMNI buoy measurements with the nearby Woods Hole Oceanographic Institution (WHOI) mooring during the year 2015 revealed an overestimation of downwelling longwave radiation (LWR↓). Analysis of the OMNI and WHOI radiation sensors at a test station at National Institute of Ocean Technology (NIOT) during 2019 revealed that the accurate and stable amplification of the thermopile voltage records along with the customized datalogger in the WHOI system results in better estimations of LWR↓. The offset in NIOT measured LWR↓ is estimated first by segregating the LWR↓ during clear-sky conditions identified using the downwelling shortwave radiation measurements from the same test station, and second, finding the offset by taking the difference with expected theoretical clear-sky LWR↓. The corrected LWR↓ exhibited good agreement with that of collocated WHOI measurements, with a correlation of 0.93. This method is applied to the OMNI field measurements and again compared with the nearby WHOI mooring measurements, exhibiting a better correlation of 0.95. This work has led to the revamping of radiation measurements in OMNI buoys and provides a reliable method to correct past measurements and improve estimation of air–sea fluxes in the Indian Ocean.
Significance Statement
Downwelling longwave radiation (LWR↓) is an important climate variable for calculating air–sea heat exchange and quantifying Earth’s energy budget. An intercomparison of LWR↓ measurements between ocean observing platforms in the north Indian Ocean revealed a systematic offset in National Institute of Ocean Technology (NIOT) Ocean Moored buoy Network for north Indian Ocean (OMNI) buoys. The observed offset limited our capability to accurately estimate air–sea fluxes in the Indian Ocean. The sensor measurements were compared with a standard reference system, which revealed problems in thermopile amplifier as the root cause of the offset. This work led to the development of a reliable method to correct the offset in LWR↓ and revamping of radiation measurements in NIOT-OMNI buoys. The correction is being applied to the past measurements from 12 OMNI buoys over 8 years to improve the estimation of air–sea fluxes in the Indian Ocean.
Abstract
The inception of a moored buoy network in the northern Indian Ocean in 1997 paved the way for systematic collection of long-term time series observations of meteorological and oceanographic parameters. This buoy network was revamped in 2011 with Ocean Moored buoy Network for north Indian Ocean (OMNI) buoys fitted with additional sensors to better quantify the air–sea fluxes. An intercomparison of OMNI buoy measurements with the nearby Woods Hole Oceanographic Institution (WHOI) mooring during the year 2015 revealed an overestimation of downwelling longwave radiation (LWR↓). Analysis of the OMNI and WHOI radiation sensors at a test station at National Institute of Ocean Technology (NIOT) during 2019 revealed that the accurate and stable amplification of the thermopile voltage records along with the customized datalogger in the WHOI system results in better estimations of LWR↓. The offset in NIOT measured LWR↓ is estimated first by segregating the LWR↓ during clear-sky conditions identified using the downwelling shortwave radiation measurements from the same test station, and second, finding the offset by taking the difference with expected theoretical clear-sky LWR↓. The corrected LWR↓ exhibited good agreement with that of collocated WHOI measurements, with a correlation of 0.93. This method is applied to the OMNI field measurements and again compared with the nearby WHOI mooring measurements, exhibiting a better correlation of 0.95. This work has led to the revamping of radiation measurements in OMNI buoys and provides a reliable method to correct past measurements and improve estimation of air–sea fluxes in the Indian Ocean.
Significance Statement
Downwelling longwave radiation (LWR↓) is an important climate variable for calculating air–sea heat exchange and quantifying Earth’s energy budget. An intercomparison of LWR↓ measurements between ocean observing platforms in the north Indian Ocean revealed a systematic offset in National Institute of Ocean Technology (NIOT) Ocean Moored buoy Network for north Indian Ocean (OMNI) buoys. The observed offset limited our capability to accurately estimate air–sea fluxes in the Indian Ocean. The sensor measurements were compared with a standard reference system, which revealed problems in thermopile amplifier as the root cause of the offset. This work led to the development of a reliable method to correct the offset in LWR↓ and revamping of radiation measurements in NIOT-OMNI buoys. The correction is being applied to the past measurements from 12 OMNI buoys over 8 years to improve the estimation of air–sea fluxes in the Indian Ocean.
Fast Floating Temperature Sensor Measures SST, Not Wet-Bulb TemperatureAbstract
A small integrated oceanographic thermometer with a nominal response time of 1 s was affixed to a floating hose “sea snake” towed near the bow of a research vessel. The sensor measured the near-surface ocean temperature accurately and in agreement with other platforms. The effect of conduction and evaporation is modeled for a sensor impulsively alternated between water and air. Large thermal mass makes most sea snake thermometers insensitive to temperature impulses. The smaller 1-s thermometer cooled by evaporation, but the sensor never reached the wet-bulb temperature. The cooling was less than 6% of the (~2.7°C) difference between the ocean temperature and the wet-bulb temperature in 99% of 2-s−1 samples. Filtering outliers, such as with a median, effectively removes the evaporative cooling effect from 1- or 10-min average temperatures.
Abstract
A small integrated oceanographic thermometer with a nominal response time of 1 s was affixed to a floating hose “sea snake” towed near the bow of a research vessel. The sensor measured the near-surface ocean temperature accurately and in agreement with other platforms. The effect of conduction and evaporation is modeled for a sensor impulsively alternated between water and air. Large thermal mass makes most sea snake thermometers insensitive to temperature impulses. The smaller 1-s thermometer cooled by evaporation, but the sensor never reached the wet-bulb temperature. The cooling was less than 6% of the (~2.7°C) difference between the ocean temperature and the wet-bulb temperature in 99% of 2-s−1 samples. Filtering outliers, such as with a median, effectively removes the evaporative cooling effect from 1- or 10-min average temperatures.
