Longwave Radiation Corrections for the OMNI Buoy Network

The inception of a moored buoy network in the northern Indian Ocean in 1997 paved the way for systematic collection of longterm time series observations of meteorological and oceanographic parameters. This buoy network was revamped in 2011 with OMNI (Ocean Moored buoy Network for north Indian Ocean) buoys fitted with additional sensors to better quantify the air-sea fluxes. An inter-comparison of OMNI buoy measurements with the nearby 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 NIOT during 2019 revealed that the accurate and stable amplification of the thermopile voltage records along with the customized data logger in the WHOI system results in better estimations of LWR↓. The offset in NIOT measured LWR↓ is estimated firstly by segregating the LWR↓ during clear sky conditions identified using the downwelling shortwave radiation measurements from the same test station, and secondly, 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.

Sustenance of Indian Moored Buoy Network During COVID-19 Pandemic – A Saga of Perseverance

The moored buoy network in the Indian Ocean revolutionized the observational programs with systematic time-series measurement of in situ data sets from remote marine locations. The real-time meteorological and oceanographic data sets significantly improved the weather forecast and warning services particularly during extreme events since its inception in 1997. The sustenance of the network requires persistent efforts to overcome the multitude of challenges such as vandalism, biofouling, rough weather, corrosion, ship time availability, and telemetry issues, among others. Besides these, the COVID-19 pandemic constrained the normal functioning of activities, mainly by delaying the maintenance of the network that resulted in losing a few expensive buoy system components and precious data sets. However, the improvements in the buoy system, in-house developed data acquisition system, and efforts in ensuring the quality of measurements together with “best practice methods” enabled 73% of the buoy network to be functional even when the cruises were reduced to 33% during the COVID-19 lockdown in 2020. The moored buoys equipped with an Indian buoy data acquisition system triggered high-frequency transmission during the Super cyclone Amphan in May 2020, which greatly helped the cyclone early warning services during the COVID-19 pandemic. The COVID-19 lockdown points toward the reliability and enhanced utility of moored buoy observations particularly when other modes of measurements are limited and necessitates more such platforms to better predict the weather systems. The present study analyzed the enhancement of the buoy program and improvisation of the buoy system that extended the life beyond the stipulated duration and enabled the high-frequency data transmission during cyclones amid the COVID-19 lockdown. The recommendations to better manage the remote platforms specifically in the event of a pandemic based on the operational experience of more than two decades were also presented.

Validation of Sentinel-3A/3B and Jason-3 Altimeter Wind Speeds and Significant Wave Heights Using Buoy and ASCAT Data

This study validated wind speed (WS) and significant wave height (SWH) retrievals from the Sentinel-3A/3B and Jason-3 altimeters for the period of data beginning 31 October 2019 (to 18 September 2019 for Jason-3) using moored buoy data and satellite Meteorological Operational Satellite Program (MetOp-A/B) Advanced Scatterometer (ASCAT) data. The spatial and temporal scales of the collocated data were 25 km and 30 min, respectively. The statistical metrics of root mean square error (RMSE), bias, correlation coefficient (R), and scatter index (SI) were used to validate the WS and SWH accuracy. Validation of WS against moored buoy data indicated errors of 1.19 m/s, 1.13 m/s and 1.29 m/s for Sentinel-3A, Sentinel-3B and Jason-3, respectively. The accuracy of Sentinel-3A/3B WS is better than that of Jason-3. All three altimeters underestimated WS slightly in comparison with the buoy data. Errors in WS at different speeds or SWHs increased slightly as WS or SWH increased. Over time, the accuracy of the Jason-3 altimeter-derived WS improved, whereas that of Sentinel-3A showed no temporal dependence. The WSs of the three altimeters were compared with ASCAT wind data for validation purposes over the global ocean without in situ measurements. On average, the WSs of the three altimeters were lower in comparison with the ASCAT data. The accuracy of the three altimeters was found to be consistent and stable at low/medium speeds but it decreased when the WS exceeded 15 m/s. Validations of SWH against buoy wave data indicated that the accuracy of Jason-3 SWH was better than that of Sentinel-3A/3B. However, the accuracy of all three altimeters decreased when the SWH exceeded 4 m. The accuracy of Sentinel-3A and Jason-3 SWH was temporally stable, whereas that of Sentinel-3B SWH improved over time. Analyses of SWH accuracy as a function of wave period showed that the Jason-3 altimeter was better than the Sentinel-3A/3B altimeters for long-period ocean waves. Generally, the accuracy of WS and SWH data derived by the Sentinel-3A/3B and Jason-3 altimeters satisfies their mission requirements. Overall, the accuracy of WS (SWH) derived by Sentinel-3A/3B (Jason-3) is better than that retrieved by Jason-3 (Sentinel-3A/3B).

Diagnosing and Predicting ENSO SSTA Development from Moored-Buoy and Scatterometer Winds

Accurate real-time knowledge of equatorial Pacific wind stress is critical for monitoring the state of the tropical Pacific Ocean and understanding sea surface temperature anomaly (SSTA) development associated with El Niño–Southern Oscillation (ENSO) events. The tropical Pacific moored-buoy array has been shown to adequately provide this knowledge when operating as designed. Ocean model simulation of equatorial Pacific SSTA by moored-buoy winds reveals that recent western Pacific buoy losses exceed the array’s minimal redundancy. Additional wind measurements are needed to adequately simulate ENSO-related SSTA development when large portions of the moored-buoy array have been lost or decommissioned. Prospects for obtaining this supplemental wind information in real time are evaluated from simulations of central equatorial Pacific SSTA development during 2017 and end-of-year Niño-3.4 conditions during the previous 25 years. Results show that filling multiple-buoy-dropout gaps with winds from a pair of scatterometers (2000–17) achieves simulation accuracy improving upon that available from the moored-buoy array in the case in which large portions of the array are out. Forcing with the reanalysis-product winds most commonly used in recent ENSO studies or the scatterometer measurements (without the buoy winds) degrades simulation accuracy. The utility of having accurate basinwide wind stress information is demonstrated in an examination of the role that easterly weather-scale wind events played in driving the unexpected development of La Niña in 2017 and by showing that wintertime Niño-3.4 conditions can be statistically forecast, with skill comparable to state-of-the-art coupled models, on the basis of accurate knowledge of equatorial Pacific wind variability over spring or summer.