On the diurnal ranges of Sea Surface Temperature (SST) in the North Indian Ocean

This paper describes the variability in the diurnal range of SST in the north Indian Ocean using in situ measurements and tests the suitability of simple regression models in estimating the diurnal range. SST measurements obtained from 1556 drifting and 25 moored buoys were used to determine the diurnal range of SSTs. The magnitude of diurnal range of SST was highest in spring and lowest in summer monsoon. Except in spring, nearly 75-80% of the observations reported diurnal range below 0.5°C. The distributions of the magnitudes of diurnal warming across the three basins of north Indian Ocean (Arabian Sea, Bay of Bengal and Equatorial Indian Ocean) were similar except for the differences between the Arabian Sea and the other two basins during November-February (winter monsoon) and May. The magnitude of diurnal warming that depended on the location of temperature sensor below the water level varied with seasons. In spring, the magnitude of diurnal warming diminished drastically with the increase in the depth of temperature sensor. The diurnal range estimated using the drifting buoy data was higher than the diurnal range estimated using moored buoys fitted with temperature sensors at greater depths. A simple regression model based on the peak solar radiation and average wind speed was good enough to estimate the diurnal range of SST at ~1.0 m in the north Indian Ocean during most of the seasons except under low wind-high solar radiation conditions that occur mostly during spring. The additional information on the rate of precipitation is found to be redundant for the estimation of the magnitude of diurnal warming at those depths

Quasi-biweekly mode of the Asian summer monsoon revealed in Bay of Bengal surface observations

Author Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 125(12),(2020): e2020JC016271, https://doi.org/10.1029/2020JC016271.Asian summer monsoon has a planetary‐scale, westward propagating “quasi‐biweekly” mode of variability with a 10–25 day period. Six years of moored observations at 18°N, 89.5°E in the north Bay of Bengal (BoB) reveal distinct quasi‐biweekly variability in sea surface salinity (SSS) during summer and autumn, with peak‐to‐peak amplitude of 3–8 psu. This large‐amplitude SSS variability is not due to variations of surface freshwater flux or river runoff. We show from the moored data, satellite SSS, and reanalyses that surface winds associated with the quasi‐biweekly monsoon mode and embedded weather‐scale systems, drive SSS and coastal sea level variability in 2015 summer monsoon. When winds are calm, geostrophic currents associated with mesoscale ocean eddies transport Ganga‐Brahmaputra‐Meghna river water southward to the mooring, salinity falls, and the ocean mixed layer shallows to 1–10 m. During active (cloudy, windy) spells of quasi‐biweekly monsoon mode, directly wind‐forced surface currents carry river water away to the east and north, leading to increased salinity at the moorings, and rise of sea level by 0.1–0.5 m along the eastern and northern boundary of the bay. During July–August 2015, a shallow pool of low‐salinity river water lies in the northeastern bay. The amplitude of a 20‐day oscillation of sea surface temperature (SST) is two times larger within the fresh pool than in the saltier ocean to the west, although surface heat flux is nearly identical in the two regions. This is direct evidence that spatial‐temporal variations of BoB salinity influences sub‐seasonal SST variations, and possibly SST‐mediated monsoon air‐sea interaction.The authors thank the Ministry of Earth Sciences (MoES) institutes NIOT and INCOIS, and the Upper Ocean Processes (UOP) group at WHOI for design, integration, and deployment of moorings in the BoB. The WHOI mooring was deployed from the ORV Sagar Nidhi and recovered from the ORV Sagar Kanya—we thank the officers, crew and science teams on the cruises for their support. Sengupta, Ravichandran and Sukhatme acknowledge MoES and the National Monsoon Mission, Indian Institute of Tropical Meteorology (IITM), Pune, for support; Lucas and Farrar acknowledge the US Office of Naval Research for support of ASIRI through grants N00014‐13‐1‐0489, N0001413‐100453, N0001417‐12880. We thank S. Shivaprasad, Dipanjan Chaudhuri and Jared Buckley for discussion on ocean currents and Ekman flow, and Fabien Durand for discussion on sea level. JSL would like to thank the Divecha Center for Climate Change, IISc., for support. DS acknowledges support from the Department of Science and Technology (DST), New Delhi, under the Indo‐Spanish Programme.2021-05-1

Validation of IRS P4 MSMR data over the central Bay of Bengal during July-August 1999

210-215Validations of satellite-derived sea surface temperature (SST) and wind speed (WS) were carried out with sea-truth measurements obtained from moored data buoy and ship during July-August 1999. The SST sensed by multi –frequency scanning microwave radiometer (MSMR) showed significant departures from sea-truth measurements. The difference in SST (sea-truth-MSMR) was negative and large during daytime and vice versa during nighttime. Sea-truth measurements of wind speed indicated that they were always lower (2-5 ms-1) than the MSMR winds. The derived correction factors reduced the biases of satellite data

Longwave radiation corrections for the OMNI Buoy Network

Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of the Atmospheric and Oceanic Technology 39(2), (2022): 271–282. https://doi.org/10.1175/jtech-d-21-0069.1.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.KJJ and RV thank Ministry of Earth Sciences (MoES), Government of India, Secretary, MoES, and Director, NIOT, for the support and encouragement in carrying out the work under the National Monsoon Mission, Ocean Mixing and Monsoon (OMM) program. AT, JTF, and RAW thank Office of Naval Research Grants N00014-19-12410 and N00014-17-12880, United States, for funding and support. The OOS team at NIOT is acknowledged for their efforts in maintaining the OMNI buoy network in North Indian Ocean. We acknowledge Dr. B.W. Blomquist, University of Colorado, for his support in computing clear-sky radiation and Iury T. Simoes-Sousa, University of Massachusetts, Dartmouth, for the graphics. NCMRWF, MoES, Government of India, is acknowledged for NGFS reanalysis dataset, which is produced under the collaboration between NCMRWF, IITM, and IMD

Bay of Bengal intraseasonal oscillations and the 2018 monsoon onset

Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(10), (2021): E1936–E1951, https://doi.org/10.1175/BAMS-D-20-0113.1.In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.This work was supported through the U.S. Office of Naval Research’s Departmental Research Initiative: Monsoon Intraseasonal Oscillations in the Bay of Bengal, the Indian Ministry of Earth Science’s Ocean Mixing and Monsoons Program, and the Sri Lankan National Aquatic Resources Research and Development Agency. We thank the Captain and crew of the R/V Thompson for their help in data collection. Surface atmospheric fields included fluxes were quality controlled and processed by the Boundary Layer Observations and Processes Team within the NOAA Physical Sciences Laboratory. Forecast analysis was completed by India Meteorological Department. Drone image was taken by Shreyas Kamat with annotations by Gualtiero Spiro Jaeger. We also recognize the numerous researchers who supported cruise- and land-based measurements. This work represents Lamont-Doherty Earth Observatory contribution number 8503, and PMEL contribution number 5193.2022-04-0