Search

The work identified the monsoon intraseasonal oscillation (MISO) from the observed met-ocean parameters from the moored buoys and satellite datasets during June 2013 – September 2013. The 30–60 days bandpass filtered winds, sea surface temperature (SST), and rainfall from both the satellites and moored buoys have indicated the existence of active and break phases of MISOs with a periodicity of 10–12 days. All the parameters show a northward propagation of the MISO signals from the southern to the northern BoB with stronger magnitude on the north of 12 °N. The warmer SST causes the high wind and precipitation in an active phase after 4–5 days. During active phases, SST dropped, and break phase occurs with less wind and precipitation after 10–12 days. Prominent signatures of the MISOs are also observed along the ocean subsurface from the temperature, salinity, and current profiles. The 23 °C isotherm (D23) deepens during the active phases of the MISOs to make the surface warm. The D23 shoals during the break phases, indicating cooling of the ocean surface. The in-phase relationship of 100 m temperature and wind speeds together indicate an important role of the surface winds during the different phases of MISO. Deepening and shoaling of mixed layer are observed in the upper ocean during the different MISO phases with varying characteristics in the northern and southern BoB. The subsurface signatures of MISOs are strong near 100 m for temperature, but for salinity and currents, the signatures are restricted within 50 m depth.

Based on the in-situ subsurface thermal and salinity measurements from the Ocean Moored buoy network for Northern Indian Ocean (OMNI) during the Super Cyclone Amphan in the Bay of Bengal during 14–18 May 2020, we have identified that the ocean-atmosphere interaction is limited to 80 m, the depth of the pycnocline. Using the OAEE-TS algorithm and dynamic changes in the sea subsurface temperature, salinity and precipitation as inputs, we have calculated the water vapor generation rates for a range of wind speeds. Based on the salinity changes, the water vapor generation rates for cyclone period-averaged wind speeds of 9, 16 and 25 m/s were 0.86, 4.33 and 11.24 kg/m2/h, respectively. For the same wind speeds, based on the Ocean Heat Content (OHC) changes, ∼76, 86 and 95 % of the OHC changes were in the form of latent heat. The identified evaporation rate parameters along with the previous study results are presented as model which could be used as inputs for ocean-atmosphere coupled models and tropical cyclone intensification studies in the Bay of Bengal.

Latent Heat Flux (LHF) and Sensible Heat Flux (SHF) are the two important parameters in air-sea interactions and hence have significant implications for any coupled ocean-atmospheric model. These two fluxes are conventionally computed from met-ocean parameters using bulk aerodynamic formulations; or the Coupled Ocean Atmosphere Response Experiment (COARE) bulk flux algorithms. Here COARE 3.5 algorithm is used to estimate the heat flux from two Ocean Moored Buoy Network for northern Indian Ocean (OMNI) buoy met-ocean observations in Arabian Sea (AS) and the Bay of Bengal (BoB). The AS and BoB are two ocean basins which are situated in same latitudinal range, but experience drastically differing in their met-ocean conditions, especially during the monsoon seasons. In this study, we have computed and compared the LHF and SHF at two different buoy locations in the AS and BoB and analysed their variability during three different seasons from November 2012 to September 2013. Additionally, 20 years (1998–2017) of Objectively Analysed (OA) Flux data sets collocated with the OMNI buoy locations were also utilised to the analyse the long period seasonal variabilities. The flux terms show strong seasonal variability with several peaks during the monsoon seasons in both the ocean basins. LHF varies directly with wind speed (WS) and inversely with relative humidity (RH). The correlation of LHF with WS is greater than 0.7 and RH is nearly -0.6 with few exceptions during pre-monsoon season in the AS and southwest monsoon in the BoB. However, SHF is less correlated with WS (∼0.3 to 0.5). The difference of sea surface temperature and air temperature (denoted as SST-AT) plays a significant role in determining SHF with a correlation greater than 0.6 in both the basins.