Search Results

You are looking at 1 - 4 of 4 items for :

  • Acoustic measurements/effects x
  • Air–Sea Interactions from the Diurnal to the Intraseasonal during the PISTON, MISOBOB, and CAMP2Ex Observational Campaigns in the Tropics x
  • All content x
Clear All
Jai Sukhatme, Dipanjan Chaudhuri, Jennifer MacKinnon, S. Shivaprasad, and Debasis Sengupta

local deformation radius ( Chelton et al. 1998 ). For example, acoustic Doppler current profiler (ADCP) data from the Gulf Stream showed steep spectra close to −3 scaling starting near 200 km ( Wang et al. 2010 ; Callies and Ferrari 2013 ), which flattened out to a much shallower form around 20 km ( Callies and Ferrari 2013 ). Further, the rotational component of the flow was dominant down to about 20 km ( Bühler et al. 2014 ), and the flattening was attributed to an increased contribution of

Restricted access
Kenneth G. Hughes, James N. Moum, and Emily L. Shroyer

illustrate the difficulty of idealizing even just the temperature profile: it is both depth and time dependent and its shape differs with wind speed. Compared to the number of attempts to idealize T ( z , t ), little attention has been given to u ( z , t ) or, equivalently, vector shear S ( z , t ). The lack of shear-focused studies reflects the challenge of making suitable near-surface measurements. Acoustic Doppler current profiler (ADCP) measurements in the near surface are challenging to obtain

Free access
Dipanjan Chaudhuri, Debasis Sengupta, Eric D’Asaro, R. Venkatesan, and M. Ravichandran

this time is nearly 10 times larger than in the west Pacific. Temperature inversions develop through autumn and winter ( Thadathil et al. 2016 ) as the sea surface temperature cools, while penetration of shortwave radiation below the shallow mixed layer continues to warm the subsurface ocean. Satellite microwave SST measurements ( Wentz et al. 2000 ) have been widely used to study the spatial structure and time evolution of SST cooling due to vertical mixing induced by tropical cyclones (e.g., D

Full access
Corinne B. Trott, Bulusu Subrahmanyam, Heather L. Roman-Stork, V. S. N. Murty, and C. Gnanaseelan

, Z = e − iω Δ T , ω is the frequency, Δ T is the sampling interval, and a , b 1 , and b 2 are constants that determine the sharpness of the filter. A recursive filter is optimal to avoid edge effects associated with phase shifts ( Zhao et al. 2017 ). Murakami (1979) applied this type of recursive filter to 4–5-day convective oscillations and lauded the ability of the filter to temporally detect anomalous peaks in a time series. Krishnamurti et al. (2017) applied this type of filter

Full access