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  • Author or Editor: Verena Hormann x
  • Air–Sea Interactions from the Diurnal to the Intraseasonal during the PISTON, MISOBOB, and CAMP2Ex Observational Campaigns in the Tropics x
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Sebastian Essink
,
Verena Hormann
,
Luca R. Centurioni
, and
Amala Mahadevan

Abstract

A cluster of 45 drifters deployed in the Bay of Bengal is tracked for a period of four months. Pair dispersion statistics, from observed drifter trajectories and simulated trajectories based on surface geostrophic velocity, are analyzed as a function of drifter separation and time. Pair dispersion suggests nonlocal dynamics at submesoscales of 1–20 km, likely controlled by the energetic mesoscale eddies present during the observations. Second-order velocity structure functions and their Helmholtz decomposition, however, suggest local dispersion and divergent horizontal flow at scales below 20 km. This inconsistency cannot be explained by inertial oscillations alone, as has been reported in recent studies, and is likely related to other nondispersive processes that impact structure functions but do not enter pair dispersion statistics. At scales comparable to the deformation radius L D , which is approximately 60 km, we find dynamics in agreement with Richardson’s law and observe local dispersion in both pair dispersion statistics and second-order velocity structure functions.

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Sebastian Essink
,
Verena Hormann
,
Luca R. Centurioni
, and
Amala Mahadevan

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 O ( 1 10 ) km , kinematic properties become as large as planetary vorticity f, but challenging to observe because they evolve on short time scales O ( hours to days ) . By simulating surface drifters in a model flow field, we quantify the sources of uncertainty in the kinematic property calculations due to the deformation of cluster shape. Uncertainties arise primarily due to (i) violation of the linear estimation methods and (ii) aliasing of unresolved scales. Systematic uncertainties (iii) due to GPS errors, are secondary but can become as large as (i) and (ii) when aspect ratios are small. Ideal cluster parameters (number of drifters, length scale, and aspect ratio) are determined and error functions estimated empirically and theoretically. The most robust method—a two-dimensional, linear least squares fit—is applied to the first few days of a drifter dataset from the Bay of Bengal. Application of the length scale and aspect-ratio criteria minimizes errors (i) and (ii), and reduces the total number of clusters and so computational cost. The drifter-estimated kinematic properties map out a cyclonic mesoscale eddy with a surface, submesoscale fronts at its perimeter. Our analyses suggest methodological guidance for computing the two-dimensional kinematic properties in submesoscale flows, given the recently increasing quantity and quality of drifter observations, while also highlighting challenges and limitations.

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.

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Emily Shroyer
,
Amit Tandon
,
Debasis Sengupta
,
Harindra J. S. Fernando
,
Andrew J. Lucas
,
J. Thomas Farrar
,
Rajib Chattopadhyay
,
Simon de Szoeke
,
Maria Flatau
,
Adam Rydbeck
,
Hemantha Wijesekera
,
Michael McPhaden
,
Hyodae Seo
,
Aneesh Subramanian
,
R Venkatesan
,
Jossia Joseph
,
S. Ramsundaram
,
Arnold L. Gordon
,
Shannon M. Bohman
,
Jaynise Pérez
,
Iury T. Simoes-Sousa
,
Steven R. Jayne
,
Robert E. Todd
,
G. S. Bhat
,
Matthias Lankhorst
,
Tamara Schlosser
,
Katherine Adams
,
S. U. P Jinadasa
,
Manikandan Mathur
,
M. Mohapatra
,
E. Pattabhi Rama Rao
,
A. K. Sahai
,
Rashmi Sharma
,
Craig Lee
,
Luc Rainville
,
Deepak Cherian
,
Kerstin Cullen
,
Luca R. Centurioni
,
Verena Hormann
,
Jennifer MacKinnon
,
Uwe Send
,
Arachaporn Anutaliya
,
Amy Waterhouse
,
Garrett S. Black
,
Jeremy A. Dehart
,
Kaitlyn M. Woods
,
Edward Creegan
,
Gad Levy
,
Lakshmi H. Kantha
, and
Bulusu Subrahmanyam

Abstract

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.

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