SearcharxivSearch

arXiv · 1711.03311

Dynamics of Summer Monsoon Currents around Sri Lanka

Abstract

$ $From June--September, the summer monsoon current (SMC) flows eastward south of Sri Lanka and bends northeastward to form a swift jet that enters the Bay of Bengal (BoB). As such, it is a crucial part of the water exchange between the Arabian Sea (AS) and BoB. The processes that determine the evolution, intensification and meandering of the SMC are only partly understood. They involve both local and remote forcing by the wind, as well as interactions with westward-propagating Rossby waves and eddies. In this study, we investigate these processes using an Indian-Ocean general circulation model (MOM4p1) that is capable of simulating the SMC realistcally. Because eddies and meanders are smoothed out in the climatology, our analyses focus on a single year of 2009, a period when a strong anticyclonic bend in the SMC was observed. An eddy-kinetic-energy budget analysis shows the region to be a zone of significant eddy activity, where both barotropic and baroclinic instabilities are active. Based on the analysis, we classify the evolution of SMC into stages of onset, intensification, anticyclonic bend, anticyclonic vortex formation, meandering and termination. In addition, analysis of eddy-potential-vorticity flux and eddy-enstrophy decay reveal when, where, and how the eddies tend to drive the mean flow. Rossby waves and westward-propagating eddies arriving from the east energize the SMC in June and accelerate the mean flow through an up-gradient eddy-potential-vorticity flux. At the same time, local winds also strengthen the flow, by increasing its mean, near-surface, kinetic energy and raising isopycnals, the latter building up available potential energy (APE). The baroclinic instability that takes place in late--July and early--August releases APE, thereby generating the SMC meanders.

Explore related subjects

Keep this discovery

BibTeXRIS

Subham Rath, P. N. Vinayachandran, A. Behara, C. P. Neema. 2017-11-09. Dynamics of Summer Monsoon Currents around Sri Lanka. https://arxiv.org/abs/1711.03311

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Windowed Envelope Statistics for Time-Domain Significant Wave Height Estimation From HF Radar

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

physics.ao-ph

KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations

Accurate kilometer-scale near-surface winds are important for understanding atmospheric processes over complex terrain, yet remain difficult to reconstruct from sparse and unevenly distributed observations. Here we introduce KiloDA, a diffusion framework for hourly kilometer-scale wind reconstruction from surface stations. KiloDA learns the statistical distribution and spatial structure of wind fields from historical 3-km Weather Research and Forecasting (WRF) model forecasts. At each reconstruction time, no contemporaneous WRF field is used. Instead, station observations provide the only constraints on the current atmospheric state and guide posterior sampling from the learned prior. In idealized WRF experiments, KiloDA recovers localized wind structures when only 0.24% of grid cells are observed and shows an overall advantage over conventional interpolation across terrain conditions and wind speed regimes. This capability largely transfers to real observations. In a fully withheld region, KiloDA reduces the median wind speed root mean square error (RMSE) by 19% relative to ERA5 reanalysis, using only observations outside the region, with the largest improvements over high-elevation and high-relief terrain. A random station holdout further confirms that this advantage extends across different complex-terrain locations and holdout configurations. These results show that historical model archives can provide useful structural knowledge for reconstructing kilometer-scale wind fields from sparse observations without requiring an accurate model estimate of the current atmospheric state.

physics.ao-ph