Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2308.10987

Northbound Lagrangian Pathways of the Mediterranean Outflow Water and the Mechanism of Time-Dependent Chaotic Advection

Ori Saporta-Katz·Nadav Mantel·Rotem Liran·Vered Rom-Kedar·Hezi Gildor
View original source ↗Read source document ↗Export metadata ↓

Abstract

The Mediterranean Sea releases approximately 1Sv of water into the North Atlantic through the Gibraltar Straits, forming the saline Mediterranean Outflow Water (MOW). Its impact on large-scale flow and specifically its northbound Lagrangian pathways are widely debated, yet a comprehensive overview of MOW pathways over recent decades is lacking. We calculate and analyze synthetic Lagrangian trajectories in 1980-2020 reanalysis velocity data. 16\% of the MOW follow a direct northbound path to the sub-polar gyre, reaching a 1000m depth crossing window at the southern tip of Rockall Ridge in about 10 years. Surprisingly, time-dependent chaotic advection, not steady currents, drives over half of the northbound transport. Our results suggest a potential 15-20yr predictability in the direct northbound transport, which points to an upcoming decrease of MOW northbound transport in the next couple of decades. Additionally, monthly variability appears more significant than inter-annual variability in mixing and spreading the MOW.

Explore related subjects

physics.ao-phnlin.CDphysics.geo-ph

Keep this discovery

BibTeXRIS

Ori Saporta-Katz, Nadav Mantel, Rotem Liran, Vered Rom-Kedar, Hezi Gildor. 2023-08-16. Northbound Lagrangian Pathways of the Mediterranean Outflow Water and the Mechanism of Time-Dependent Chaotic Advection. https://arxiv.org/abs/2308.10987

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

KEEP EXPLORING

Related papers

arXiv2026

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↗
arXiv2026

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↗