Search arXivSearch

arXiv · 1610.06708

Coherent changes of the circulation in the deep North Atlantic from moored transport arrays

Abstract

In situ boundary arrays have been installed in the North Atlantic to measure the large-scale ocean circulation. Here, we use measurements at the western edge of the North Atlantic at $16^\circ$N and $26^\circ$N to investigate low-frequency variations in deep densities and their associated influence on ocean transports. At both latitudes, deep waters (below 1100 dbar) at the western boundary are becoming fresher and less dense. The associated change in geopotential thickness is about $0.15$ $\mbox{m}^2\mbox{s}^{-2}$ between 2004-2009 and 2010-2014, with the shift occurring between 2009-2010 and earlier at $26^\circ$N than $16^\circ$N. Without a similar density change on the east of the Atlantic, a mid-depth reduction in water density at the west drives an increase in the shear between the upper and lower layers of North Atlantic Deep Water of about 2.6 Sv at $26^\circ$N and 3.9 Sv at $16^\circ$N. While these transport anomalies result in an intensifying tendency in the meridional overturning circulation (MOC) estimate at $16^\circ$N, the method of applying a zero net mass transport constraint at $26^\circ$N results in an opposing (reducing) tendency of the MOC.

Explore related subjects

Keep this discovery

BibTeXRIS

E. Frajka-Williams, M. Lankhorst, J. Koelling, U. Send. 2016-10-21. Coherent changes of the circulation in the deep North Atlantic from moored transport arrays. https://arxiv.org/abs/1610.06708

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