The relation between weekly Arctic sea ice concentrations (SICs) from December to April and sea level pressure (SLP) during 1979–2007 is investigated using maximum covariance analysis (MCA). In the North Atlantic sector, the interaction between the North Atlantic Oscillation (NAO) and a SIC seesaw between the Labrador Sea and the Greenland–Barents Sea dominates. The NAO drives the seesaw and in return the seesaw precedes a midwinter/spring NAO-like signal of the opposite polarity but with a strengthened northern lobe, thus acting as a negative feedback, with maximum squared covariance at a lag of 6 weeks. Statistical significance decreases when SLP is considered in the whole Northern Hemisphere but it increases when North Pacific SIC is included in the analysis. The maximum squared covariance then occurs after 8 weeks, resembling a combination of the NAO response to the Atlantic SIC seesaw and the Aleutian–Icelandic low seesaw-like response to in-phase SIC changes in the Bering and Okhotsk Seas, which is found to lag the North Pacific SIC. Adding SST anomalies to the SIC anomalies in the MCA leads to a loss of significance when the MCA is limited to the North Atlantic sector and a slight degradation in the Pacific and hemispheric cases, suggesting that SIC is the driver of the midwinter/spring atmospheric signal. However, North Pacific cold season SST anomalies also precede a NAO/Arctic Oscillation (AO)-like SLP signal after a shorter delay of 3–4 weeks

Wind speed measurements are needed to understand ocean–atmosphere coupling processes and their effects on climate. Satellite observations provide sufficient spatial and temporal coverage but are lacking adequate calibration, while ship- and mooring-based observations are spatially limited and have technical shortcomings. However, wind-generated underwater noise can be used to measure wind speed, a method known as Weather Observations Through Ambient Noise (WOTAN). Here, we adapt the WOTAN technique for application to ocean gliders, enabling calibrated wind speed measurements to be combined with contemporaneous oceanographic profiles over extended spatial and temporal scales. We demonstrate the methodology in three glider surveys in the Mediterranean Sea during winter 2012/13. Wind speeds ranged from 2 to 21.5 m s−1, and the relationship to underwater ambient noise measured from the glider was quantified. A two-regime linear model is proposed, which validates a previous linear model for light winds (below 12 m s−1) and identifies a regime change in the noise generation mechanism at higher wind speeds. This proposed model improves on previous work by extending the validated model range to strong winds of up to 21.5 m s−1. The acquisition, data processing, and calibration steps are described. Future applications for glider-based wind speed observations and the development of a global wind speed estimation model are discussed.

An experiment was carried out in the Gulf of Lions (NW Mediterranean) in February 2014 to assess the temporal and spatial variability of the distribution and size of suspended particulate matter (SPM) in the Rhône Region of Freshwater Influence (ROFI). A set of observations from an autonomous underwater glider, satellite ocean color data, and meteorological and hydrological time-series data highlighted the high variability of the Rhône River surface turbid plume and presence of a bottom nepheloid layer (BNL) that depended on wind and river discharge conditions. While continental winds pushed the surface plume offshore, marine winds pressed the plume at the coast and favored the sedimentation of as well as nourishment of the BNL. Moderate storm events favored breakage of the plume stratification and along-shelf transport of Rhône River particles. The spectral slopes of glider and satellite-derived light backscattering coefficients, γ, were used as a proxies of the SPM size distribution. The results clearly showed that the change of the SPM size in the nepheloid layers was induced by the flocculation of fine sediments, which became finer seaward throughout the ROFI, as well as the effect of rough weather in the breakup of flocs