Correction: Tomasino et al. Diversity and Hydrocarbon-Degrading Potential of Deep-Sea Microbial Community from the Mid-Atlantic Ridge, South of the Azores (North Atlantic Ocean). Microorganisms 2021, 9, 2389. [PDF]
Tomasino MP +7 more
europepmc +1 more source
The relationship between seasonal mean temperature and most extreme day
In Northern Hemisphere winter, there is a strong correlation between seasonal mean temperature and coldest daily mean temperature which varies in magnitude from one region to another (with a weaker relationship in summer between mean and hottest day).
Anna Maidens +3 more
wiley +1 more source
Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors. [PDF]
Dadashazar H +21 more
europepmc +1 more source
Modulation of North Atlantic atmospheric rivers by the Gulf Stream
Gulf Stream ocean variability plays a key role in modulating atmospheric river (AR) activity over the North Atlantic during winter and spring at monthly time‐scales. Increased ocean heat transport and mesoscale activity in the Gulf Stream are linked to northward shifts in ARs, while stronger surface heat fluxes drive ARs southward.
Ferran Lopez‐Marti +3 more
wiley +1 more source
Subpolar North Atlantic Ocean heat content drives 21st-century Arctic multi-decadal variability in CESM1 LE. [PDF]
Cai D, Chen X.
europepmc +1 more source
Whole-Genome Sequence of a Brucella pinnipedialis Sequence Type 54 Strain Isolated from a Hooded Seal (Cystophora cristata) from the North Atlantic Ocean, Norway. [PDF]
Zygmunt MS, Vergnaud G, Cloeckaert A.
europepmc +1 more source
Fifteen size‐resolved aerosol samples collected during marine fog, with adjacent ambient observations, show that coarse sea salt aerosol is rapidly grown and lost in the northwest North Atlantic Ocean except when subject to extreme winds. The persistence of fog in the absence of sea salt is determined by available fine‐mode aerosol, where greater ...
Leyla Salehpoor +10 more
wiley +1 more source
Polar‐low track prediction using machine‐learning methods
Machine‐learning models are developed to produce reliable and efficient forecasts of polar‐low (PL) trajectories 12 hours ahead. A temporal model (RLSTM) benefiting from the rolling‐forecast strategy, improves overall prediction accuracy and is suitable for quick experimentation, while a spatiotemporal model (PL‐UNet), incorporating both historical and
Ziying Yang +4 more
wiley +1 more source

