Results 181 to 190 of about 393,837 (280)

The relationship between seasonal mean temperature and most extreme day

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
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

NORTH ATLANTIC OCEAN

open access: yesMonthly Weather Review, 1930
openaire   +2 more sources

Cloud drop number concentrations over the western North Atlantic Ocean: seasonal cycle, aerosol interrelationships, and other influential factors. [PDF]

open access: yesAtmos Chem Phys, 2021
Dadashazar H   +21 more
europepmc   +1 more source

Modulation of North Atlantic atmospheric rivers by the Gulf Stream

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
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

NORTH ATLANTIC OCEAN

open access: yesMonthly Weather Review, 1931
openaire   +2 more sources

Microphysical chemistry of fog–aerosol interactions over the northwest Atlantic Ocean during Fatima 2022

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
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

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
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

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