Results 211 to 220 of about 97,145 (309)

South China Sea "(Trident)": Solution for ocean forecast foundation models. [PDF]

Innovation (Camb)
Zhao W, Lin X, Jin Y, Huang W, Liang Y, Guan S.   +5 more
europepmc   +1 more source

Present and future downslope windstorms in the Scandinavian Mountains from a kilometre‐scale climate model

Quarterly Journal of the Royal Meteorological Society, EarlyView.
Kilometre‐scale climate simulations for Scandinavia indicate the importance of high resolution for reproducing downslope windstorms (DWs). Scandinavian DWs on average induce a limited local warming but with large variability due to the region's complex orography.
Patrik Jureša, Danijel Belušić, Sophie Marimbordes, Felicitas Hansen, Petter Lind, John T. Abatzoglou   +5 more
wiley   +1 more source

Protocol for identifying compound heat-danger and ozone-pollution hotspots and their synoptic drivers. [PDF]

STAR Protoc
Wang J, Liang Q, Miao Y.
europepmc   +1 more source

Assimilation of machine‐learning‐predicted nitrate to improve the quality of phytoplankton forecasting in the shelf‐sea environment

Quarterly Journal of the Royal Meteorological Society, EarlyView.
This article demonstrates that assimilating machine‐learning‐derived surface nitrate can improve five‐day phytoplankton forecast substantially within the Met Office operational system for the Northwest European Shelf. We explain the reasons behind this improvement and propose that an online system where machine learning and data assimilation are cycled
Deep S. Banerjee, Jozef Skákala, David Ford   +2 more
wiley   +1 more source

Two-decade in-situ oceanographic and meteorological observations from Ieodo Ocean Research Station in the northern East China Sea. [PDF]

Sci Data
Kim GU, Min Y, Lee SW, Oh H, Jeong J, Ok J, Lee J, Lee SC, Min IK, Jeong E, Jeong KY, Ham H, Jeong JY.   +12 more
europepmc   +1 more source

Polar‐low track prediction using machine‐learning methods

Quarterly 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, Rune Grand Graversen, Filippo Maria Bianchi, Jiping Liu, Ruibo Lei   +4 more
wiley   +1 more source

Cloze, Frequency, Surprisal, or Plausibility? A Comparative Analysis of Predictors for Local Ambiguity Resolution. [PDF]

Cogn Sci
Ceháková M, Chromý J.
europepmc   +1 more source

Near‐resonant excitation of the Adriatic barotropic modes: The seiche events of December 2019

Quarterly Journal of the Royal Meteorological Society, EarlyView.
This study examines severe flooding in the northern Adriatic Sea in December 2019, which existing forecasting systems failed to predict. Analysis of wind and sea‐level data, alongside reanalysis datasets and a high‐resolution hydrodynamic model, revealed a wind‐induced resonance mechanism.
Marco Bajo, Luca Arpaia, Christian Ferrarin, Mirko Orlić   +3 more
wiley   +1 more source

A Conceptual Wound-Oriented Reinterpretation of Perfusion Heterogeneity in Chronic Limb-Threatening Ischemia. [PDF]

J Clin Med
Popitiu MI, Patrone L, Clerici G, Comsa S, Gavrila-Ardelean G, Kundnani NR, Olariu N, Ionac ME.   +7 more
europepmc   +1 more source

A new method to identify and explain sources of precipitation modification, illustrated for the western Netherlands

Quarterly Journal of the Royal Meteorological Society, EarlyView.
This study develops a method to identify the source areas of precipitation events, as illustrated for the western part of the Netherlands. Radar‐based precipitation data are traced back to their source areas and machine‐learning techniques are used to identify hypothesized causes: urban heat, surface roughness, and air pollution. We find that urban and
Jelmer van der Graaff, Gert‐Jan Steeneveld   +1 more
wiley   +1 more source