Results 231 to 240 of about 322,650 (353)

Climatology of upper‐tropospheric turbulence: Capabilities and limitations of aircraft reports and ERA5 reanalysis diagnostics

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
Based on turbulence diagnostics, airlines are willing to avoid up to 15% of the airspace in order to avoid a fraction of turbulence that takes up about 0.1% of the airspace. This study quantifies these three fractions using turbulence reports from commercial aircraft and ERA5 reanalysis diagnostics, revealing that the low and regionally variable ...
Thorsten Kaluza   +3 more
wiley   +1 more source

Assessing wildfire dynamics during a megafire in Portugal using the MesoNH/ForeFire coupled model

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
Weather conditions affect megafires by inducing different fire behaviors over several days or weeks. The coupled MesoNH/ForeFire code was used to represent the dynamics of fire generating pyro‐convective clouds. To advance the understanding of wildfire dynamics, high‐resolution coupled fire–atmosphere modeling was employed.
Cátia Campos   +12 more
wiley   +1 more source

Seasonal hindcasts to assess the hazard of meteorological drought over Europe: A multimodel approach

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
An application of seasonal hindcasts is presented for assessing the hazard of meteorological drought at the regional scale across Europe. The realism of seasonal hindcasts from five contributors to the Copernicus Climate Change Service is assessed through a rigorous workflow.
Marco Buccellato   +2 more
wiley   +1 more source

Data assimilation with extremum Monte Carlo methods

open access: yesQuarterly Journal of the Royal Meteorological Society, EarlyView.
This study presents the extremum Monte Carlo filter as a data assimilation method and, in particular, a variant of the variational approach (three‐ and four‐dimensional variational), where the state estimates are obtained by solving an optimization problem numerically over a space of prediction functions, instead of the state space itself.
Karim Moussa, Siem Jan Koopman
wiley   +1 more source

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