activity
20182020
most citedA highly scalable Met Office NERC Cloud model

23 citations · 52 across the 4 of their papers we have counts for

collaborators

6 papers

cs.DC2020

Porting the microphysics model CASIM to GPU and KNL Cray machines

Nick Brown, Alexandr Nigay, Michèle Weiland +2

CASIM is a microphysics scheme which calculates the interaction between moisture droplets in the atmosphere and forms a critical part of weather and climate modelling codes. Howeve…

cs.DC202019 cited

In-situ data analytics for highly scalable cloud modelling on Cray machines

Nick Brown, Michèle Weiland, Adrian Hill +1

MONC is a highly scalable modelling tool for the investigation of atmospheric flows, turbulence and cloud microphysics. Typical simulations produce very large amounts of raw data w…

cs.DC202010 cited

A directive based hybrid Met Office NERC Cloud model

Nick Brown, Angus Lepper, Michèle Weiland +3

Large Eddy Simulation is a critical modelling tool for the investigation of atmospheric flows, turbulence and cloud microphysics. The models used by the UK atmospheric research com…

cs.SE202023 cited

A highly scalable Met Office NERC Cloud model

Nick Brown, Michèle Weiland, Adrian Hill +4

Large Eddy Simulation is a critical modelling tool for scientists investigating atmospheric flows, turbulence and cloud microphysics. Within the UK, the principal LES model used by…

math.NA2019

A Compatible Finite Element Discretisation for the Moist Compressible Euler Equations

Thomas M. Bendall, Thomas H. Gibson, Jemma Shipton +2

We present new discretisation of the moist compressible Euler equations, using the compatible finite element framework identified in Cotter and Shipton (2012). The discretisation s…

cs.DC2018

LFRic: Meeting the challenges of scalability and performance portability in Weather and Climate models

S. V. Adams, R. W. Ford, M. Hambley +10

This paper describes LFRic: the new weather and climate modelling system being developed by the UK Met Office to replace the existing Unified Model in preparation for exascale comp…