Results 111 to 120 of about 505 (141)

The impact of simulated mesoscale convective systems on global precipitation: A multiscale modeling study. [PDF]

J Adv Model Earth Syst, 2017
Tao WK, Chern JD.
europepmc   +1 more source

Madden-Julian Oscillation analog and intraseasonal variability in a multicloud model above the equator. [PDF]

Proc Natl Acad Sci U S A, 2007
Majda AJ, Stechmann SN, Khouider B.
europepmc   +1 more source

A GCM with cloud microphysics and its MJO simulation [PDF]

, 2016

core   +1 more source

New perspectives on superparameterization for geophysical turbulence [PDF]

Journal of Computational Physics, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
IAN GROOMS
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Stochastic Superparameterization and Multiscale Filtering of Turbulent Tracers

Multiscale Modeling and Simulation, 2017
Summary: Data assimilation or filtering combines a numerical forecast model and observations to provide accurate statistical estimation of the state of interest. In this paper, we are concerned with accurate data assimilation of a sparsely observed passive tracer advected in turbulent flows using a reduced-order forecast model.
Yoonsang Lee, Di Qi
exaly   +3 more sources

Test Models for Filtering with Superparameterization

Multiscale Modeling and Simulation, 2013
Superparameterization is a fast numerical algorithm to mitigate implicit scale separation of dynamical systems with large-scale, slowly varying “mean” and smaller-scale, rapidly fluctuating “eddy” term. The main idea of superparameterization is to embed parallel highly resolved simulations of small-scale eddies on each grid cell of coarsely resolved ...
John Harlim, Andrew J. Majda
exaly   +2 more sources

Climate sensitivity and cloud response of a GCM with a superparameterization [PDF]

Geophysical Research Letters, 2006
The climate sensitivity of an atmospheric GCM that uses a cloud‐resolving model as a convective superparameterization is analyzed by comparing simulations with specified climatological sea surface temperature (SST) and with the SST increased by 2 K. The model has weaker climate sensitivity than most GCMs, but comparable climate sensitivity to recent ...
Matthew C Wyant, Marat Khairoutdinov, Christopher S Bretherton   +2 more
exaly   +2 more sources

Stochastic superparameterization in a quasigeostrophic model of the Antarctic Circumpolar Current

Ocean Modelling, 2015
Stochastic superparameterization, a stochastic parameterization framework based on a multiscale formalism, is developed for mesoscale eddy parameterization in coarse-resolution ocean modeling. The framework of stochastic superparameterization is reviewed and several configurations are implemented and tested in a quasigeostrophic channel model – an ...
IAN GROOMS, K Shafer Smith
exaly   +2 more sources

Toward low‐cloud‐permitting cloud superparameterization with explicit boundary layer turbulence

Journal of Advances in Modeling Earth Systems, 2017
AbstractSystematic biases in the representation of boundary layer (BL) clouds are a leading source of uncertainty in climate projections. A variation on superparameterization (SP) called “ultraparameterization” (UP) is developed, in which the grid spacing of the cloud‐resolving models (CRMs) is fine enough (250 × 20 m) to explicitly capture the BL ...
Hossein Parishani, M S Pritchard, Christopher S Bretherton   +2 more
exaly   +4 more sources

‘Superparameterization’ and statistical emulation in the Lorenz '96 system

Quarterly Journal of the Royal Meteorological Society, 2012
AbstractAn idealized ‘superparameterization’, or abbreviated but dynamically explicit representation of small‐scale influences on the conventionally resolved larger scales of a dynamical model, is constructed within the Lorenz '96 system. The feasibility of abstracting the greater portion of its information content using computationally much faster ...
Daniel S Wilks
exaly   +2 more sources