▪ Abstract Weather and climate predictions are uncertain, because both forecast initial
conditions and the computational representation of the known equations of motion are …

There is no more challenging problem in computational science than that of estimating, as
accurately as science and technology allows, the future evolution of Earth's climate; nor …

Representing unresolved moist convection in coarse‐scale climate models remains one of
the main bottlenecks of current climate simulations. Many of the biases present with …

A multi-model ensemble-based system for seasonal-to-interannual prediction has been
developed in a joint European project known as DEMETER (Development of a European …

A Stochastic Parameterization for Deep Convection Based on Equilibrium Statistics in: Journal
of the Atmospheric Sciences Volume 65 Issue 1 (2008) Jump to Content Jump to Main …

A stochastic model for representing the missing variability in global climate models due to
unresolved features of organized tropical convection is presented here. We use a Markov …

A stochastic parameterization of ocean mesoscale eddies is constructed in order to account
for the fluctuations in subgrid transport and to represent upscale turbulent cascades. Eddy …

Multiscale simulation is an emerging scientific field that spans many disciplines, including
physics, chemistry, mathematics, statistics, chemical engineering, mechanical engineering …

Systematic strategies from applied mathematics for stochastic modelling in climate are
reviewed here. One of the topics discussed is the stochastic modelling of mid-latitude low …

Subgrid-Scale Parameterization with Conditional Markov Chains in: Journal of the
Atmospheric Sciences Volume 65 Issue 8 (2008) Jump to Content Jump to Main Navigation …