A new approach for improving the accuracy of data assimilation, by trading numerical precision for ensemble size, is introduced. Data assimilation is inherently uncertain …
Members in ensemble forecasts differ due to the representations of initial uncertainties and model uncertainties. The inclusion of stochastic schemes to represent model …
Predictability of Atlantic Ocean sea surface temperatures (SST) on seasonal and decadal timescales is investigated using a suite of statistical linear inverse models (LIM). …
As the current funding for climate process teams comes to an end, scientists emphasize the continuing need for teams that translate basic research into improved climate models.
Uncertainties in parametrized processes in general circulation models can be represented as stochastic perturbations to the model formulation. The European Centre for …
The Climate SPHINX (Stochastic Physics HIgh resolutioN eXperiments) project is a comprehensive set of ensemble simulations aimed at evaluating the sensitivity of present and …
The use of reduced numerical precision to reduce computing costs for the cloud resolving model of superparameterized simulations of the atmosphere is investigated. An approach …
We use a stochastic differential equation (SDE) model with a random precipitation trigger for mass balance to simulate the 20 s temporal resolution column precipitable water …
A suite of statistical atmosphere-only linear inverse models of varying complexity are used to hindcast recent MJO events from the Year of Tropical Convection and the …