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Stochastic climate theory and modeling
Stochastic methods are a crucial area in contemporary climate research and are
increasingly being used in comprehensive weather and climate prediction models as well as …
increasingly being used in comprehensive weather and climate prediction models as well as …
New trends in ensemble forecast strategy: uncertainty quantification for coarse-grid computational fluid dynamics
Numerical simulations of industrial and geophysical fluid flows cannot usually solve the
exact Navier–Stokes equations. Accordingly, they encompass strong local errors. For some …
exact Navier–Stokes equations. Accordingly, they encompass strong local errors. For some …
Stochastic parameterization: Toward a new view of weather and climate models
The last decade has seen the success of stochastic parameterizations in short-term, medium-
range, and seasonal forecasts: operational weather centers now routinely use stochastic …
range, and seasonal forecasts: operational weather centers now routinely use stochastic …
Is weather chaotic?: Coexistence of chaos and order within a generalized Lorenz model
Over 50 years since Lorenz's 1963 study and a follow-up presentation in 1972, the
statement “weather is chaotic” has been well accepted. Such a view turns our attention from …
statement “weather is chaotic” has been well accepted. Such a view turns our attention from …
Geophysical flows under location uncertainty, Part II Quasi-geostrophy and efficient ensemble spreading
Models under location uncertainty are derived assuming that a component of the velocity is
uncorrelated in time. The material derivative is accordingly modified to include an advection …
uncorrelated in time. The material derivative is accordingly modified to include an advection …
Stochastic climate theory
In this chapter we review stochastic modeling methods in climate science. First we provide a
conceptual framework for stochastic modeling of deterministic dynamical systems based on …
conceptual framework for stochastic modeling of deterministic dynamical systems based on …
A computational method to extract macroscopic variables and their dynamics in multiscale systems
This paper introduces coordinate-independent methods for analyzing multiscale dynamical
systems using numerical techniques based on the transfer operator and its adjoint. In …
systems using numerical techniques based on the transfer operator and its adjoint. In …
[HTML][HTML] A kernel principal component analysis of coexisting attractors within a generalized Lorenz model
Based on recent studies that reveal the coexistence of chaotic and non-chaotic solutions
using a generalized Lorenz model (GLM), a revised view on the dual nature of weather has …
using a generalized Lorenz model (GLM), a revised view on the dual nature of weather has …
Is weather chaotic? Coexisting chaotic and non-chaotic attractors within Lorenz models
The pioneering study of Lorenz in 1963 and a follow-up presentation in 1972 changed our
view on the predictability of weather by revealing the so-called butterfly effect, also known as …
view on the predictability of weather by revealing the so-called butterfly effect, also known as …
Data-driven versus self-similar parameterizations for stochastic advection by lie transport and location uncertainty
Stochastic subgrid parameterizations enable ensemble forecasts of fluid dynamic systems
and ultimately accurate data assimilation (DA). Stochastic advection by Lie transport (SALT) …
and ultimately accurate data assimilation (DA). Stochastic advection by Lie transport (SALT) …