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Stochastic parametrisations are used in weather and climate models to improve the representation of unpredictable unresolved processes. When compared to a deterministic model, a stochastic model represents `model uncertainty, i.e., sources of error in the forecast due to the limitations of the forecast model. We present a technique for systematically deriving new stochastic parametrisations or for constraining existing stochastic approaches. A high-resolution model simulation is coarse-grained to the desired forecast model resolution. This provides the initial conditions and forcing data needed to drive a Single Column Model (SCM). By comparing the SCM parametrised tendencies with the evolution of the high resolution model, we can estimate the error in the SCM tendencies that a stochastic parametrisation seeks to represent. We use this approach to assess the physical basis of the widely used Stochastically Perturbed Parametrisation Tendencies (SPPT) scheme. We find justification for the multiplicative nature of SPPT, and for the use of spatio-temporally correlated stochastic perturbations. We find evidence that the stochastic perturbation should be positively skewed, indicating that occasional large-magnitude positive perturbations are physically realistic. However other key assumptions of SPPT are less well justified, including coherency of the stochastic perturbations with height, coherency of the perturbations for different physical parametrisation schemes, and coherency for different prognostic variables. Relaxing these SPPT assumptions allows for an error model that explains a larger fractional variance than traditional SPPT. In particular, we suggest that independently perturbing the tendencies associated with different parametrisation schemes is justifiable, and would improve the realism of the SPPT approach.
Observations of tropical convection from precipitation radar and the concurring large-scale atmospheric state at two locations (Darwin and Kwajalein) are used to establish effective stochastic models to parameterise subgrid-scale tropical convective
The daily cycle of heating and cooling of the near-surface ocean may be quite different in a shallow lagoon with a few meters deep seafloor that can be heated directly by the sun. If important, the solar radiation will affect the local benthic commun
With LOFAR we have been able to image the development of lightning flashes with meter-scale accuracy and unprecedented detail. We discuss the primary steps behind our most recent lightning mapping method. To demonstrate the capabilities of our techni
We develop new numerical schemes for Vlasov--Poisson equations with high-order accuracy. Our methods are based on a spatially monotonicity-preserving (MP) scheme and are modified suitably so that positivity of the distribution function is also preser
We study the density structures of dark matter subhalos for both cold dark matter and self-interacting dark matter models using high-resolution cosmological $N$-body simulations. We quantify subhalos central density at 150 pc from the center of each