Statistical Weather Prediction And Regional Climate Modelling For Downscale Coarse Resolution Global / Regional Simulations

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One-way nested Limited-Area Models (LAMs) are used in numerical weather prediction and regional climate modelling to downscale coarse-resolution global/regional simulations or analyses that are provided as the time-evolving Lateral Boundary Conditions (LBC). The LAM integrations are sensitively dependent on infinitesimally small modifications. The so-called twin simulations, i.e., LAM integrations identical in all respect, except having slightly different initial conditions, may with time lead to substantially different solutions. This phenomenon has been referred to as internal variability (IV) in the existing literature [e.g., Giorgi and Bi, 2000; Christensen et al., 2001; Rinke et al., 2004; Lucas-Picher et al., 2008a; Crétat et al., 2011; Done et al., 2014].
Internal variability is usually quantified in terms of the inter-member standard deviation between the simulations pertaining to the different initial conditions. In extended-range LAM integrations conducted over months to years, the IV varies with several factors that include the synoptic situation, season of a year, the size and position of the computational domain and the spatial and temporal scales under consideration. For computational domains centered over midlatitudes, IV is typically larger in summer [e.g., Caya and Biner, 2004], increases with the size of the computational domain [Alexandru et al., 2007; Rapaić et al., 2011] and increases downstream with respect to the inflow lateral boundaries [e.g.,
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