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[1] The occurrence of mid-latitude windstorms is related to strong socio-economic effects. For detailed and reliable regional impact studies, large datasets of high-resolution wind fields are required. In this study, a statistical downscaling approach in combination with dynamical downscaling is introduced to derive storm related gust speeds on a highresolution grid over Europe. Multiple linear...

This paper explores the benefits and limitations of using a inspector/executor approach for Software Distributed Shared Memory (SDSM) systems. The role of the inspector is to obtain a description of the address space accessed during the execution of parallel loops. The information collected by the inspector will enable the runtime to optimize the movement of shared data that will happen during ...

Rainfall is one of the climatic elements in tropics which very influential agriculture, especially determining growing season. Thus, proper rainfall modeling needed to help determine best time start cultivating soil. can be done using Statistical Downscaling (SDS) method. SDS a statistical model field climatology analyze relationship between large-scale and small-scale climate data. This study ...

Spatially explicit precipitation data is often responsible for the prediction accuracy of hydrological and ecological models. Several statistical downscaling approaches have been developed to map precipitation at a high spatial resolution, which are mainly based on the valid conjugations between satellite-driven precipitation data and geospatial predictors. Performance of the existing approache...

This paper reviews methods that have been used to evaluate global climate simulations and to downscale global climate scenarios for the assessment of climate impacts on hydrologic systems in the Pacific Northwest, USA. The approach described has been developed to facilitate integrated assessment research in support of regional resource management. Global climate model scenarios are evaluated an...

A class of interacting superprocesses arising from branching particle systems with continuous spatial motions, called superprocesses with dependent spatial motion (SDSMs), has been introduced and studied in Wang [26] and Dawson et al. [8]. In this paper, we extend the model to allow discontinuous spatial motions. Under Lipschitz condition for coefficients, we show that under a proper rescaling,...

Since the TAR there have been numerous statistical downscaling (SD) studies but several important challenges remain largely unresolved (Leung et al., 2003). Foremost are questions surrounding the characterisation of predictor-predictand relationships, and the extent to which more sophisticated techniques can extract greater regional predictability. A significant fraction of articles were devote...