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Francis Codron, Augustin Vintzileos, and Robert Sadourny

interior. The most important modification concerns the horizontal water vapor advection scheme: moisture can be advected up mountain slopes along the terrain-following coordinates from a warm grid point to a much colder one. In reality, if supersaturation occurs on the way, the advected water vapor partly precipitates before reaching the summit. But if the temperature difference is not taken into account by the advection scheme, all the moisture reaches the colder point, leading to an systematic

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Justin M. Glisan, William J. Gutowski Jr., John J. Cassano, and Matthew E. Higgins

. Pan-Arctic WRF We use version 3.1.1 of the Advanced Research Weather Research and Forecasting model (ARW-WRF) ( Skamarock et al. 2008 ). Selection of Arctic-appropriate physical parameterizations was an important consideration for our model simulations. This parameterization set is similar to the choices developed by Cassano et al. (2011) for Arctic simulation, with further modifications based on work by M. Seefeldt (2010, unpublished data). We use the subgrid cumulus scheme developed in Grell

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Ruidan Chen, Zhiping Wen, and Riyu Lu

heat, cold, drought, storm, and flood events, EH is reported to be the most prominent cause of weather-related human mortality ( CDC 2004 ; WMO 2013 ). Moreover, EH threatens social and economic activities, increasing the consumption of electricity and water and inducing forest fires and crop losses ( Valor et al. 2001 ; Zhang and Wang 2002 ; Peng et al. 2004 ; Coumou and Rahmstorf 2012 ). Therefore, EH has become an important public concern and detailed investigation into the causes of EH

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Nauman K. Awan, H. Truhetz, and A. Gobiet

(NCAR) Mesoscale Model (MM5) ( Dudhia 1993 ) and the National Centers for Environmental Prediction –NCAR Weather Research and Forecasting (WRF) model ( Skamarock et al. 2007 ). Both models are primarily used in numerical weather prediction (NWP) but are applied with some modifications for long-term simulations in climate mode as well. The applicability of MM5 as an RCM has been frequently demonstrated, for example, in Zhu and Liang (2007) and Fernández et al. (2007) , while the application of WRF

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R. W. Higgins, V. B. S. Silva, V. E. Kousky, and W. Shi

1. Introduction A major challenge for the climate community is to provide information that decision makers can directly apply to reduce vulnerability to climate risk. While probabilistic forecasts of seasonal mean quantities (such as precipitation and surface temperature over the conterminous United States) have proven utility, they do not address questions relating to the specific character of the daily weather statistics within the season. User requests for products that expand beyond

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P. J. Rasch and J. E. Kristjánsson

estimated monthly mean estimates for the years of 1979–93. Thus the simulation is an extension of an AMIP style integration. b. Modification to the standard CCM3 In spite of the general quality of the simulation discussed above, there are significant biases in the model simulations. There is a persistent polar cold bias of 2–6 K in the lower troposphere in both hemispheres when compared to analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) or National Centers for Environmental

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Gonzalo Miguez-Macho, Georgiy L. Stenchikov, and Alan Robock

rotating the pole ( Wang et al. 1999 ). However, the nested approach is more economical, and in this study, we will use it for climate downscaling. The nested model technique is used routinely for short-to-medium-range weather prediction, but its extension for simulations lasting extended periods of time to produce climate statistics is relatively new and is the subject of active research and controversy. Giorgi and Mearns (1999) , for example, present an overview of several issues regarding regional

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Qingtao Song, Dudley B. Chelton, Steven K. Esbensen, and Andrew R. Brown

–sea interaction on oceanic mesoscales is especially pronounced in the Antarctic Circumpolar Current (ACC) and in all of the western boundary current systems and their eastward extensions into the interior ocean. The SST influence on surface winds is evident in numerical weather prediction (NWP) models to varying degrees, depending on the resolution of the SST fields used as the surface boundary condition ( Chelton 2005 ; Chelton and Wentz 2005 ; Maloney and Chelton 2006 ; Song et al. 2009 ; Chelton and

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Robert J. Trapp and Kimberly A. Hoogewind

, geographical coexistence of supercell thunderstorms, which are responsible for most (though not all) devastating tornadoes (e.g., Trapp et al. 2005 ; Duda and Gallus 2010 ), and a squall line, which predominately generates swaths of straight-line wind damage, is not uncommon. It is partly for this reason that convective-weather–climate applications of high-resolution regional models were introduced by Trapp et al. (2011) and then further implemented by Robinson et al. (2013) and Gensini and Mote

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David I. Duncan, Christian D. Kummerow, and Gregory S. Elsaesser

1. Introduction Clouds, precipitation, and their effects on the local environment are inextricably linked, yet are often treated separately. New paradigms that seek to exploit the relationship between cloud and precipitation states offer some hope to link the two disciplines. Studies that have endeavored to categorize “weather states” have approached the issue from the perspective of either classifying similar cloud states (e.g., Jakob and Tselioudis 2003 ; Rossow et al. 2005 ) or

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