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Pengfei Xue, Jeremy S. Pal, Xinyu Ye, John D. Lenters, Chenfu Huang, and Philip Y. Chu

the Great Lakes region ( Williamson 1854 ). Fig . 1. (top) North American RCM model domain with topography. (bottom) Bathymetry of the North American Great Lakes with NDBC buoy station locations (black squares). Table 1. Morphometric information for the Great Lakes. The Great Lakes are not only sensitive to climate change, which is likely to have contributed to recent large fluctuations in lake level, thermal structure, and ice coverage, but they are also a significant regional climate driver

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Tanya L. Otte, Christopher G. Nolte, Martin J. Otte, and Jared H. Bowden

may not accurately represent local changes in temperature and precipitation extremes ( Dulière et al. 2011 ; Werth and Garrett 2011 ). To predict the local effects of climate change, the GCM fields can be projected to local scales using a regional climate model (RCM) by applying dynamical downscaling techniques (e.g., Giorgi 1990 ). The RCM may then be used to inform problem-focused climate assessments that address community goals and values ( Tryhorn and DeGaetano 2011 ). To interpret climate

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Csaba Torma, Erika Coppola, Filippo Giorgi, Judit Bartholy, and Rita Pongrácz

regional climate conditions during the twenty-first century, such as drier and hotter summers over central Europe. Moreover, studies with different greenhouse gas emission scenarios show that Europe is one of the earth’s most sensitive regions to global warming ( Giorgi 2006 ), and that the Carpathian basin is located in a transition region of the precipitation change pattern ( Giorgi and Coppola 2007 ). High-resolution climate model simulations are thus needed to provide accurate climate change

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Bart J. J. M. van den Hurk and Erik van Meijgaard

circulation model (GCM) outputs focusing on the role of LCL, clouds, and radiation on the local land–atmosphere interaction. Also, regional climate models (RegCMs) have been used by a number of authors to assess the sensitivity of the regional hydroclimate to anomalous moisture conditions. Like the work of Findell and Eltahir (2003b) , both positive and negative feedbacks are found depending on the governing conditions and processes ( Schär et al. 1999 ; Kanamitsu and Mo 2003 ; Cook et al. 2006

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Tanya L. Spero, Christopher G. Nolte, Megan S. Mallard, and Jared H. Bowden

historical conditions; for regional climate modeling, the reference state originates from a global climate model’s coarse realization of the atmosphere. The nudging terms can also be scaled to account for the accuracy and representativeness of the reference state at the modeled location, in addition to the time scale of the phenomena that are simulated. Nudging began in limited-area NWP [expansions of the acronyms used in this paper can be found online ( https://www.ametsoc.org/PubsAcronymList )] as a

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S. H. Rasmussen, J. H. Christensen, M. Drews, D. J. Gochis, and J. C. Refsgaard

). However, the resolution of nearly all GCMs is presently too coarse to adequately represent regional and local climate conditions. Downscaling of GCM results for especially precipitation is therefore required for many purposes. Statistical downscaling relies on a combination of climate model output and present-day climatologies derived from observations. In contrast, dynamical downscaling by regional climate models (RCMs) relies solely on model output and attempts to present a more physically

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Kerstin Stahl, Lena M. Tallaksen, Lukas Gudmundsson, and Jens H. Christensen

1. Introduction Large-scale gridded models, including global (general circulation) and regional climate models and large-scale hydrological models, are employed for a variety of purposes in hydrology and related disciplines. They provide spatial simulations of hydrological variables such as soil moisture, runoff, and river discharge for historical records and can be used to simulate the response of the hydrological cycle to future global change, that is, climate scenarios and human impacts

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Philippe Lucas-Picher, Daniel Caya, Sébastien Biner, and René Laprise

1. Introduction Regional climate models (RCMs) have been widely used for more than 15 yr to simulate climate at the regional scale ( Giorgi 1990 ). RCMs allow climate simulations with high spatial resolutions that are not accessible with general circulation models (GCMs) or objective reanalyses (RAs). The RCM approach consists of using a fine-resolution grid over a limited-area domain, which requires to be fed at its boundaries by large-scale information usually taken from a GCM or RA. Initial

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J. F. Scinocca, V. V. Kharin, Y. Jiao, M. W. Qian, M. Lazare, L. Solheim, G. M. Flato, S. Biner, M. Desgagne, and B. Dugas

1. Introduction At the Canadian Centre for Climate Modelling and Analysis (CCCma), a new regional climate model, the CCCma Regional Climate Model (CanRCM4), has been developed. CanRCM4’s novelty does not arise from the method of solution in its dynamical core or the climate-based physics package it employs. Both of these are well known and currently operational for global model applications. The novelty of CanRCM4 stems from a new philosophy of coordinating the development and application of

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Sara A. Rauscher, Anji Seth, Brant Liebmann, Jian-Hua Qian, and Suzana J. Camargo

rainfall. This may be of particular importance for South America because of the presence of the South American low-level jet (SALLJ). Located just to the east of the Andes Mountains, the jet is a mesoscale feature that plays a strong role in transporting moisture from tropical to subtropical South America ( Virji 1981 ; Paegle 1998 ; Berbery and Barros 2002 ; Marengo et al. 2002 , 2004 ; Vera et al. 2006 ). Regional climate models can be used to identify these mesoscale dynamical processes (i

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