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Sergey Malyshev, Elena Shevliakova, Ronald J. Stouffer, and Stephen W. Pacala

changes in near-surface climate (i.e., biophysical effect). While globally these biophysical effects of LULCC are thought to be small ( Findell et al. 2007 ), regionally they play an important role ( Pitman et al. 2009 ; Findell et al. 2009 ; Lawrence and Chase 2010 ; de Noblet-Ducoudré et al. 2012 ). Additionally, land-use activities alter the amount of carbon stored in the terrestrial ecosystem ( Ciais et al. 2013 ) and therefore contribute to the change of atmospheric CO 2 (i.e., biogeochemical

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Hyodae Seo, Shang-Ping Xie, Raghu Murtugudde, Markus Jochum, and Arthur J. Miller

can cause climate biases through multiple feedback processes in coupled climate models ( Lin 2007 ). A better assessment of the impact of BLs on climate requires an intercomparison exercise using the results from those climate models with and without the salinity and BL effects. These kinds of studies will help determine the extent to which common biases in the climate models can be attributed to BL errors. It will also help detect common and robust features of the sensitivity of the regional

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Axel Timmermann, Shayne McGregor, and Fei-Fei Jin

project into the next decades. The goal of our paper is to elucidate the effects of long-term wind changes on the regional characteristics of past and future sea level trends in the tropical southern Indo-Pacific region and to compare these regional projections with recent estimates of global mean future sea level rise. The paper is organized as follows. In section 2 we describe the simplified modeling approach applied to recent wind data and future wind projections from IPCC-type models to quantify

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E-S. Im, E. Coppola, F. Giorgi, and X. Bi

circulations (e.g., Giorgi and Mearns 1991 ; Feddema et al. 2005 ; Giorgi and Avissar 1997 ; Pielke 2001 ). It is therefore important to account for the effects of complex topography and land use in climate simulations. To fully capture the complexity of the topography and land surface structure, however, a resolution is required that is well beyond that achievable with present day global and even regional climate models used in multidecadal to centennial simulations. For this reason, different

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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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Guoyu Ren, Yaqing Zhou, Ziying Chu, Jiangxing Zhou, Aiying Zhang, Jun Guo, and Xuefeng Liu

urbanization effect reached 71%. If only the Beijing station is considered, the contribution of urban warming to the overall warming is as large as 80% ( Ren et al. 2007 ). However, Li et al. (2004) indicated a much weaker urban warming in some regions and the country as a whole by comparing SAT trends between rural and urban stations. It is clear that the issue of the possible influence of UHI effects on the present available global and regional mean SAT series has not yet been solved. Chinese

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Yongkang Xue, Fernando De Sales, Ratko Vasic, C. Roberto Mechoso, Akio Arakawa, and Stephen Prince

global and seasonal assessment of VBP effects on the water cycle. The assessment was conducted at the global scale (i.e., is not limited to one or two regions) in recognition of the strong interconnections between regional climates, and covers all seasons (i.e., is not limited to the summer). The impact at long temporal scales, however, is not addressed in this study. VBPs include (but are not limited to) radiative transfer in the canopy, moisture exchange between soil layers and extraction by roots

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Kathleen Huybers and Gerard H. Roe

-spaced dataset produced very similar results. However, climate data with a resolution of 0.5° cannot capture the full gamut of climatic effects in mountainous terrain. The unresolved details of small-scale precipitation patterns will not change the results regarding the overall contrast between maritime and continental climates or the general north–south trends due to the inherent spatial scale of the regional climate patterns. It is likeliest to make a difference in the predicted sensitivities of, and

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Zhuo Wang and Chih-Pei Chang

appreciable temperature change in the Indian Ocean. In a case study of the Asian monsoon onset in 1989, Wu and Zhang (1998) suggested that the earliest monsoon onset in the BoB is linked to the thermal and mechanical forcing of the Tibetan Plateau. Based on experiments using a simplified regional climate model, Sato and Kimura (2007) suggested that the Tibetan Plateau induces midtropospheric subsidence over northern India through the thermal and mechanical effects and that the gradual weakening and

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Xiuquan Wang, Guohe Huang, Jinliang Liu, Zhong Li, and Shan Zhao

local policymakers and climate researchers who are focusing on climate change impact assessment at regional scales ( Wang et al. 2014a ). In this study, we will develop high-resolution regional climate projections over Ontario using an ensemble modeling approach to provide reliable and ready-to-use climate scenarios for assessing plausible effects of future climatic changes. Specifically, we will adopt the Providing Regional Climates for Impacts Studies (PRECIS) regional climate modeling system to

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