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Adèle Révelard, Claude Frankignoul, Nathalie Sennéchael, Young-Oh Kwon, and Bo Qiu

. Transient eddy activity and fluxes were estimated from high-pass daily values, using the Blackmon filter to retain fluctuations with periods between 2 and 8 days ( Blackmon and Lau 1980 ; Hurrell and Deser 2009 ). In addition, the latent and sensible heat fluxes were taken from the 1° objectively analyzed air–sea fluxes (OAFlux) product provided by the Woods Hole Oceanographic Institution ( Yu and Weller 2007 ). Sea ice cover (SIC) and snow cover extent (SCE) datasets provided by NOAA/National Climatic

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Kotaro Katsube and Masaru Inatsu

; potential temperature; and density of dry air, water vapor, cloud water, cloud ice, snow, and graupel. The model also includes state-of-the-art physical parameterizations such as cloud microphysics ( Ikawa and Saito 1991 ), atmospheric radiative transfer ( Sugi et al. 1990 ), turbulent mixing ( Kumagai and Saito 2004 ), boundary layer processes ( Sun and Chang 1986 ), and surface flux estimations ( Sommeria 1976 ; Louis et al. 1982 ). Convective precipitation is compensated by the Kain–Fritsch scheme

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Benoît Vannière, Arnaud Czaja, Helen Dacre, and Tim Woollings

1. Introduction The long-term climatological impact of the SST gradient on the atmosphere has been identified both in observations and numerical experiments. The meanderings of the ocean fronts are tightly related to mesoscale features of the low-level atmosphere, such as the curl and divergence of wind stress ( Xie 2004 ; Chelton et al. 2004 ) and cloud cover ( Small et al. 2008 ). Minobe et al. (2008) proposed a climatological pathway by which the Gulf Stream SST gradient affects the

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Xiaohui Ma, Ping Chang, R. Saravanan, Raffaele Montuoro, Hisashi Nakamura, Dexing Wu, Xiaopei Lin, and Lixin Wu

. Finally, a summary of major findings and discussion are presented in section 6 . 2. Regional climate simulations a. Model configuration Similar to Ma et al. (2015) and Willison et al. (2013) , in this study we use the Weather Research and Forecasting (WRF) Model developed by NCAR ( Skamarock et al. 2008 ). The model setup follows Ma et al. (2015) closely, and a brief description of the model is given below for completeness. The computational domain covers the entire North Pacific from 3.6° to 66

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