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Larry W. O’Neill, Dudley B. Chelton, and Steven K. Esbensen

-scale perturbations in the crosswind and downwind components of the SST gradient, respectively ( Chelton et al. 2001 , 2004 , 2007 ; Chelton 2005 ; O’Neill et al. 2003 , 2005 ). The surface wind stress curl and divergence fields are related linearly to the crosswind and downwind SST gradients, respectively. These curl and divergence dependencies are simulated to varying degrees in numerical weather predication and climate models ( Maloney and Chelton 2006 ; Haack et al. 2008 ) and in regional mesoscale

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Edmund K. M. Chang and Yunfei Fu

1. Introduction The midlatitude storm tracks are locations where cyclones/anticyclones and baroclinic waves are most prevalent. These storms/waves bring strong winds and weather to the surface observers, while transporting large amounts of heat and momentum poleward as part of the maintenance of the global circulation. Thus there are two popular ways to define the storm tracks. The first takes advantage of the weather-generating potential of these cyclones and define storm

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James Doss-Gollin, Ángel G. Muñoz, Simon J. Mason, and Max Pastén

-to-seasonal predictions. Fig . 1. Topographical map of the study area. Colors indicate log 10 of elevation (m) from the Global Land 1-km Base Elevation Project (available online at http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NGDC/.GLOBE/.topo/ ). (a) All of South America, with the domains of the LPRB and the domain used for weather typing indicated in red and blue boxes, respectively. (b) As in (a), the LPRB is marked with a red box. (Streamflow time series shown in Fig. 3 were taken from the four stations

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Dorian J. Burnette, David W. Stahle, and Cary J. Mock

, instrumentation changes, and station relocations, and these observations have only limited overlap with the modern standardized measurements of the U.S. National Weather Service. These problems can introduce serious discontinuities into early temperature records and make it difficult to recover unbiased daily temperature time series. The scarcity of observations also makes it difficult to screen and correct individual records, which has been done extensively in the relatively data-rich context of Western

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Nicole Feldl, Bruce T. Anderson, and Simona Bordoni

does latent heat release modify the response? The impact of Arctic changes on midlatitude weather patterns, including jet stream position and variability, is a particular topic of debate. Though a few studies have linked weather extremes to high-latitude warming ( Francis and Vavrus 2012 ), analyses of the observational record are hindered by large internal variability ( Screen et al. 2014 ). A number of recent studies in fact suggest decreasing trends in cold weather extremes associated with

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Larry W. O’Neill, Steven K. Esbensen, Nicolai Thum, Roger M. Samelson, and Dudley B. Chelton

realistic, high-resolution, three-dimensional numerical simulation using the Weather Research and Forecasting (WRF) mesoscale model. This study is the first dynamical analysis of mesoscale wind–SST interactions in the extratropical Southern Ocean. Unique aspects of this region relevant for this simulation include: strong background winds between 10 and 16 m s −1 averaged over the 1-month simulation period; a much larger range of surface sensible heat flux perturbations of 80–100 W m −2 than seen in

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Rasmus A. Pedersen, Ivana Cvijanovic, Peter L. Langen, and Bo M. Vinther

1. Introduction The drastic Arctic sea ice decline observed in recent years ( Vaughan et al. 2013 ) has motivated an increased scientific focus on the impacts of sea ice loss on weather and climate. The surface energy balance is affected by sea ice loss through surface albedo changes and as a result of a reduction of the insulating layer between the ocean and the atmosphere ( Stroeve et al. 2012b ). These characteristics mean that sea ice loss initiates feedbacks that contribute directly to

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James J. Hack, Jeffrey T. Kiehl, and James W. Hurrell

. Most aspects of the model’s dynamical formulation and implementation are identical to the CCM2. The most important changes to the model formulation have been made to the collection of parameterized physics. When compared to the CCM2, changes to the physics most relevant to the global hydrological cycle fall into three major categories: modifications to the representation of radiative transfer through both clear and cloudy atmospheric columns; modifications to the atmospheric boundary layer, moist

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Axel J. Schweiger, Ron W. Lindsay, Steve Vavrus, and Jennifer A. Francis

known, however, to play a role in the various mechanisms that have been proposed over the years to explain the large annual cycle of clouds over the Arctic Ocean, which is characterized by fewer clouds during winter than summer (see Beesley and Moritz 1999 for a review). Prevailing theories are 1) air mass modification: moist, warm air from the warmer continents (summer) is advected over the colder sea ice, where it cools to saturation; 2) lack of moisture source: during winter the pack ice cannot

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Achim Stössel

on sea ice by affecting the oceanic stratification, and thus the vertical oceanic heat flux that affects sea ice (e.g., Marsland and Wolff 2001 ). Through this interaction with sea ice, these two atmospheric variables strongly affect the rates of deep- and bottom-water formation, and therefore the long-term deep-ocean properties. For a sea ice–ocean GCM that is not coupled to a GCM of the atmosphere, (re)analyses from numerical weather prediction centers are considered the most reliable source

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