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Y. C. He, P. W. Chan, and Q. S. Li

1. Introduction Wind measurement offers the essential data source for a wide range of practices in the fields of meteorology and wind engineering, such as weather forecasting ( Stauffer et al. 1991 ), wind energy assessment ( Shu et al. 2015 ), wind-disaster mitigation, and wind-resistant design ( Irwin 2006 ). Unfortunately, because of the terrain/topographic/height effects ( He et al. 2013 , 2014a ) as well as the influences caused by measurement systems ( Beljaars 1987 ), in situ

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Kirsty E. Hanley, Stephen E. Belcher, and Peter P. Sullivan

1. Introduction Ocean surface waves are the medium that transfer momentum across the air–sea interface. Currently, all operational ocean–atmosphere models only allow the momentum flux τ tot to be positive, from atmosphere to ocean. Recent observations during conditions when waves propagate faster than the wind have reported upward momentum flux from the waves to the atmosphere (e.g., Drennan et al. 1999 ; Grachev and Fairall 2001 ) and the occurrence of low-level wave-driven jets (e

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Scott Applequist

1. Introduction Wind roses are histograms that depict the joint relative frequency of wind speed and direction. These diagrams are used in runway orientation, air-quality modeling, and wind-energy planning, to name only a few uses. A well-known methodological bias exists in the creation of wind roses from directional wind data. In brief, the practice of reporting wind direction at discrete 10° increments and analyzing them in a 360° range divided into 16 equally spaced, 22.5°-wide bins results

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Fabrice Ardhuin, T. H. C. Herbers, Kristen P. Watts, Gerbrant Ph van Vledder, R. Jensen, and Hans C. Graber

1. Introduction Wave forecasting and hindcasting is based on a large body of theory (e.g., Komen et al. 1994 ; Janssen 2004 ), which is often insufficient to fully account for complex flows near the ocean surface. For engineering purposes and to provide a benchmark for modeling wave growth, many studies have used dimensional analysis following Kitaigorodskii (1962) and established empirical relations between the wave spectrum and the fetch or duration of wind forcing, water depth, and wind

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Jonny W. Malloy, Daniel S. Krahenbuhl, Chad E. Bush, Robert C. Balling Jr., Michael M. Santoro, Joshua R. White, Renée C. Elder, Matthew B. Pace, and Randall S. Cerveny

wind lull” is defined as “a marked decrease in the wind speed” ( Glickman 2000 , p. 845). If we adapt that definition for long-term surface winds, we can define a wind lull as an extended period of abnormally calm or weak surface winds. The concept of protracted weak or calm winds could exacerbate poor air-quality conditions (e.g., Chen and Xie 2013 ; Munir et al. 2013 ; Onat and Stakeeva 2013 ; Zhu and Liang 2013 ) or cause intermittent wind-farming energy generation (e.g., Archer and

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Elad Shilo, Yosef Ashkenazy, Alon Rimmer, Shmuel Assouline, and Yitzhaq Mahrer

.g., Csanady 1976 ; Saylor et al. 1980 ; Mysak 1985a , b ), the effect of external forcing on their characteristics has received little attention. The effects of wind stress and bottom friction on topographic waves were addressed by Huang and Saylor (1982 , hereafter HS82 ), in their analysis of the topographic (vorticity) wave dynamics in the southern basin of Lake Michigan. Interaction of a free vortex mode with a forced mode was suggested as the mechanism for the generation of topographic waves

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Walker S. Ashley and Alan W. Black

1. Introduction Severe windstorms are responsible for many casualties each year in the United States. While investigations have examined casualties due to tornadoes (e.g., Galway 1975 ; Brown et al. 2002 ; Brooks and Doswell 2002 ; Ashley 2007 ), severe convective wind events ( Ashley and Mote 2005 ), and hurricanes ( Rappaport 2000 ), no known studies have explored specifically the casualties caused by wind phenomena such as downslope and gap winds, gradient winds, dust storms, and other

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Xudong Liang

patterns) are only moved by winds and there is no growth or decay. However, the TREC method does not take into account the velocity information directly. Recently, some more sophisticated wind retrieval methods that use prognostic equations or numerical models as strong or weak constraints in a variational framework have been developed (e.g., Sun et al. 1991 ; Kapitza 1991 ; Qiu and Xu 1992 ; Xu et al. 1994a , b , 1995 ; Shapiro et al. 2003 ). Although using complicated constraints may give a

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Yvonne Käsler, Stephan Rahm, Rudolf Simmet, and Martin Kühn

1. Measurement technique Lidar is a remote sensing technique that transmits a laser beam into the atmosphere and the backscattered light is detected. The pulsed Doppler wind lidar, which was used for the measurements in Bremerhaven, Germany, takes advantage of the fact that the center frequency of the received laser pulses is shifted compared to the outgoing pulses because of the Doppler effect, which occurs from backscattering on moving particles. This shift in frequency provides information

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Larry Mahrt

1. Introduction Motions on scales just larger than the turbulence are always present ( Anfossi et al. 2005 ) and cause substantial wind direction variation when the large-scale wind is weak. Such unpredictable wind direction changes cause complex transport of contaminants that are not adequately captured in models. Difficulties modeling wind variability is demonstrated in Belušić and Güttler (2010) . Wind direction changes include gradual meandering of the wind direction ( Kristensen et al

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