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Yingtao Ma, Rachel T. Pinker, Margaret M. Wonsick, Chuan Li, and Laura M. Hinkelman

1. Introduction a. Background Snow-covered mountain ranges are a major source of water supply for runoff and groundwater recharge. Snowmelt supplies as much as 75% of the surface water in basins of the western United States ( Beniston 2006 ). Factors that affect the rate of snowmelt include incoming shortwave (SW) and longwave radiation; surface albedo; snow emissivity and temperature; sensible, latent, and ground heat fluxes; and energy transferred to the snowpack from deposited snow or rain

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David A. Rutan, Seiji Kato, David R. Doelling, Fred G. Rose, Le Trang Nguyen, Thomas E. Caldwell, and Norman G. Loeb

more complex than at the TOA, as it requires a radiative transfer model and satellite-derived properties of clouds and aerosols and atmospheric state from either satellites or reanalysis. Underlying assumptions in the radiative transfer model calculations and ancillary input data error increases the uncertainty in the surface radiation budget estimates. Furthermore, it is known that the diurnal cycle of clouds and their contribution to the diurnal cycle of surface radiant flux must be taken into

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Liping Zhang, Lixin Wu, and Jiaxu Zhang

1. Introduction Changes of freshwater flux can lead to changes in ocean salinity, currents, and temperature (e.g., Carton 1991 ; Reason 1992 ; Schmitz 1996 ; Murtugudde and Busalacchi 1998 ), which may in turn further feed back to the atmosphere (e.g., Zhang et al. 1999 ; Wu et al. 2010 ). Modeling studies have shown that a suppression of the freshwater flux in the coupled ocean–atmosphere system can lead to warming over the global oceans with more significant warming in high latitudes

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J. Mann, A. Peña, F. Bingöl, R. Wagner, and M. S. Courtney

1. Introduction Measurements of the vertical flux of horizontal momentum are important for understanding the atmosphere and for testing models of the atmospheric flow over terrain. Methods of extracting the momentum flux from conically scanning Doppler lidars have been described before, for example, by Eberhard et al. (1989) and Gal-Chen et al. (1992) . Techniques for analyzing lidar data are very similar to those applied to radars. Apart from the vertical flux of horizontal momentum, the

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Liguo Su, Richard L. Collins, David A. Krueger, and Chiao-Yao She

heat fluxes (i.e., u ′ w ′ , υ ′ w ′ , w ′ T  ′ ), and the resultant forcing of the mean flow due to the vertical gradients in these fluxes, places even greater demands on the accuracy and precision of the measurements. Measurements of the momentum flux have attracted the most attention because the formulation of the gravity wave forcing arises in the momentum equations of the general circulation, and radar systems capable of measuring winds have been operated since the 1980s ( Vincent and Reid

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Øyvind Saetra, Jon Albretsen, and Peter A. E. M. Janssen

1. Introduction In numerical ocean modeling, the momentum fluxes from the atmosphere to the ocean are traditionally calculated from the wind speed provided by an atmospheric model, using a drag coefficient relating the 10-m winds to the surface stress. With this formulation, the surface fluxes are dependent on the local wind speed only. There are at least two problems with this approach. First, unless care is taken that the identical formulation for the momentum flux is used as a boundary

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Ivan B. Savelyev, Brian K. Haus, and Mark A. Donelan

1. Introduction Momentum transfer from a shear flow to a wavy boundary has been of great interest throughout the past century. Solution of this problem for light wind conditions has lead to a better understanding of air–sea interaction and its influence on ocean and atmosphere dynamics. To fully parameterize air–sea fluxes, the influence of the surface wave state must be taken into account. Therefore, it is important to resolve both wind-wave and wind-current momentum fluxes for various wind

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David Rivas, Antoine Badan, Julio Sheinbaum, José Ochoa, and Julio Candela

1. Introduction The direct evaluation of buoyancy fluxes is a difficult issue in many oceanographic situations (e.g., in frontal eddies and currents), because it requires knowing the vertical currents, which are generally small (except, e.g., in convection phenomena, where these can be 2–8 cm s −1 ; Lilly et al. 1999 ), often of a few millimeters per second, and hence unresolved by most measurements. Nonetheless, observational studies like that of Schott and Johns (1987) in the Somali

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Brian S. Chinn and Sarah T. Gille

1. Introduction Eddy heat fluxes are thought to be important contributors to the time-mean ocean heat transport ( Jayne and Marotzke 2002 ). However, existing observations provide only a limited view of total eddy heat fluxes. Estimates from satellite data are confined to the surface layer of the ocean and rely on a number of assumptions ( Keffer and Holloway 1988 ; Stammer 1998 ). Subsurface estimates from current meter data are restricted to the specific locations at which current meters

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Hilary Spencer, Rowan Sutton, and Julia M. Slingo

; Codron et al. 2001 ; Wang and An 2002 ; Guilyardi et al. 2004 ; Toniazzo 2006 ; Guilyardi 2006 ; Brown et al. 2006, manuscript submitted to Climate Dyn .; Dong and Sutton 2007 ). One approach that has frequently been used to improve simulations of the mean state in coupled climate models is the application of “flux corrections” (e.g., Knutson and Manabe 1994 ; Sausen et al. 1988 ; Latif et al. 1988 ; Johns et al. 1997 ; AchutaRao and Sperber 2002 ; Davey et al. 2002 ). Heat flux

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