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Kenneth S. Gage and Earl E. Gossard


This review begins with a brief look at the early perspectives on turbulence and the role of Dave Atlas in the unfolding of mysteries concerning waves and turbulence as seen by powerful radars. The remainder of the review is concerned with recent developments that have resulted in part from several decades of radar and Doppler radar profiler research that have been built upon the earlier foundation.

A substantial part of this review is concerned with evaluating the intensity of atmospheric turbulence. The refractivity turbulence structure-function parameter C 2 n , where n is radio refractive index, is a common metric for evaluating the intensity of refractivity turbulence and progress has been made in evaluating its climatology. The eddy dissipation rate is a common measure of the intensity of turbulence and a key parameter in the Kolmogorov theory for locally homogeneous isotropic turbulence. Much progress has been made in the measurement of the eddy dissipation rate under a variety of meteorological conditions including within clouds and in the presence of precipitation. Recently, a new approach using dual frequencies has been utilized with improved results.

It has long been recognized that atmospheric turbulence especially under hydrostatically stable conditions is nonhomogeneous and layered. The layering means that the eddy dissipation and eddy diffusivity is highly variable especially in the vertical. There is ample observational evidence that layered fine structure is responsible for the aspect sensitive echoes observed by vertically directed very high frequency VHF profilers. In situ observations by several groups have verified that coherent submeter-scale structure is present in the refractivity field sufficient to account for the “clear air” radar echoes. However, despite some progress there is still no consensus on how these coherent structures are produced and maintained.

Advances in numerical modeling have led to new insights by simulating the structures observed by radars. This has been done utilizing direct numerical simulation (DNS) and large eddy simulation (LES). While DNS is especially powerful for examining the breaking of internal waves and the transition to turbulence, LES had been especially valuable in modeling the atmospheric boundary layer.

Internal gravity waves occupy the band of intrinsic frequencies bounded above by the Brunt–Väisälä frequency and below by the inertial frequency. These waves have many sources and several studies in the past decade have improved our understanding of their origin. Observational studies have shown that the amplitude of the mesoscale spectrum of motions is greater over mountainous regions than over flat terrain or oceans. Thus, it would appear that flow over nonuniform terrain is an important source for waves. Several numerical studies have successfully simulated the generation of internal waves from convection. Most of these are believed to result from deep convection with substantial wave motion extending into the upper troposphere, stratosphere, and mesosphere. Gravity waves known as convection waves are often seen in the stable free atmosphere that overlay convective boundary layers.

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David M. Schultz and Paul J. Roebber


Over 50 yr have passed since the publication of Sanders' 1955 study, the first quantitative study of the structure and dynamics of a surface cold front. The purpose of this chapter is to reexamine some of the results of that study in light of modern methods of numerical weather prediction and diagnosis. A simulation with a resolution as high as 6-km horizontal grid spacing was performed with the fifth-generation-Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) Mesoscale Model (MM5), given initial and lateral boundary conditions from the National Centers for Environmental Precipitation-National Center for Atmospheric Research (NCEP-NCAR) reanalysis project data from 17 to 18 April 1953. The MM5 produced a reasonable simulation af the front, albeit its strength was not as intense and its movement was not as fast as was analyzed by Sanders. The vertical structure of the front differed from that analyzed by Sanders in several significant ways. First, the strongest horizontal temperature gradient associated with the cold front in the simulation occurred above a surface-based inversion, not at the earth's surface. Second, the ascent plume at the leading edge of the front was deeper and more intense than that analyzed by Sanders. The reason was an elevated mixed layer that had moved over the surface cold front in the simulation, allowing a much deeper vertical circulation than was analyzed by Sanders. This structure is similar to that of Australian cold fronts with their deep, well-mixed, prefrontal surface layer. These two differences between the model simulation and the analysis by Sanders may be because upper-air data from Fort Worth, Texas, was unavailable to Sanders. Third, the elevated mixed layer also meant that isentropes along the leading edge of the front extended vertically. Fourth, the field of frontogenesis of the horizontal temperature gradient calculated from the three-dimensional wind differed in that the magnitude of the maximum of the deformation term was larger than the magnitude of the maximum of the tilting term in the simulation, in contrast to Sanders' analysis and other previously published cases. These two discrepancies may be attributable to the limited horizontal resolution of the data that Sanders used in constructing his cross section. Last, a deficiency of the model simulation was that the postfrontal surface superadiabatic layer in the model did not match the observed well-mixed boundary layer. This result raises the question of the origin of the well-mixed postfrontal boundary layer behind cold fronts. To address this question, an additional model simulation without surface fluxes was performed, producing a well-mixed, not superadiabatic, layer. This result suggests that surface fluxes were not necessary for the development of the well-mixed layer, in agreement with previous research. Analysis of this event also amplifies two research themes that Sanders returned to later in his career, First, a prefrontal wind shift occurred in both the observations and model simulation at stations in western Oklahoma. This prefrontal wind shift was caused by a lee cyclone departing the leeward slopes of the Rockies slightly equatorward of the cold front, rather than along the front as was the case farther eastward. Sanders' later research showed how the occurrence of these prefrontal wind shifts leads to the weakening of fronts. Second, this study shows the advantage of using surface potential temperature, rather than surface temperature, for determining the locations of the surface fronts on sloping terrain.

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Maike Ahlgrimm, Richard M. Forbes, Jean-Jacques Morcrette, and Roel A. J. Neggers

relevant observational data obtained during meteorological field campaigns (e.g., Holland and Rasmusson 1973 ; Yanai et al. 1973 ). An often-applied technique in model development has been the time integration of the suite of subgrid parameterizations in a single-column model (SCM) in an offline, “isolated” mode, using prescribed large-scale forcings and boundary conditions ( Randall et al. 1996 ). The absence of interaction with the larger scale simplifies the model analysis, giving insight into the

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Margaret A. LeMone, Wayne M. Angevine, Christopher S. Bretherton, Fei Chen, Jimy Dudhia, Evgeni Fedorovich, Kristina B. Katsaros, Donald H. Lenschow, Larry Mahrt, Edward G. Patton, Jielun Sun, Michael Tjernström, and Jeffrey Weil

drive the exchange of momentum, heat, and moisture between the surface and the atmosphere, and strongly affect human activities. “Boundary layer” has a specific meaning in theoretical and experimental fluid dynamics, and the ABL is both similar to and different from those boundary layers. It is similar in being directly affected by a surface, but different in scale (on the order of a kilometer rather than a meter or less). 1 Laboratory flows have well-defined boundary conditions, while Earth

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Larry K. Berg and Peter J. Lamb

radiosonde and surface flux measurements in conjunction with a one-dimensional atmospheric model to investigate the effect of soil moisture on a number of different boundary layer variables. This led to a methodology for describing the regional-scale fluxes. Based on their analysis they described two limiting cases: instances where conditions are limited by the thermodynamic properties of the atmosphere and instances where conditions are limited by soil properties. In the case defined as atmosphere

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David A. R. Kristovich, Eugene Takle, George S. Young, and Ashish Sharma

. Different types of crops are planted over regions tens to hundreds of kilometers across, irrigation alters the surface moisture conditions sometimes in large swaths, and the forested areas give way to prairies. To give a full accounting of the research on all boundary layer features driven by mesoscale land surface changes would be beyond the space allocated for this chapter. Therefore, we provide information on research on common examples of atmospheric responses to the surface, starting from thermally

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David Randall, Charlotte DeMott, Cristiana Stan, Marat Khairoutdinov, James Benedict, Rachel McCrary, Katherine Thayer-Calder, and Mark Branson

boundary conditions. In the study of Khairoutdinov and Randall (2001) , the CRM had a horizontal domain 64 grid columns wide, with a horizontal grid spacing of 4 km. Khairoutdinov and Randall dubbed the embedded CRM a “superparameterization.” The combination of a GCM with a superparameterization is now called a multiscale modeling framework (MMF), and the MMF based on the CAM is now called the SP-CAM. A second MMF was created by Tao et al. (2009) , using a different GCM and a different CRM. As of

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Steven K. Krueger, Hugh Morrison, and Ann M. Fridlind

horizontal wind components, and 4) horizontal pressure gradient, as well as the surface and top-of-atmosphere boundary conditions, all varying in time. Because of the difficulties of determining the large-scale horizontal wind’s advective tendency and the large-scale horizontal pressure gradient, the large-scale forcing for the horizontal wind is usually specified as a relaxation of the CRM’s horizontally averaged wind towards the observed wind, with a relaxation time scale of about 2 h. This relaxation

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Kerry Emanuel

boundary of the patch with gravity waves that are well outside the patch, and it is thus filtered from quasi-balanced systems. The idea that less-balanced modes might be unstable even if Charney–Stern–Fjørtoft–like sufficient conditions for stability are satisfied is strongly supported by the work of Zhong et al. (2009) , who showed using linear shallow water theory that while Rossby-type and inertia–gravity–type oscillations are clearly separable in the eye and outer regions of tropical cyclone

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Graham Feingold and Allison McComiskey

.g., Ackerman et al. 2003 ; Christensen and Stephens 2011 ); in severely CCN-limited situations, boundary layers can even collapse because cloud dissipates as fast as it is generated. It therefore becomes important to identify conditions in which the cloudy boundary layer is either sensitive or insensitive to the aerosol. The general picture that has emerged is that, under clean conditions that are apt to generate precipitation, increases in the aerosol do indeed increase cloud fraction and LWP, but in

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