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  • Author or Editor: Georg J. Mayr x
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Georg J. Mayr and Laurence Armi

Abstract

The potential for a stably stratified air mass upstream of the Sierra Nevada (California) to descend as foehn into the nearly 3-km-deep Owens Valley was studied for the 2 March 2006 case with observations from sondes, weather stations, and two aircraft flights. While upstream conditions remained almost unchanged throughout the day, strong diurnal heating on the downstream side warmed the valley air mass sufficiently to permit flow through the passes to descend to the valley floor only in the late afternoon. Potential temperatures of air crossing the crest were too warm to descend past a virtual floor formed by the strong potential temperature step at the top of the valley air mass, the height of which changed throughout the day primarily due to diurnal heating in the valley. The descending stably stratified flow and its rebound with vertical velocities as high as 8 m s−1 were shaped by the underlying topography and the virtual valley floor.

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Laurence Armi and Georg J. Mayr

Abstract

Cross-barrier density differences and westerly flow established a descending stratified flow across the Sierra Nevada (United States) on 9–10 April 2006. Downslope flow and an internal hydraulic jump occurred only when the potential temperature of the westerly descending flow was at least as cold as the existing upvalley-flowing valley air mass. The onset was observed in sequences of visible satellite images and with weather stations. The University of Wyoming King Air flew through the stratified flow and imaged the structure of the internal hydraulic jump with its cloud radar. Shear-layer instabilities, which first developed near the jump face, grew and paired downstream, mixing the internal hydraulic jump layer. A single wave response to the downslope flow and internal hydraulic jump was observed aloft, but only after the downslope flow had become established.

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Laurence Armi and Georg J. Mayr

Abstract

A combination of real and virtual topography is shown to be crucial to describe the essentials of stratified flow over mountain ranges and leeside valleys. On 14 March 2006 [Intensive Observation Period 4 of the Terrain-Induced Rotor Experiment (T-REX)], a nearly neutral cloud-filled layer, capped by a strong density step, overflowed the Sierra Nevada and separated from the lee slope upon encountering a cooler valley air mass. The flow in this lowest layer was asymmetric across and hydraulically controlled at the crest with subcritical flow upstream and supercritical flow downstream. The density step at the top of this flowing layer formed a virtual topography, which descended 1.9 km and determined the horizontal scale and shape of the flow response aloft reaching into the stratosphere. A comparison shows that the 11 January 1972 Boulder, Colorado, windstorm case was similar: hydraulically controlled at the crest with the same strength and descent of the virtual topography. In the 18 February 1970 Boulder case, however, the layer beneath the stronger virtual topography was subcritical everywhere with a symmetric dip across the Continental Divide of only 0.5 km. In all three cases, the response and strength of the flow aloft depend on the virtual topography. The layer up to the next strong density step at or near the tropopause was hydraulically supercritical for the 18 February case, subcritical for the T-REX case, and critically controlled for the 11 January case, for which a weak density step and isolating layer aloft made possible the strong response aloft for which it is famous.

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David Plavcan, Georg J. Mayr, and Achim Zeileis

Abstract

Diagnosing foehn winds from weather station data downwind of topographic obstacles requires distinguishing them from other downslope winds, particularly nocturnal ones driven by radiative cooling. An automatic classification scheme to obtain reproducible results that include information about the (un)certainty of the diagnosis is presented. A statistical mixture model separates foehn and no-foehn winds in a measured time series of wind. In addition to wind speed and direction, it accommodates other physically meaningful classifiers such as the (potential) temperature difference to an upwind station (e.g., near the crest) or relative humidity. The algorithm was tested for Wipp Valley in the central Alps against human expert classification and a previous objective method (), which the new method outperforms. Climatologically, using only wind information gives nearly identical foehn frequencies as when using additional covariables. A data record length of at least one year is required for satisfactory results. The suitability of mixture models for objective classification of foehn at other locations will have to be tested in further studies.

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Susanne Drechsel, Georg J. Mayr, Jakob W. Messner, and Reto Stauffer

Abstract

Wind speed measurements from one year from meteorological towers and wind turbines at heights between 20 and 250 m for various European sites are analyzed and are compared with operational short-term forecasts of the global ECMWF model. The measurement sites encompass a variety of terrain: offshore, coastal, flat, hilly, and mountainous regions, with low and high vegetation and also urban influences. The strongly differing site characteristics modulate the relative contribution of synoptic-scale and smaller-scale forcing to local wind conditions and thus the performance of the NWP model. The goal of this study was to determine the best-verifying model wind among various standard wind outputs and interpolation methods as well as to reveal its skill relative to the different site characteristics. Highest skill is reached by wind from a neighboring model level, as well as by linearly interpolated wind from neighboring model levels, whereas the frequently applied 10-m wind logarithmically extrapolated to higher elevations yields the largest errors. The logarithmically extrapolated 100-m model wind reaches the best compromise between availability and low cost for data even when the vertical resolution of the model changes. It is a good choice as input for further statistical postprocessing. The amplitude of measured, height-dependent diurnal variations is underestimated by the model. At low levels, the model wind speed is smaller than observed during the day and is higher during the night. At higher elevations, the opposite is the case.

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