Predictability of Flows over Complex Terrain

Paegle, Jan; Pielke, Roger A.; Dalu, G.; Miller, William C.; Garratt, J. R.; Vukićević, Tomislava; Berri, Guillermo J.; Nicolini, María G.

doi:10.1007/978-1-935704-25-6_10

Cited by 15 publications

(6 citation statements)

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“…Strong downward flow, which is characterized by strong advection of horizontal momentum, low pressure, and relatively warm temperatures, is typical in the lee side of mountainous ridges where forced ascent occurs on the windward side [Paegal et al, 1990;Cotton and Anthes, 1989;Wallace and Hobbs, 1977;Lin, 1986]. Thermodynamically, the result is to force the dry adiabatic descent of air parcels in the lee side and to reduce precipitation drastically (rain shadow effect (see Figure l a)).…”

Section: Through Numerical Experimentation Smolarckiewiczmentioning

confidence: 99%

“…In the latter case, transient dynamics inherent to the interaction between orographically and thermally originated gravity waves determine the formation, splitting, and regeneration of unstable clouds (cumulus), and the triggering of thunderstorms [Lin, 1986;Cotton and Anthes, 1989;Banta, 1990]. Unstable clouds and thunderstorms are a warm season feature (late spring and summer), during which synoptic conditions are weaker, hence allowing the development of such regional mesoscale circulations as mountain-valley winds and land breezes [Paegal et al, 1990;Pielke, 1984]. …”

Section: Through Numerical Experimentation Smolarckiewiczmentioning

confidence: 99%

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Dynamic modeling of orographically induced precipitation

Barros

Lettenmaier²

1994

Reviews of Geophysics

214

118

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Local orography governs the triggering of cloud formation and the enhancement of processes such as condensation and hydrometeor nucleation and growth in mountainous regions. Intense, lengthy precipitation events are typical upwind of the topographic divide, with sharply decreasing magnitude and duration on the lee side. Differences in mean annual precipitation of several hundred percent between windward slopes of orographic barriers and adjacent valleys or lee side slopes are not unusual. Because much of the streamflow in areas such as the western United States is derived from mountainous areas that are remote and often poorly instrumented, modeling of orographic precipitation has important implications for water resources management. Models of orographically induced precipitation differ by their treatment of atmospheric dynamics and by the extent to which they rely on bulk parameterization of cloud and precipitation physics. Adiabatic ascent and a direct proportionality between precipitation efficiency and orographically magnified updrafts are the most frequent assumptions in orographic precipitation modeling. Space-time discretization (i.e., resolution) is a major issue because of the high spatial variability of orographic precipitation. For a specific storm, relative errors as large as 50 to 100% are common in the forecast/hindcast of precipitation intensity and can be even larger in the case of catastrophic storms. When monthly or seasonal timescales are used to evaluate model performance, the magnitude of such errors decreases dramatically, reaching values as low as 10 to 15%. Current research is focusing on the development of data assimilation techniques to incorporate radar and satellite observations, and on the development of aggregation and disaggregation methodologies to address the implications of modeling a multiscale problem at restricted spatial and temporal resolutions.Under the same sky in which the stars pursue their orbits, as symbols of the unchangeable fullness of Nature, we see the clouds towering, the rain pouring, and the winds changing, as symbols--as it were--ofjust the opposite extreme, the most capricious of all processes in Nature, impossible to bring inside the fence of its Laws. H. von Helmholtz 1875 (as cited by Bergeron [1960a]) INTRODUCTIONMountains are a complex source of perturbations and deformation of atmospheric flows, the signature of which is detected over a wide range of time-space frequencies extending from the scale of boundary layer motions up to that of planetary waves [Namias, 1960;Smith, 1979;Kasahara, 1980;Wallace, 1987]. The influence of orography on the long-term spatial distribution of precipitation is readily observable in mountainous areas. For instance, Figures la and 1 b show the distribution of annual precipitation along east-west transects at the Canadian/U.S. border and through the Coast Range and Sierra Nevada Moun-•Now at Department of Civil and Environmental Engineering, Pennsylvania State University, University Park. tains of California. Orography expl...

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Section: Through Numerical Experimentation Smolarckiewiczmentioning

confidence: 99%

Section: Through Numerical Experimentation Smolarckiewiczmentioning

confidence: 99%

Dynamic modeling of orographically induced precipitation

Barros

Lettenmaier²

1994

Reviews of Geophysics

214

118

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“…In seminal work, argued that the rapid upscale propagation of uncertainties in the specification of initial conditions would limit the predictability of mesoscale motions with spatial scales on the order of 10 km to time scales on the order of 1 h. While early practical experience with numerical weather prediction (NWP) led many to believe that known mesoscale forcing, such as terrain or lateral boundary conditions, may act to constrain error growth and extend the predictability of certain motions (e.g., Anthes et al 1985;Paegle et al 1990;Mass et al 2002), more recent work has suggested that mesoscale predictability is not only limited by rapid upscale growth of initially small-scale errors as originally suggested by Lorenz, but even faster downscale growth of synoptic-scale errors (Reinecke and Durran 2009;Rotunno and Snyder 2008;Durran and Gingrich 2014). We begin this section by highlighting several examples which demonstrate how initial condition uncertainty can limit the predictability of terrain-induced gravity wave breaking and turbulence and then address the role of model error in mesoscale predictability.…”

Section: Predictability Of Mountain Waves and Mountainmentioning

confidence: 99%

Aviation Turbulence

2016

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“…In principle, the predictability of convective precipitation should be increased over orography (Paegle et al, 1990), where vertical motions owing to specific topographic features can locally remove the convective inhibition and initiate cells (Done et al, 2006). However, for this enhanced predictability to be realized the initial and boundary conditions on the larger scales must be sufficiently accurate, and high-resolution grids are needed to represent the fine-scale terrain details.…”

Section: Introductionmentioning

confidence: 99%

Ensemble predictability of an isolated mountain thunderstorm in a high‐resolution model

Hanley

Kirshbaum

Belcher

et al. 2011

Quart J Royal Meteoro Soc

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Convective-scale ensemble simulations with perturbed initial conditions are performed to investigate the physical mechanisms, sensitivities and predictability of convective precipitation for a well-observed event from the Convective and Orographically induced Precipitation Study (COPS). On this day an isolated thunderstorm developed over the Black Forest mountains in southwest Germany that was initiated by thermally driven low-level convergence. With the default ensemble configuration, none of the members simulated any deep convection. A soil moisture and atmospheric moisture deficiency was found to be responsible for a lack of boundary layer moisture in the analysis. Correction of this moisture bias yielded an ensemble in which some members produced a realistic convective storm. In contrast, other members only produced shallow convection. A robust feature of the members that simulated the storm was that an impinging upper-level disturbance to the west had progressed further east towards the COPS region. This led to increased westerly winds aloft, which when mixed down into the boundary layer acted to feed a deeper layer of moist valley air into the convergent mountain circulation. The simulations reveal a very strong sensitivity to uncertainties in the large-scale flow as well as the boundary layer structure and stability.

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Predictability of Flows over Complex Terrain

Cited by 15 publications

References 0 publications

Dynamic modeling of orographically induced precipitation

Dynamic modeling of orographically induced precipitation

Aviation Turbulence

Ensemble predictability of an isolated mountain thunderstorm in a high‐resolution model

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