“Log-Chipper” Turbulence in the Convective Boundary Layer

Kimmel, Shari J.; Wyngaard, J. C.; Otte, Martin J.

doi:10.1175/1520-0469(2002)059<1124:lctitc>2.0.co;2

Cited by 14 publications

(9 citation statements)

References 23 publications

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“…Some previous studies also have employed the wave cut-off filter to decompose complex multi-scale atmospheric flows into mean and turbulent parts (e.g. Kimmel et al, 2002;Kang and Lenschow, 2014). The wave cut-off filter passes Fourier components of longer (or shorter) wavelengths than the cut-off wavelength and rejects those of shorter (or longer) wavelengths in the low-pass (or high-pass) form.…”

Section: ; Lemonementioning

confidence: 99%

Response of moist convection to multi‐scale surface flux heterogeneity

Kang

Ryu

2016

Quart J Royal Meteoro Soc

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We investigate the response of moist convection to the spatial variation of surface sensible heat flux (SHF) in a mesoscale domain during the evolution of the afternoon convective boundary layer (CBL), using large-eddy simulation. The surface SHF heterogeneity in the domain is analytically created as a function of the spectral slope in the wavelength range from a few tens of kilometres to a few hundreds of metres in the SHF spectrum on a log-log scale. Assuming surface energy balance and spatially uniform available energy, the prescribed SHF has a phase lag of 180• with respect to the latent heat flux (LHF) in the domain. Two sets of three simulations are forced by heterogeneous surface SHF fields, which are characterized by similar statistics. One set, however, is created with a spectral slope of k −3 (where k is wave number) and the other with a slope of k −2 . All of the simulations are integrated with the same observation-based initial sounding favourable for moist convection.In all of the k

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Section: ; Lemonementioning

confidence: 99%

Response of moist convection to multi‐scale surface flux heterogeneity

Kang

Ryu

2016

Quart J Royal Meteoro Soc

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“…T . In addition, mesoscale fluctuations in advected scalars (here temperature) may yield an extra production of variance as shown by Kimmel et al (2002). Such effects of shear and advection might generally also apply to C 2 q .…”

Section: Validation Of the Les Profiles With Cabauw Observations Cmentioning

confidence: 99%

Derivation of Structure Parameters of Temperature and Humidity in the Convective Boundary Layer from Large-Eddy Simulations and Implications for the Interpretation of Scintillometer Observations

Maronga

Moene

Dinther

et al. 2013

Boundary-Layer Meteorol

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We derive the turbulent structure parameters of temperature C 2 T and humidity C 2 q from high-resolution large-eddy simulations (LES) of a homogeneously-heated convective boundary layer. Boundary conditions and model forcing were derived from measurements at Cabauw in The Netherlands. Three different methods to obtain the structure-parameters from LES are investigated. The shape of the vertical structure-parameter profiles from all three methods compare well with former experimental and LES results. Depending on the method, deviations in the magnitude up to a factor of two are found and traced back to the effects of discretization and numerical dissipation of the advection scheme. Furthermore, we validate the LES data with airborne and large-aperture scintillometer (LAS) measurements at Cabauw. Virtual path measurements are used to study the variability of C 2 T in the mixed layer and surface layer and its implications for airborne and LAS measurements. A high variability of C 2 T along a given horizontal path in the LES data is associated with plumes (high values) and downdrafts (low values). The path average of C 2 T varies rapidly in time due to the limited path length. The LES results suggest that measured path averages require sufficient temporal averaging and an adequate ratio of path length to height above the ground for the LAS in order to approach the domain average of C 2 T .

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“…To decompose LES variables into mesoscale and turbulent components, we use a sharp-cutoff filter in Fourier space (e.g., Moeng and Wyngaard 1988;Kimmel et al 2002;Wyngaard 2010). In this study, the surface heat flux heterogeneity is imposed only in the x direction, as shown in (1) and (2).…”

Section: B Scale Decompositionmentioning

confidence: 99%

A Large-Eddy Simulation Study of Moist Convection Initiation over Heterogeneous Surface Fluxes

Kang

Bryan

2011

Mon. Wea. Rev.

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This study uses large-eddy simulations to investigate processes of moist convection initiation (CI) over heterogeneous surface fluxes. Surface energy balance is imposed via a 1808 phase lag of the surface moisture flux (relative to the sensible heat flux), such that the relatively warm surface is relatively dry (and the relatively cool surface is relatively wet). As shown in previous simulations, a mesoscale circulation forms in the presence of surface-flux heterogeneity, which coexists with turbulent fluctuations. The mesoscale convergence zone of this circulation develops over the relatively warm surface, and this is where clouds first form. Convection initiation occurs sooner as the amplitude of the heterogeneity increases, and as the surface moisture increases (i.e., Bowen ratio decreases). Shallow clouds initiate when boundary layer heights (z i ) become greater than the lifting condensation level (LCL). Deep precipitating clouds initiate when the LCL and level of free convection (LFC) are roughly the same when averaged over the relatively warm surface, which is equivalent to the mean convective inhibition (CIN) becoming nearly zero. From the perspective of the entire (mesoscale) domain, cases with strongly heterogeneous surfaces have a wider distribution of both z i and LCL. Thus, a comparison of z i with LCL over a mesoscale area (i.e., within one mesoscale model grid box) may lead to misleading conclusions about CI and cloud-base height. It is also shown that as the amplitude of the surfaceflux heterogeneity increases the mesoscale convergence zone becomes narrower and stronger. Furthermore, CI occurs earlier over relatively wet surfaces partly because turbulent eddies are more vigorous owing to slightly greater buoyancy.

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“Log-Chipper” Turbulence in the Convective Boundary Layer

Cited by 14 publications

References 23 publications

Response of moist convection to multi‐scale surface flux heterogeneity

Response of moist convection to multi‐scale surface flux heterogeneity

Derivation of Structure Parameters of Temperature and Humidity in the Convective Boundary Layer from Large-Eddy Simulations and Implications for the Interpretation of Scintillometer Observations

A Large-Eddy Simulation Study of Moist Convection Initiation over Heterogeneous Surface Fluxes

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