Abstract: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 fluctuat… Show more
“…The redistribution of soil moisture increases the large-area heterogeneity, but decreases the small-area heterogeneity. This is in accordance with Adler et al (2011);Kang and Bryan (2011), who found an influence of redistribution of soil moisture on the location of convective inition. Therefore, area "blue", mainly containing small convective cells, is more influenced than area "red" with the large advected precipitation band.…”
supporting
confidence: 92%
“…Despite to the systematic effect on partitioning of the heat fluxes, precipitation reacts less systematically on soil moisture variations Hohenegger et al, 2009). The distribution and inhomogeneity of soil moisture patterns may initiate secondary circulation (Clark et al, 2004;Adler et al, 2011;Kang and Bryan, 2011;Dixon et al, 2013;Maronga and Raasch, 2013;Froidevaux et al, 10 2014).…”
Abstract. Soil moisture influences the occurrence of convective precipitation. Therefore an accurate knowledge of soil moisture might be useful for an improved prediction of convective cells. But still the model uncertainty overshadows the impact of soil moisture in realistic cases even in 1 km resolution and therefore convection resolving models. Only drastic soil moisture changes can exhibit the model uncertainties but the systematic behaviour is still complex and depends strongly on the strength of soil moisture change.
5Here we performed seven experiments with modified soil moisture using an ensemble approach for each experiment. Only a 50% soil moisture enhancement and a complete dried soil impact precipitation patterns considerably in structure, amplitude and location in certain analysis areas. Both, the enhanced and reduced soil moisture result in a reduced precipitation rate.Replacing the soil moisture by a realistic field from different days influences the precipitation insignificantly. We point out the need for uncertainty estimations in soil moisture studies.
“…The redistribution of soil moisture increases the large-area heterogeneity, but decreases the small-area heterogeneity. This is in accordance with Adler et al (2011);Kang and Bryan (2011), who found an influence of redistribution of soil moisture on the location of convective inition. Therefore, area "blue", mainly containing small convective cells, is more influenced than area "red" with the large advected precipitation band.…”
supporting
confidence: 92%
“…Despite to the systematic effect on partitioning of the heat fluxes, precipitation reacts less systematically on soil moisture variations Hohenegger et al, 2009). The distribution and inhomogeneity of soil moisture patterns may initiate secondary circulation (Clark et al, 2004;Adler et al, 2011;Kang and Bryan, 2011;Dixon et al, 2013;Maronga and Raasch, 2013;Froidevaux et al, 10 2014).…”
Abstract. Soil moisture influences the occurrence of convective precipitation. Therefore an accurate knowledge of soil moisture might be useful for an improved prediction of convective cells. But still the model uncertainty overshadows the impact of soil moisture in realistic cases even in 1 km resolution and therefore convection resolving models. Only drastic soil moisture changes can exhibit the model uncertainties but the systematic behaviour is still complex and depends strongly on the strength of soil moisture change.
5Here we performed seven experiments with modified soil moisture using an ensemble approach for each experiment. Only a 50% soil moisture enhancement and a complete dried soil impact precipitation patterns considerably in structure, amplitude and location in certain analysis areas. Both, the enhanced and reduced soil moisture result in a reduced precipitation rate.Replacing the soil moisture by a realistic field from different days influences the precipitation insignificantly. We point out the need for uncertainty estimations in soil moisture studies.
“…Here we use the numerical model "Cloud Model version 1" (CM1) that has been used for several LES studies in recent years (e.g., Kang and Bryan 2011;Kang et al 2012;Wang 2014;Nowotarski et al 2014;Markowski and Bryan 2016). Details of the model used here, including a new "two part" subgrid model near the surface, are provided in the Appendix.…”
A method to simulate characteristics of wind speed in the boundary layer of tropical cyclones in an idealized manner is developed and evaluated. The method can be used in a single-column modelling set-up with a planetary boundary-layer parametrization, or within large-eddy simulations (LES). The key step is to include terms in the horizontal velocity equations representing advection and centrifugal acceleration in tropical cyclones that occurs on scales larger than the domain size. Compared to other recently developed methods, which require two input parameters (a reference wind speed, and radius from the centre of a tropical cyclone) this new method also requires a third input parameter: the radial gradient of reference wind speed. With the new method, simulated wind profiles are similar to composite profiles from dropsonde observations; in contrast, a classic Ekman-type method tends to overpredict inflow-layer depth and magnitude, and two recently developed methods for tropical cyclone environments tend to overpredict near-surface wind speed. When used in LES, the new technique produces vertical profiles of total turbulent stress and estimated eddy viscosity that are similar to values determined from low-level aircraft flights in tropical cyclones. Temporal spectra from LES produce an inertial subrange for frequencies 0.1 Hz, but only when the horizontal grid spacing 20 m.
“…Garcia-Carreras et al (2011) explained the reasons for a preferred location of shallow convective clouds on the front of the mesoscale circulations. Recently, Kang and Bryan (2011) studied the effect of the amplitude of the surface heterogeneity on the transition to deep convection by prescribing sinusoidal surface fluxes of various amplitudes. As the amplitude becomes larger the area of mesoscale convergence becomes narrower and stronger and will lead to an earlier transition to deep convection.…”
This study analyzes the effects of land surface heterogeneities at various horizontal scales on the transition from shallow to deep convection and on the cloud size distribution. An idealized case of midlatitude summertime convection is simulated by means of large-eddy simulations coupled to an interactive land surface. The transition is accelerated over heterogeneous surfaces. The simulation with an intermediate patch size of 12.8 km exhibits the fastest transition with a transition time two-thirds that over a homogeneous surface. A similar timing is observed for the precipitation onset whereas the total accumulated rainfall tends to increase with patch size. The cloud size distribution can be approximated by a power law with a scale break. The exponent of the power law is independent of the heterogeneity scale, implying a similar cloud cover between the simulations. In contrast, the scale break varies with patch size. The size of the largest clouds does not scale with the boundary layer height, although their maximum size scales with the patch size. Finally, the idea that larger clouds grow faster, known from homogeneous surface conditions, is not fully valid over heterogeneous surfaces. These various aspects can be understood from the complex interplay between the characteristics of the triggered mesoscale circulations and a cloud development acting in response to the diurnal cycle in surface heating. The results also call for adequate representation of such effects in convective parameterizations.
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