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The impact of precipitation in shallow cumulus convection on the moisture variance and third-order moments of moisture is investigated with the help of large-eddy simulations. Three idealized simulations based on the Rain in Cumulus over the Ocean field experiment are analyzed: one nonprecipitating, on a smaller domain, and two precipitating cases, on a larger domain with different initial profiles of moisture. Results show that precipitation and the associated cloud organization lead to increased generation of higher-order moments (HOM) of moisture compared to the nonprecipitating case. To understand the physical mechanism and the role of individual processes in this increase, budgets of HOM of moisture are studied. Microphysics directly decreases the generation of HOM of moisture, but this effect is not dominant. The gradient production term is identified as the main source term in the HOM budgets. The influence of the gradient production term on moisture variance is further examined separately in cloud active and nonactive regions. The main contribution to the gradient production term comes from the smaller cloud active region because of the stronger moisture flux. Further analyses of the horizontal and vertical cross sections of moisture fluctuations show that the precipitation-induced downdrafts and updrafts are the main mechanism for the generation of moisture variance. The variance increase is linked to shallow dry downdraft regions with horizontal divergence in the subcloud layer, moist updrafts with horizontal convergence in the bulk cloud layer, and finally wider areas of horizontal divergence in the cloud inversion layer.
The ICON single-column mode
(2021)
The single-column mode (SCM) of the ICON (ICOsahedral Nonhydrostatic) modeling framework is presented. The primary purpose of the ICON SCM is to use it as a tool for research, model evaluation and development. Thanks to the simplified geometry of the ICON SCM, various aspects of the ICON model, in particular the model physics, can be studied in a well-controlled environment. Additionally, the ICON SCM has a reduced computational cost and a low data storage demand. The ICON SCM can be utilized for idealized cases—several well-established cases are already included—or for semi-realistic cases based on analyses or model forecasts. As the case setup is defined by a single NetCDF file, new cases can be prepared easily by the modification of this file. We demonstrate the usage of the ICON SCM for different idealized cases such as shallow convection, stratocumulus clouds, and radiative transfer. Additionally, the ICON SCM is tested for a semi-realistic case together with an equivalent three-dimensional setup and the large eddy simulation mode of ICON. Such consistent comparisons across the hierarchy of ICON configurations are very helpful for model development. The ICON SCM will be implemented into the operational ICON model and will serve as an additional tool for advancing the development of the ICON model.
An update of the two-energy turbulence scheme is presented, the 2TE + APDF scheme. The original version of the two-energy scheme is able to successfully model shallow convection without the need of an additional parameterization for non-local fluxes. However, the performance of the two-energy scheme is worse in stratocumulus cases, where it tends to overestimate the erosion of the stable layers. We have identified the causes: the non-local stability parameter does not consider local stratification, the scheme lacks an internal parameter that could distinguish between a shallow convection regime and a stratocumulus regime, and it uses an inflexible turbulence length scale formulation. To alleviate this problem, we propose several modifications: an update of the stability parameter, a modified computation of the turbulence length scale, and the introduction of the entropy potential temperature to distinguish between a shallow convection and a stratocumulus regime. In addition, the two-energy scheme is coupled to a simplified assumed probability density function method in order to achieve a more universal representation of the cloudy regimes. The updated turbulence scheme is evaluated for several idealized cases and one selected real case in the ICOsahedral Nonhydrostatic (ICON) modeling framework. The results show that the updated scheme corrects the overmixing problem in the stratocumulus cases. The performance of the updated scheme is comparable to the operational setup, and can be thus used instead of the operational turbulence and shallow convection scheme in ICON. Additionally, the updated scheme improves the coupling with dynamics, which is beneficial for the modeling of coherent flow structures in the atmospheric boundary layer.
The most frequently used boundary-layer turbulence parameterization in numerical weather prediction (NWP) models are turbulence kinetic energy (TKE) based-based schemes. However, these parameterizations suffer from a potential weakness, namely the strong dependence on an ad-hoc quantity, the so-called turbulence length scale. The physical interpretation of the turbulence length scale is difficult and hence it cannot be directly related to measurements or large eddy simulation (LES) data. Consequently, formulations for the turbulence length scale in basically all TKE schemes are based on simplified assumptions and are model-dependent. A good reference for the independent evaluation of the turbulence length scale expression for NWP modeling is missing. Here we propose a new turbulence length scale diagnostic which can be used in the gray zone of turbulence without modifying the underlying TKE turbulence scheme. The new diagnostic is based on the TKE budget: The core idea is to encapsulate the sum of the molecular dissipation and the cross-scale TKE transfer into an effective dissipation, and associate it with the new turbulence length scale. This effective dissipation can then be calculated as a residuum in the TKE budget equation (for horizontal sub-domains of different sizes) using LES data. Estimation of the scale dependence of the diagnosed turbulence length scale using this novel method is presented for several idealized cases.
Measurements of vertical velocity from vertically pointing Doppler lidars are used to derive the profiles of normalized vertical velocity variance. Observations were taken during the FESSTVaL (Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg) campaign during the warm seasons of 2020 and 2021. Normalized by the square of the convective velocity scale, the average vertical velocity variance profile follows the universal profile of Lenschow et al. (1980). However, daily profiles still show a high day-to-day variability. We found that moisture transport and the content of moisture in the boundary layer could explain the remaining variability of the normalized vertical velocity variance. The magnitude of the normalized vertical velocity variance is highest on clear-sky days and decreases as the absolute humidity increases and surface latent heat flux decreases on cloud-topped days. This suggests that moisture content and moisture transport are limiting factors for the intensity of turbulence in the convective boundary layer. We also found that the intensity of turbulence decreases with an increase in the boundary layer cloud fraction during FESSTVaL, while the latent heating in the cloud layer was not a relevant source of turbulence in this case. We conclude that a new vertical velocity scale has to be defined that would take into account the moist processes in the convective boundary layer.
Measurements of vertical velocity from vertically pointing Doppler lidars are used to derive the profiles of vertical velocity variance. Observations were taken during the FESSTVaL (Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg) campaign during the warm seasons of 2020 and 2021. Normalized by the square of convective velocity scale, the average vertical velocity variance profile follows the universal profile of Lenschow et al. (1980), however, daily profiles still show a high day-to-day variability. We found that moisture transport and the content of moisture in the boundary layer could explain the remaining variability of the normalized vertical velocity variance. The magnitude of the normalized vertical velocity variance is highest on clear-sky days, and decreases as the relative humidity increase and surface latent heat flux decrease in cloud-topped and rainy days. This suggests that moisture content and moisture transport are limiting factors for the intensity of turbulence in the convective boundary layer. We also found that the intensity of turbulence decreases with an increase in boundary layer cloud fraction during FESSTVaL, while the latent heating in the cloud layer was not a relevant source of turbulence in this case. We conclude that a new vertical velocity scale has to be defined that would take into account the moist processes in the convective boundary layer.
We evaluate the influence of a forest parametrization on the simulation of the boundary layer flow over moderate complex terrain in the context of the Perdigão 2017 field campaign. The numerical simulations are performed using the Weather Research and Forecasting model in large eddy simulation mode (WRF-LES). The short-term, high-resolution (40 m horizontal grid spacing) and long-term (200 m horizontal grid spacing) WRF-LES are evaluated for an integration time of 12 h and 1.5 months, respectively, with and without forest parameterization. The short-term simulations focus on low-level jet events over the valley, while the long-term simulations cover the whole intensive observation period (IOP) of the field campaign. The results are validated using lidar and meteorological tower observations. The mean diurnal cycle during the IOP shows a significant improvement of the along-valley wind speed and the wind direction when using the forest parametrization. However, the drag imposed by the parametrization results in an underestimation of the cross-valley wind speed, which can be attributed to a poor representation of the land surface characteristics. The evaluation of the high-resolution WRF-LES shows a positive influence of the forest parametrization on the simulated winds in the first 500 m above the surface.
We evaluate the influence of a forest parametrization on the simulation of the boundary layer flow over moderate complex terrain in the context of the Perdigão 2017 field campaign. The numerical simulations are performed using the Weather Research and Forecasting model in large eddy simulation mode (WRF-LES). The short-term, high-resolution (40 m horizontal grid spacing) and long-term (200 m horizontal grid spacing) WRF-LES are evaluated for an integration time of 12 h and 1.5 months, respectively, with and without forest parameterization. The short-term simulations focus on low-level jet events over the valley, while the long-term simulations cover the whole intensive observation period (IOP) of the field campaign. The results are validated using lidar and meteorological tower observations. The mean diurnal cycle during the IOP shows a significant improvement of the along-valley wind speed and the wind direction when using the forest parametrization. However, the drag imposed by the parametrization results in an underestimation of the cross-valley wind speed, which can be attributed to a poor representation of the land surface characteristics. The evaluation of the high-resolution WRF-LES shows a positive influence of the forest parametrization on the simulated winds in the first 500 m above the surface.
Diurnal valley winds frequently form over complex topography, particularly under fair weather conditions, and have a significant impact on the local weather and climate. Since diurnal valley winds result from complex and multi-scale interactions, their representation in numerical weather prediction models is challenging. Better understanding of these local winds based on observations is crucial to improve the accuracy of the forecasts. This study investigates the diurnal evolution of the three-dimensional mean wind structure in a deep Alpine valley, the Rhone valley at Sion, using data from a radar wind profiler and a surface weather station operated continuously from 1 September 2016 to 17 July 2017. In particular, the wind profiler data was analyzed for a subset of days on which fair weather conditions allowed for the full development of thermally driven winds. A pronounced diurnal cycle of the wind speed, as well as a reversal of the wind direction twice per day is documented for altitudes up to about 2 km above ground level (AGL) in the warm season and less than 1 km AGL in winter. The diurnal pattern undergoes significant changes during the course of the year. Particularly during the warm-weather months of May through to September, a low-level wind maximum occurs, where mean maximum up-valley velocities of 8–10 m s−1 are found between 15–16 UTC at altitudes around 200 m AGL. In addition, during nighttime, a down-valley jet with maximum wind speeds of 4–8 m s−1 around 1 km AGL is found. A case study of a three-day period in September 2016 illustrates the occurrence of an elevated layer of cross-valley flow around 1–1.5 km AGL.
We evaluate the near-surface representation of thermally driven winds in the Swiss Alps in a numerical weather prediction model at km-scale resolution. In addition, the influence of grid resolution (2.2 km and 1.1 km), topography filtering, and land surface datasets on the accuracy of the simulated valley winds is investigated. The simulations are evaluated against a comprehensive set of surface observations for an 18-day fair-weather summer period in July 2006. The episode is characterized by strong diurnal wind systems and the formation of shallow convection over the mountains, which transitions to precipitating convection in some areas. The near-surface winds (10 m above ground level) follow a typical diurnal pattern with strong daytime up-valley flow and weaker nighttime down-valley flow. At a 2.2 km resolution the valley winds are poorly simulated for most stations, while at a 1.1 km resolution the diurnal cycle of the valley winds is well represented in most large (e.g., Rhein valley at Chur and Rhone valley at Visp) and medium-sized valleys (e.g., Linth valley at Glarus). In the smaller valleys (e.g., Maggia valley at Cevio), the amplitude of the valley wind is still significantly underestimated, even at a 1.1 km resolution. Detailed sensitivity experiments show that the use of high-resolution land surface datasets, for both the soil characteristics as well as for the land cover, and reduced filtering of the topography are essential to achieve good performance at a 1.1 km resolution