Search Results

You are looking at 1 - 5 of 5 items for

  • Author or Editor: Kwinten Van Weverberg x
  • All content x
Clear All Modify Search
Kwinten Van Weverberg

Abstract

Despite a number of studies dedicated to the sensitivity of deep convection simulations to the properties of the rimed ice species in microphysics schemes, no consensus has been achieved on the nature of the impact. Considering the need for improved quantitative precipitation forecasts, it is crucial that the cloud modeling community better understands the reasons for these differing conclusions and knows the relevance of these sensitivities for the numerical weather prediction. This study examines the role of environmental conditions and storm type on the sensitivity of precipitation simulations to the nature of the rimed ice species (graupel or hail). Idealized 3D simulations of supercells/multicells and squall lines have been performed in varying thermodynamic environments. It has been shown that for simulation periods of sufficient length (>2 h), graupel-containing and hail-containing storms produce domain-averaged surface precipitation that is more similar than many earlier studies suggest. While graupel is lofted to higher altitudes and has a longer residence time aloft than hail, these simulations suggest that most of this graupel eventually reaches the surface and the surface precipitation rates of hail- and graupel-containing storms converge. However, environmental conditions play an important role in the magnitude of this sensitivity. Storms in large-CAPE environments (typical of storms in the U.S. Midwest) are more sensitive than their low-CAPE counterparts (typical of storms in Europe) to the nature of the rimed ice species in terms of domain-average surface precipitation. Supercells/multicells are more sensitive than squall lines to the nature of the rimed ice species in terms of spatial precipitation distribution and peak precipitation, disregarding of the amount of CAPE.

Full access
Kwinten Van Weverberg, Nicole P. M. van Lipzig, and Laurent Delobbe

Abstract

In this research the impact of modifying the size distribution assumptions of the precipitating hydrometeors in a bulk one-moment microphysics scheme on simulated surface precipitation and storm dynamics has been explored for long-lived low-topped supercells in Belgium. It was shown that weighting the largest precipitating ice species of the microphysics scheme to small graupel results in an increase of surface precipitation because of counteracting effects. On the one hand, the precipitation formation process slowed down, resulting in lower precipitation efficiency. On the other hand, latent heat release associated with freezing favored more intense storms. In contrast to previous studies finding decreased surface precipitation when graupel was present in the microphysics parameterization, storms were rather shallow in the authors’ simulations. This left little time for graupel sublimation. The impact of size distribution assumptions of snow was found to be small, but more realistic size distribution assumptions of rain led to the strongest effect on surface precipitation. Cold pools shrunk because of weaker rain evaporation at the cold pool boundaries, leading to a decreased surface rain area.

Full access
Kwinten Van Weverberg, Cyril J. Morcrette, and Ian Boutle

Abstract

A wide range of approaches exists to account for subgrid cloud variability in regional simulations of the atmosphere. This paper addresses the following questions: (1) Is there still benefit in representing subgrid variability of cloud in convection-permitting simulations? (2) What is the sensitivity to the cloud fraction parameterization complexity? (3) Are current cloud fraction parameterizations scale-aware across convection-permitting resolutions? These questions are addressed for regional simulations of a six-week observation campaign in the US Southern Great Plains. Particular attention is given to a new diagnostic cloud fraction scheme with a bimodal subgrid saturation-departure PDF, described in Part I. The model evaluation is performed using ground-based remote sensing synergies, satellite-based retrievals and surface observations. It is shown that not using a cloud-fraction parameterization results in underestimated cloud frequency and water content, even for stratocumulus. The use of a cloud-fraction parameterization does not guarantee improved cloud property simulations, however. Diagnostic and prognostic cloud schemes with a symmetric subgrid saturation-departure PDF underestimate cloud fraction and cloud optical thickness, and hence overestimate surface shortwave radiation. These schemes require empirical bias-correction techniques to improve the cloud cover. The new cloud-fraction parameterization, introduced in Part I, improves cloud cover, liquid water content, cloud base height, optical thickness and surface radiation compared to schemes reliant on a symmetric PDF. Furthermore, cloud parameterizations using turbulence-based, rather than prescribed constant subgrid variances, are shown to be more scale-aware across convection-permitting resolutions.

Restricted access
Kwinten Van Weverberg, Andrew M. Vogelmann, Hugh Morrison, and Jason A. Milbrandt

Abstract

This paper investigates the level of complexity that is needed within bulk microphysics schemes to represent the essential features associated with deep convection. To do so, the sensitivity of surface precipitation is evaluated in two-dimensional idealized squall-line simulations with respect to the level of complexity in the bulk microphysics schemes of H. Morrison et al. and of J. A. Milbrandt and M. K. Yau. Factors examined include the number of predicted moments for each of the precipitating hydrometeors, the number and nature of ice categories, and the conversion term formulations. First, it is shown that simulations of surface precipitation and cold pools are not only a two-moment representation of rain, as suggested by previous research, but also by two-moment representations for all precipitating hydrometeors. Cold pools weakened when both rain and graupel number concentrations were predicted, because size sorting led to larger graupel particles that melted into larger raindrops and caused less evaporative cooling. Second, surface precipitation was found to be less sensitive to the nature of the rimed ice species (hail or graupel). Production of hail in experiments including both graupel and hail strongly depends on an unphysical threshold that converts small hail back to graupel, indicating the need for a more physical treatment of the graupel-to-hail conversion. Third, it was shown that the differences in precipitation extremes between the two-moment microphysics schemes are mainly related to the treatment of drop breakup. It was also shown that, although the H. Morrison et al. scheme is dominated by deposition growth and low precipitation efficiency, the J. A. Milbrandt and M. K. Yau scheme is dominated by riming processes and high precipitation efficiency.

Full access
Kwinten Van Weverberg, Cyril J. Morcrette, Ian Boutle, Kalli Furtado, and Paul R. Field

Abstract

Cloud fraction parameterizations are beneficial to regional, convection-permitting numerical weather prediction. For its operational regional mid-latitude forecasts, the UK Met Office uses a diagnostic cloud fraction scheme which relies on a unimodal, symmetric subgrid saturation-departure distribution. This scheme has been shown before to underestimate cloud cover and hence an empirically-based bias correction is used operationally to improve performance. This first of a series of two papers proposes a new diagnostic cloud scheme as a more physically-based alternative to the operational bias correction. The new cloud scheme identifies entrainment zones associated with strong temperature inversions. For model grid boxes located in this entrainment zone, co-located moist and dry Gaussian modes are used to represent the subgrid conditions. The mean and width of the Gaussian modes, inferred from the turbulent characteristics, are then used to diagnose cloud water content and cloud fraction. It is shown that the new scheme diagnoses enhanced cloud cover for a given grid-box mean humidity, similar to the current operational approach. It does so, however, in a physically meaningful way. Using observed aircraft data and ground-based retrievals over the Southern Great Plains in the US, it is shown that the new scheme improves the relation between cloud fraction, relative humidity and liquid water content. An emergent property of the scheme is its ability to infer skewed and bimodal distributions from the large-scale state that qualitatively compare well against observations. A detailed evaluation and resolution sensitivity study will follow in part II.

Restricted access