A Bimodal Diagnostic Cloud Fraction Parameterization. Part I: Motivating Analysis and Scheme Description

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.

Sensitivity of cloud‐radiative effects to cloud fraction parametrizations in tropical, midlatitude, and arctic kilometre‐scale simulations

“…Previous studies have shown that surface precipitation, mainly in the Tropics, is better captured with the PC2 scheme than with diagnostic CF schemes (Bush et al ., 2020; Dipankar et al ., 2020; Van Weverberg et al ., 2021a). This is mainly evident in the overall structure of the precipitations events, such as squall lines (Dipankar et al ., 2020).…”

“…Previous studies (Bush et al ., 2020; Dipankar et al ., 2020; Van Weverberg et al ., 2021a)) have shown that though diagnostic CF schemes tend to be better at capturing midlatitude low‐level cloud and surface radiation, prognostic CF schemes better represent high‐level cloud and surface precipitation, especially in the Tropics.…”

The Regional Coupled Suite (RCS-IND1): application of a flexible regional coupled modelling framework to the Indian region at kilometre scale

“…In common with the wind speed results, it will be valuable to re-examine the impact of using revised RAL configurations on the RCS-IND1 precipitation characteristics. For example, development of a new bimodal diagnostic cloud fraction (Van Weverberg et al, 2021) and cloud microphysics (e.g. Hill et al, 2015) parameterizations in RAL offer pathways towards improving the frequency distribution of simulated precipitation.…”

A Bimodal Diagnostic Cloud Fraction Parameterization. Part II: Evaluation and Resolution Sensitivity

“…A second additional configuration uses the Smith cloud scheme, but rather than using a prescribed and time-invariant profile of RHcrit, it diagnoses variances from the turbulence parameterization, following Van Weverberg et al (2016) (SMITH-TKE). Subgrid saturation-departure variance s 2 s in this configuration is estimated as follows:…”

“…Most of the stratocumulus cloud (highlighted by the dotted area) resides well within this region of high variability. The RHcrit parameterization described in Van Weverberg et al (2016) imposes a resolution-dependent minimum limit on the RHcrit, based on aircraft observations. From Fig.…”