243 The Interaction between Cumulus and Microphysics Parameterization Schemes in WRF across Convective Grey Zone Resolutions: A Case Study.

Wednesday, 11 July 2018
Regency A/B/C (Hyatt Regency Vancouver)
Julia Jeworrek, University of British Columbia, Vancouver, BC, Canada; and R. B. Stull

Handout (3.0 MB)

Cumulus and microphysics parameterization schemes determine together the amount, the local intensity, the spatial extent and general organisation of the total precipitation in Numerical Weather Prediction (NWP) models. While microphysics parameterization schemes yield large-scale precipitation at grid-scale condensation by representing the complex processes inside a cloud, cumulus parameterization schemes account collectively for unresolved vertical motion that can cause additional convective precipitation. For coarse resolutions, deep convection must be parameterized. However, when decreasing the horizontal grid spacing one enters the convective grey zone where cumulus-cloud processes become partially resolved and traditional closure assumptions break down. Today only few cumulus schemes are scale aware and attempt to account for the transition from parameterized to explicitly resolved convective effects at this range of scales.

This case study explores the grid-scale dependent performance of different cumulus and microphysics schemes in WRF (version 3.9.1.1). Two precipitation events in the Southern Great Plains were investigated: a mesoscale convective system that caused rain rates of up to 35 mm/h, and a synoptic-scale low pressure system that caused extended frontal precipitation.

The choice of the cumulus parameterization appears to be crucial to the convective development in the NWP model, whereas different microphysics schemes produce very similar outcomes. The forecast error converges toward a minimum at approximately 3 kilometers grid spacing for most microphysics and cumulus schemes, except Kain-Fritsch, which shows little to no improvements at increased resolutions for this case study. Grell-Freitas produces the smallest errors for the mesoscale convective system and outperforms the other cumulus schemes in timing and intensity of the precipitation, resulting from a smooth transition from sub-grid (cumulus) to large-scale (microphysics) precipitation.

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