Cloud‐resolving model intercomparison of an MC3E squall line case: Part I—Convective updrafts

Abstract

An intercomparison study of a midlatitude mesoscale squall line is performed using the Weather Research and Forecasting (WRF) model at 1 km horizontal grid spacing with eight different cloud microphysics schemes to investigate processes that contribute to the large variability in simulated cloud and precipitation properties. All simulations tend to produce a wider area of high radar reflectivity (Ze > 45 dBZ) than observed but a much narrower stratiform area. The magnitude of the virtual potential temperature drop associated with the gust front passage is similar in simulations and observations, while the pressure rise and peak wind speed are smaller than observed, possibly suggesting that simulated cold pools are shallower than observed. Most of the microphysics schemes overestimate vertical velocity and Ze in convective updrafts as compared with observational retrievals. Simulated precipitation rates and updraft velocities have significant variability across the eight schemes, even in this strongly dynamically driven system. Differences in simulated updraft velocity correlate well with differences in simulated buoyancy and low‐level vertical perturbation pressure gradient, which appears related to cold pool intensity that is controlled by the evaporation rate. Simulations with stronger updrafts have a more optimal convective state, with stronger cold pools, ambient low‐level vertical wind shear, and rear‐inflow jets. Updraft velocity variability between schemes is mainly controlled by differences in simulated ice‐related processes, which impact the overall latent heating rate, whereas surface rainfall variability increases in no‐ice simulations mainly because of scheme differences in collision‐coalescence parameterizations.

Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection‐Permitting Simulations Over the United States

“…Although graupel particles in MORR have slightly smaller diameters than THOM above the melting layer, they have faster fall speeds throughout the troposphere (Figure o). Since graupels are primarily produced in convective updrafts (Fan et al, ), they are generally associated with high radar reflectivity due to their high density and large size. Larger and slower falling graupel particles above 6 km in THOM are likely the cause for higher 40‐dBZ echo‐tops in the convective core regions compared to MORR shown in Figure d.…”

“…Studies comparing remote sensing and in situ observations with CPM simulations of MCSs show consistent high biases in ice hydrometeor size and their associated radar reflectivity across many commonly used microphysics parameterizations (Stanford et al, ; Varble, Zipser, Fridlind, Zhu, Ackerman, Chaboureau, Collis, et al, ). Comparison of model output to dual‐Doppler radar retrievals in both tropical maritime and midlatitude continental convection indicates that simulated convective‐scale updraft intensities in MCSs are systematically too strong, and stratiform region area and rainfall are consistently underestimated across almost all microphysics parameterizations (Fan et al, ; Varble, Zipser, Fridlind, Zhu, Ackerman, Chaboureau, Fan, et al, ). Because high‐quality simultaneous remote sensing and in situ observations of MCSs are difficult to obtain, they are only available from limited‐duration field campaigns.…”

Aerosol Impacts on Mesoscale Convective Systems Forming Under Different Vertical Wind Shear Conditions

“… and are the mean pressure and air density averaged over domain at a given height for each outputting time, respectively. This calculation follows Fan et al () and Houze () and includes both dynamic and buoyancy sources. The values of PPG at upper levels are negative, associated with the negative vertical gradients of 3‐D divergence (i.e., the dynamic source) and buoyancy (i.e., the buoyancy source).…”

Response of Extreme Precipitating Cell Structures to Atmospheric Warming

“…A single‐moment microphysics parameterization keeps the computational cost of our simulations on a feasible level. However, we note that the choice of the microphysics scheme can influence, for example, in‐cloud properties such as updraft velocities and latent heating, mostly through ice‐related processes (Fan et al, ). Moreover, the representation of ice‐related microphysics can affect the simulated response of extreme precipitation to surface warming (Singh & O'Gorman, ).…”