Abstract
Abstract. The representation of cloud microphysical processes contributes substantially to the uncertainty of numerical weather simulations. In part, this is owed to some fundamental knowledge gaps in the underlying processes due to the difficulty of observing them directly. On the path to closing these gaps, we present a setup for the systematic characterization of differences between numerical weather model and radar observations for convective weather situations. Radar observations are introduced which provide targeted dual-wavelength and polarimetric measurements of convective clouds with the potential to provide more detailed information about hydrometeor shapes and sizes. A convection-permitting regional weather model setup is established using five different microphysics schemes (double-moment, spectral bin (“Fast Spectral Bin Microphysics”, FSBM), and particle property prediction (P3)). Observations are compared to hindcasts which are created with a polarimetric radar forward simulator for all measurement days. A cell-tracking algorithm applied to radar and model data facilitates comparison on a cell object basis. Statistical comparisons of radar observations and numerical weather model runs are presented on a data set of 30 convection days. In general, simulations show too few weak and small-scale convective cells. Contoured frequency by altitude diagrams of radar signatures reveal deviations between the schemes and observations in ice and liquid phase. Apart from the P3 scheme, high reflectivities in the ice phase are simulated too frequently. Dual-wavelength signatures demonstrate issues of most schemes to correctly represent ice particle size distributions, producing too large or too dense graupel particles. Comparison of polarimetric radar signatures reveals issues of all schemes except the FSBM to correctly represent rain particle size distributions.
Highlights
In numerical weather models, clouds play an important role by strongly affecting, e.g., the radiation budget or the precipitation formation
They objectively compare simulated cell characteristics with observations over 4.5 d after applying a celltracking algorithm on their data. They found the simulated convective cells to reach higher altitudes on average compared to their radar observations, which is visible in our analysis. This is independent of the chosen cloud microphysics scheme and mainly a result of the missing small-scale cells in the simulations, which is indicative of a resolution effect: the very small cell heights correspond to small cells that we might not be able to resolve, even with our 400 m grid spacing
Given that the forward simulator applied in this study does not consider wet particles, we find the high bias in Z exists even without considering wet graupel and comes mostly from rain, suggesting particle size distribution (PSD) that contain too many large raindrops compared to the observations
Summary
Clouds play an important role by strongly affecting, e.g., the radiation budget or the precipitation formation. Ryzhkov et al (2011) and Putnam et al (2017) compare simulated polarimetric radar signals with radar observations to evaluate microphysics schemes but focus on one or two convective cases. We present a setup for the systematic characterization of differences between model simulations with different microphysics schemes and polarimetric radar observations for convective weather situations. This includes the application of a radar forward simulator to the model output and of an automated cell-tracking algorithm to the observations and simulations alike. The potential of the generated data set is demonstrated by showing differences in reflectivity between models and observations in convective clouds to identify issues of microphysics schemes to correctly simulate ice and liquid particle size distributions.
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