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 to observe them directly. On the path to close 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 5 different microphysics schemes (double-moment, spectral bin (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 dataset of 30 convection days. In general, simulations show too few weak and small-scale convective cells. Contoured frequency by altitude distributions of radar signatures reveal deviations between the schemes and observations in ice and liquid phase. Apart from the P3 scheme, simulated reflectivities in the ice phase are too high. Dual-wavelength signatures demonstrate issues of most schemes to correctly represent ice particle size distributions, producing overly large graupel particles. Comparison of polarimetric radar signatures reveal 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
90 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
TINT does not deal with splits or mergers, but it was designed for tracking of convective cells over large datasets and is straightforward to apply to our data (Fig. 2)
Summary
In numerical weather models clouds play an important role by strongly affecting, e.g., the radiation budget or the precipitation formation. 2. Evaluate multiple state-of-the-art cloud microphysics schemes for current generation numerical weather prediction models in a common model framework against observations with a sound statistical basis. 90 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. 95 The potential of the generated data set is demonstrated by showing differences in reflectivity between model and observations in convective clouds to identify issues of microphysics schemes to correctly simulate ice and liquid particle size distributions. 3 the microphysics schemes are evaluated by comparing statistics of cloud geometry and frequency (3.1) as well as analyzing frequency distributions of reflectivity (3.2), polarimetric variables (3.3), and dual-wavelength ratio (3.4) in simulations and observations.
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