WRF Rainfall Modeling Post-Processing by Adaptive Parameterization of Raindrop Size Distribution: A Case Study on the United Kingdom

Raindrop size distribution (RSD) is a key parameter in the Weather Research and Forecasting (WRF) model for rainfall estimation, with gamma distribution models commonly used to describe RSD under WRF microphysical parameterizations. The RSD model sets the shape parameter (μ) as a constant of gamma distribution in WRF double-moment bulk microphysics schemes. Here, we propose to improve the gamma RSD model with an adaptive value of μ based on the rainfall intensity and season, designed using a genetic algorithm (GA) and the linear least-squares method. The model can be described as a piecewise post-processing function that is constant when rainfall intensity is <1.5 mm/h and linear otherwise. Our numerical simulation uses the WRF driven by an ERA-interim dataset with three distinct double-moment bulk microphysical parameterizations, namely, the Morrison, WDM6, and Thompson aerosol-aware schemes for the period of 2013–2017 over the United Kingdom at a 5 km resolution. Observations were made using a disdrometer and 241 rain gauges, which were used for calibration and validation. The results show that the adaptive-μ model of the gamma distribution was more accurate than the gamma RSD model with a constant shape parameter, with the root-mean-square error decreasing by averages of 23.62%, 11.33%, and 22.21% for the Morrison, WDM6, and Thompson aerosol-aware schemes, respectively. This model improves the accuracy of WRF rainfall simulation by applying adaptive RSD parameterization and can be integrated into the simulation of WRF double-moment microphysics schemes. The physical mechanism of the RSD model remains to be determined to improve its performance in WRF bulk microphysics schemes.

Raindrop Size Distribution and Rain Characteristics of the 2017 Great Hunan Flood Observed with a Parsivel2 Disdrometer

Disdrometer observations obtained by an OTT Parsivel2 during the 2017 Great Hunan Flood from 1:00 a.m. LST 23 June 2017 to 4:00 a.m. LST 2 July 2017 in Changsha, Hunan Province, southern China, are analyzed to diagnose characteristics of raindrop size distribution (DSD). This event was characterized by a large number of small- to medium-sized raindrops (diameters smaller than 1.5 mm) and the mean median volume diameter (D0) is about 1.04 mm. The median values of rain rate R (1.57 mm h−1), liquid water content W (0.10 g m−3), and radar reflectivity Z (25.7 dBZ) are smaller than that of the 2013 Great Colorado Flood. This event was composed of two intense rainfall periods and a stratiform period, and notable distinctions of rainfall microphysics among the three rainfall episodes are observed. Two intense rainfall periods were characterized by widespread and intense convection rains with a surface reflectivity of 48.8~56.7 dBZ. A maximum diameter of raindrops up to 7.5 mm was observed, as well as high concentrations of small and midsize drops, resulting in large rainfall amounts during the two intense rainfall episodes. The mean radar reflectivity of 22.6 dBZ, total rainfall of 17.85 mm and the maximum raindrop of approximately 4.25 mm were observed during the stratiform rainfall episode. The composite DSD for each rainfall episode peaked at 0.56 mm but higher concentrations of raindrops appeared in the two intense rainfall episodes. The Z-R relationships derived from the disdrometer measurements reflect the unusual characteristics of DSD during the flood. As a result, the standard NEXRAD Z-R relationship (Z = 300R1.4) strongly underestimated hourly rainfall by up to 27.5%. In addition, the empirical relations between rainfall kinetic energy (KE) versus rainfall intensity (R) and mean mass diameter (Dm) are also derived using DSDs to further investigate the impacts of raindrop properties on the rainfall erosivity.

Retrieval of Raindrop Size Distribution Using Dual-Polarized Microwave Signals from LEO Satellites: A Feasibility Study through Simulations

In this paper, a novel approach for raindrop size distribution retrieval using dual-polarized microwave signals from low Earth orbit satellites is proposed. The feasibility of this approach is studied through modelling and simulating the retrieval system which includes multiple ground receivers equipped with signal-to-noise ratio estimators and a low Earth orbit satellite communicating with the receivers using both vertically and horizontally polarized signals. Our analysis suggests that the dual-polarized links offer the opportunity to estimate two independent raindrop size distribution parameters. To achieve that, the vertical and horizontal polarization attenuations need to be measured at low elevation angles where the difference between them is more distinct. Two synthetic rain fields are generated to test the performance of the retrieval. Simulation results suggest that the specific attenuations for both link types can be retrieved through a least-squares algorithm. They also confirm that the specific attenuation ratio of vertically to horizontally polarized signals can be used to retrieve the slope and intercept parameters of raindrop size distribution.

A High-precision and Fast Solution Method of Gamma Raindrop Size Distribution based on 0-Moment and 3-Moment in South China

According to the high accuracy linear shape-slope (μ-Λ) relationship observed by several 2-Dimensional-Video-Distrometers (2DVD) in South China, a high-precision and fast solution method of gamma (Γ) raindrop size distribution (RSD) function based on the zeroth order moment (M0) and the third order moment (M3) of RSD has been proposed. The 0-moment (M0) and 3-moment (M3) of RSD can be easily calculated from rain mass mixing ratio (Qr) and total number concentration (Ntr) simulated by the two-moment (2M) microphysical scheme, respectively. Three typical heavy rainfall processes and all RSD samples observed during 2019 in South China were selected to verify the accuracy of the method. Compared to the current widely used exponential RSD with a fixed shape parameter of zero in 2M microphysical scheme, the Γ RSD function using the linear constrained gamma (C-G) method agreed better with the Γ fit RSD from 2DVD observations. The characteristic precipitation parameters (e.g., rain rate, M2, M6 and M9) obtained by the proposed method are generally consistent with the parameters calculated by Γ fit RSD from 2DVD observations. The proposed method has effectively solved the problem that the shape parameter in the 2M microphysical scheme set to a constant, so that the Γ RSD functions are closer to the observations and have obviously smaller errors. This method has a good potential to be applied to the 2M microphysical schemes to improve the simulation of heavy precipitation in South China, but also paves the way for in-depth applications of radar data in numerical weather prediction models.