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

Atmosphere ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 36
Author(s):  
Qiqi Yang ◽  
Shuliang Zhang ◽  
Qiang Dai ◽  
Hanchen Zhuang
Keyword(s):  
United Kingdom ◽  
Size Distribution ◽  
Gamma Distribution ◽  
Shape Parameter ◽  
Rainfall Intensity ◽  
Post Processing ◽  
The United Kingdom ◽  
Raindrop Size Distribution ◽  
Double Moment ◽  
Raindrop Size

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.

scholarly journals Evolution of the Shape of the Raindrop Size Distribution in Simulated Shallow Cumulus

2016 ◽  
Vol 73 (6) ◽  
pp. 2279-2297 ◽  
Author(s):  
Ann Kristin Naumann ◽  
Axel Seifert
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Shape Parameter ◽  
Cumulus Clouds ◽  
Microphysics Scheme ◽  
Space And Time ◽  
Shallow Cumulus ◽  
Raindrop Size Distribution ◽  
The Mean ◽  
Raindrop Size

Abstract In this paper, the evolution of the raindrop size distribution (RSD) is investigated for two isolated shallow cumulus clouds that are modeled with large-eddy simulations. For a two-moment bulk rain microphysics scheme that assumes the RSD to follow a gamma distribution, it is shown that the evolution of the rainwater content of an individual shallow cumulus cloud—in particular, its subcloud-layer rainwater amount and its surface precipitation rate—is highly sensitive to the choice of the shape parameter of the gamma distribution. To further investigate the shape of the RSD, a Lagrangian drop model is used to represent warm rain microphysics without a priori assumptions on the RSD. It is found that the shape parameter is highly variable in space and time and that existing closure equations, which are established from idealized studies of more heavily precipitating cases, are not appropriate for shallow cumulus. Although a relation of the shape parameter to the mean raindrop diameter is also found for individual shallow cumulus clouds, this relation differs already for the two clouds considered. It is therefore doubtful whether a two-moment scheme with a diagnostic parameterization of the shape parameter (i.e., a local closure in space and time) can be sufficient, especially when being applied across different cloud regimes. A three-moment bulk rain microphysics scheme is able to capture the general development of the relation of the shape parameter to the mean raindrop diameter for the two simulated clouds but misses some relevant features.

scholarly journals On the Shape–Slope Relation of Drop Size Distributions in Convective Rain

2005 ◽  
Vol 44 (7) ◽  
pp. 1146-1151 ◽  
Author(s):  
Axel Seifert
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Drop Size ◽  
Empirical Relation ◽  
Size Distributions ◽  
Shape Parameters ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Drop Size Distributions ◽  
Good Agreement

Abstract The relation between the slope and shape parameters of the raindrop size distribution parameterized by a gamma distribution is examined. The comparison of results of a simple rain shaft model with an empirical relation based on disdrometer measurements at the surface shows very good agreement, but a more detailed discussion reveals some difficulties—for example, deviations from the gamma shape and the overestimation of collisional breakup.

scholarly journals STUDY ON SUMMER RAINDROP SIZE DISTRIBUTION AND RETRIEVED POLARIMETRIC RADAR PARAMETER OVER LEIZHOU PENINSULA

2019 ◽  
Vol XLII-3/W9 ◽  
pp. 245-250
Author(s):  
Z. B. Zhou ◽  
J. J. Lv ◽  
S. J. Niu
Keyword(s):  
Size Distribution ◽  
Gamma Distribution ◽  
Least Squares Method ◽  
Convective Precipitation ◽  
Polarimetric Radar ◽  
Leizhou Peninsula ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Raindrop Size ◽  
Subtropical Monsoon Climate

Abstract. Leizhou peninsula is located in the south of Guangdong Province, near South China Sea, and has a tropical and subtropical monsoon climate. Based on observed drop size distribution (DSD) data from July 2007 to August 2007 with PARSIVEL disdrometers deployed at Zhanjiang and Suixi, the characterists of DSDs are studied. Non-linear least squares method is used to fit Gamma distribution. Convective and stratiform averaged DSDs are in good agreement with Gamma distribution, especially in stratiform case. Convective average DSDs have a wider spectrum and higher peak. Microphysical parameter differences between convective and stratiform are discussed, convective precipitation has a higher mass-weighted mean diameter (Dm) and generalized intercepts (Nw) in both areas. The constrained relations between Gamma distribution parameter (μ, Λ, N0) is derived. The retrieved polarimetric radar parameter (KDP, ZDR, Zh) have a good self-consistency, which can be used to improve the accuracy of KDP calculation. R-KDP-ZDR is superior to the R-KDP, R-ZDR-Zh in quantitative precipitation estimation (QPE), with a correlation coefficient higher than 0.98.

scholarly journals Invariance of the Double-Moment Normalized Raindrop Size Distribution through 3D Spatial Displacement in Stratiform Rain

2017 ◽  
Vol 56 (6) ◽  
pp. 1663-1680 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Vertical Displacement ◽  
Statistical Moments ◽  
Stratiform Rain ◽  
Vertical Range ◽  
Raindrop Size Distribution ◽  
Double Moment ◽  
Raindrop Size ◽  
Polarimetric Weather Radar ◽  
Using Data

AbstractDouble-moment normalization of the drop size distribution (DSD) summarizes the DSD in a compact way, using two of its statistical moments and a “generic” double-moment normalized DSD function. Results are presented of an investigation into the invariance of the double-moment normalized DSD through horizontal and vertical displacement in space, using data from disdrometers, vertically pointing K-band Micro Rain Radars, and an X-band polarimetric weather radar. The invariance of the double-moment normalized DSD is tested over a vertical range of up to 1.8 km and a horizontal range of up to approximately 100 km. The results suggest that for practical use, with well-chosen input moments, the double-moment normalized DSD can be assumed invariant in space in stratiform rain. The choice of moments used to characterize the DSD affects the amount of DSD variability captured by the normalization. It is shown that in stratiform rain, it is possible to capture more than 85% of the variability in DSD moments zero to seven using the technique. Most DSD variability in stratiform rain can thus be explained through the variability of two of its statistical moments. The results suggest similar behavior exists in transition and convective rain, but the limited data samples available do not allow for robust conclusions for these rain types. The results have implications for practical uses of double-moment DSD normalization, including the study of DSD variability and microphysics, DSD-retrieval algorithms, and DSD models used in rainfall retrieval.

scholarly journals Retrieval of the raindrop size distribution from polarimetric radar data using double-moment normalisation

2016 ◽  
Author(s):  
Timothy H. Raupach ◽  
Alexis Berne
Keyword(s):  
Size Distribution ◽  
Radar Data ◽  
Polarimetric Radar ◽  
Climatic Regions ◽  
Retrieval Technique ◽  
Raindrop Size Distribution ◽  
X Band ◽  
Double Moment ◽  
Raindrop Size ◽  
A New Technique

Abstract. A new technique for estimating the raindrop size distribution (DSD) from polarimetric radar data is proposed. Two statistical moments of the DSD are estimated from polarimetric variables, and the DSD is reconstructed. The technique takes advantage of the relative invariance of the double-moment normalised DSD. The method was tested using X-band radar data and networks of disdrometers in three different climatic regions. Radar-derived estimates of the DSD compare reasonably well to observations. In the three tested domains, the proposed method performs similarly to and often better than a state-of-the-art DSD-retrieval technique. The approach is flexible because no specific double-normalised DSD model is prescribed. In addition, a method is proposed to treat noisy radar data to improve DSD-retrieval performance with radar measurements.

scholarly journals Measurements and Modeling of the Full Rain Drop Size Distribution

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 39 ◽  
Author(s):  
Merhala Thurai ◽  
Viswanathan Bringi ◽  
Patrick Gatlin ◽  
Walter Petersen ◽  
Matthew Wingo
Keyword(s):  
Size Distribution ◽  
Small Drop ◽  
Dual Frequency ◽  
Raindrop Size Distribution ◽  
Precipitation Estimation ◽  
Rain Drop ◽  
Double Moment ◽  
Raindrop Size ◽  
Microphysical Processes ◽  
Global Precipitation

The raindrop size distribution (DSD) is fundamental for quantitative precipitation estimation (QPE) and in numerical modeling of microphysical processes. Conventional disdrometers cannot capture the small drop end, in particular the drizzle mode which controls collisional processes as well as evaporation. To overcome this limitation, the DSD measurements were made using (i) a high-resolution (50 microns) meteorological particle spectrometer to capture the small drop end, and (ii) a 2D video disdrometer for larger drops. Measurements were made in two climatically different regions, namely Greeley, Colorado, and Huntsville, Alabama. To model the DSDs, a formulation based on (a) double-moment normalization and (b) the generalized gamma (GG) model to describe the generic shape with two shape parameters was used. A total of 4550 three-minute DSDs were used to assess the size-resolved fidelity of this model by direct comparison with the measurements demonstrating the suitability of the GG distribution. The shape stability of the normalized DSD was demonstrated across different rain types and intensities. Finally, for a tropical storm case, the co-variabilities of the two main DSD parameters (normalized intercept and mass-weighted mean diameter) were compared with those derived from the dual-frequency precipitation radar onboard the global precipitation mission satellite.

scholarly journals On Use of the Standard Deviation of the Mass Distribution as a Parameter in Raindrop Size Distribution Functions

2019 ◽  
Vol 58 (4) ◽  
pp. 787-796 ◽  
Author(s):  
Paul L. Smith ◽  
Roger W. Johnson ◽  
Donna V. Kliche
Keyword(s):  
Standard Deviation ◽  
Maximum Likelihood ◽  
Size Distribution ◽  
Mass Distribution ◽  
Shape Parameter ◽  
The Other ◽  
Maximum Likelihood Estimates ◽  
Moment Methods ◽  
Raindrop Size Distribution ◽  
Raindrop Size

AbstractUse of the standard deviation σm of the drop mass distribution as one of the three parameters of raindrop size distribution (DSD) functions was introduced for application to disdrometer data supporting the Global Precipitation Measurement dual-frequency radar system. The other two parameters are a normalized drop number concentration Nw and the mass-weighted mean diameter Dm. This paper presents an evaluation of that formulation of the DSD functions, in two parts. First is a mathematical analysis showing that the procedure for estimating σm, along with the other DSD parameters, from disdrometer data is in essence another moment method. As such, it is subject to the biases and errors inherent in all moment methods. When the form of the DSD function is specified, it is inferior (like all moment methods) to the maximum likelihood technique for fitting parameters to sampled data. The second part is a series of sampling simulations illustrating the biases and errors involved in applying the formulation to the specific case of gamma DSDs. It leads to underestimates of σm and consequently to overestimates of the gamma shape parameter—with large root-mean-square errors. Comparison with maximum likelihood estimates shows the degree of improvement that could be obtained in the estimates of the shape parameter. The propensity to underestimate σm will be pervasive, and users of this DSD formulation should be cognizant of the biases and errors that can occur.

scholarly journals Raindrop Size Distribution Retrieval Using Joint Dual-Frequency and Dual-Polarization Microwave Links

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Kun Song ◽  
Xichuan Liu ◽  
Taichang Gao ◽  
Binsheng He
Keyword(s):  
Size Distribution ◽  
Rainfall Intensity ◽  
Propagation Path ◽  
Monitoring Systems ◽  
Dual Frequency ◽  
Dual Polarization ◽  
Telecommunication System ◽  
Raindrop Size Distribution ◽  
Raindrop Size ◽  
Theoretical Analyses

Estimation of raindrop size distribution (DSD) is essential in many meteorological and hydrologic fields. This paper proposes a method for retrieving path-averaged DSD parameters using joint dual-frequency and dual-polarization microwave links of the telecommunication system. Detailed analyses of the rain-induced attenuation calculation are performed based on the T-matrix method. A forward model is established for describing the relation between the DSD and the rain-induced attenuation. Then, the method is proposed to retrieve propagation path DSD parameters based on Levenberg–Marquardt optimization algorithm. The numerical simulation for path-averaged DSD retrieval shows that the RMSEs of three gamma DSD parameters are 0.34 mm−1, 0.81, and 3.21×103 m−3·mm−1, respectively, in rainfall intensity above 30 mm/h. Meanwhile, the method can retrieve the rainfall intensity without the influence of variational DSD. Theoretical analyses and numerical simulations confirm that the method for retrieving path-averaged DSD parameters is promising. The method can complement existing DSD monitoring systems such as the disdrometer and provide high-resolution rainfall measurements with widely distributed microwave links without additional cost.

Numerical Simulations for the Warm Rain Properties during RICO with a Newly Developed Triple-moment Warm Cloud Scheme

2020 ◽  
Author(s):  
Wei Deng
Keyword(s):  
Size Distribution ◽  
Water Drop ◽  
Cloud Droplet ◽  
Condensation Process ◽  
Observation Study ◽  
Warm Cloud ◽  
Raindrop Size Distribution ◽  
Double Moment ◽  
Simulation Results ◽  
Raindrop Size

&lt;p&gt;&amp;#160; &amp;#160; Double-moment schemes with a constant shape parameter cannot describe the condensation process and the collision coalescence processes properly. Evolutions of cloud droplet spectra and raindrop spectra simulated with different current bulk microphysical schemes also showed big differences. The newly developed triple-moment scheme (IAP-LACS scheme) considered the variation of the shape parameters of water drop distributions by means of the radar reflectivities of cloud droplets and raindrops, respectively, during the condensation process and collision-coalescence processes. In order to evaluate the performance of our new scheme, we use large-eddy simulation in WRF to research the precipitation formation in Rain in Cumulus over the Ocean (RICO) observation study with new triple-moment warm cloud scheme. This paper will show the simulation results for the microphysical characteristic, specical for the evolution of warm raindrop size distribution in comparison with aircarft measurement. Our simulations show that our new triple-moment scheme can grasp the main characteristic of raindrop size distribution as observation and there must be difference exsiting in simulation results between new scheme and other microphysical bulk schemes.&lt;/p&gt;

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