scholarly journals Retrievals of ice microphysics using dual-wavelength polarimetric radar observations during stratiform precipitation events

2021 ◽  
Author(s):  
Eleni Tetoni ◽  
Florian Ewald ◽  
Martin Hagen ◽  
Gregor Köcher ◽  
Tobias Zinner ◽  
...  

Abstract. Ice growth processes within clouds affect the type as well as the amount of precipitation. Hence, the importance of an accurate representation of ice microphysics in numerical weather and numerical climate models has been confirmed by several studies. To better constrain ice processes in models, we need to study ice cloud regions before and during monitored precipitation events. For this purpose, two radar instruments facing each other were used to collect complementary measurements. The C-band POLDIRAD weather radar from the German Aerospace Center (DLR), Oberpfaffenhofen and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilians University of Munich (LMU) were used to monitor stratiform precipitation in the vertical cross-section area between both instruments. The logarithmic difference of radar reflectivities at two different wavelengths (54.5 and 8.5 mm), known as dual-wavelength ratio, was exploited to provide information about the size of the detected ice hydrometeors, taking advantage of the different scattering behavior in the Rayleigh and Mie regime. Along with the dual-wavelength ratio, differential radar reflectivity measurements from POLDIRAD provided information about the apparent shape of the detected ice hydrometeors. Scattering simulations using the T-matrix method were performed for oblate and horizontally aligned prolate ice spheroids of varying shape and size using a realistic particle size distribution and a well-established mass-size relationship. The combination of dual-wavelength ratio, radar reflectivity and differential radar reflectivity measurements as well as scattering simulations was used for the development of a novel retrieval for ice cloud microphysics. The development of the retrieval scheme also comprised a method to estimate the hydrometeor attenuation in both radar bands. To demonstrate this approach, a feasibility study was conducted on three stratiform snow events which were monitored over Munich in January 2019. The ice retrieval can obtain ice particle shape, size and mass which are in line with differential radar reflectivity, dual-wavelength ratio and radar reflectivity observations when a suitable mass-size relation is used and when ice hydrometeors are assumed to be represented by oblate ice spheroids. A furthermore finding was the importance of the differential radar reflectivity for the particle size retrieval directly above the MIRA-35 cloud radar. Especially for that observation geometry, the simultaneous slantwise observation from the polarimetric weather radar POLDIRAD could reduce ambiguities in retrieval of the ice particle size by constraining the ice particle shape.

2021 ◽  
Author(s):  
Eleni Tetoni ◽  
Florian Ewald ◽  
Gregor Möller ◽  
Martin Hagen ◽  
Tobias Zinner ◽  
...  

<p>The challenge of the ice microphysical processes representation in numerical weather models is a well-known phenomenon as it can lead to high uncertainty due to the variety of ice microphysics. As ice microphysical properties can strongly affect the initiation of precipitation as well as the type and amount of it, we need to better understand the complexity of ice processes. To accomplish this, better microphysics information through ice retrievals from measurements is needed. The multi-wavelength radar method is nowadays becoming more and more popular in such microphysics retrievals. Taking advantage of different scattering regimes (Rayleigh or Mie), information about the size of atmospheric hydrometeors can be inferred using different radar bands. For this study, dual-wavelength reflectivity ratio measurements were combined with polarimetric measurements to estimate the size of ice hydrometeors. The measurements were obtained by using the synergy of the C-band POLDIRAD weather radar from the German Aerospace Center, located in Oberpfaffenhofen, and the Ka-band MIRA-35 cloud radar from the Ludwig Maximilian University of Munich. Along with the dual-wavelength dataset, the Differential Reflectivity (Z<sub>DR</sub>) from POLDIRAD was used as a polarimetric contribution for the shape estimation of the detected ice particles. The radar observations were compared with T-matrix scattering simulations for the development of a retrieval scheme of ice microphysics. In the course of these studies, different assumptions were considered in the simulations. To capture the size variability, a Gamma particle size distribution (PSD) with different values of median volume diameter (MVD) was used. The soft spheroid approximation was used to approximate the ice particle shapes and to simplify the calculation and variation of their aspect ratios and effective densities. The selection of the most representative mass-size relation was the most crucial for the scattering simulations. In this study, we explored the modified Brown and Francis as well as the aggregates mass-size relation. After comparing the simulations to radar observations, we selected the better fitting one, i.e. aggregates, excluding the Brown and Francis as the simulated particles appeared to be too fluffy. Using the aggregates formulas, Look-Up tables (LUTs) for MVD, aspect ratio, and IWC were developed and used in the ice microphysics retrieval scheme. Here, we present preliminary microphysics retrievals of the median size, shape, and IWC of the detected hydrometeors combining the simulations in LUTs with the radar observations from different precipitation events over the Munich area.</p>


2019 ◽  
Vol 12 (2) ◽  
pp. 1409-1427 ◽  
Author(s):  
Gwo-Jong Huang ◽  
Viswanathan N. Bringi ◽  
Andrew J. Newman ◽  
Gyuwon Lee ◽  
Dmitri Moisseev ◽  
...  

Abstract. quantitative precipitation estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the prefactor of the power law due to changes in particle size distribution (PSD), density, and fall velocity, whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter), thus reducing the variability due to the prefactor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is falls in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold-season Precipitation Experiment). Since the particle mass can be estimated using 2-D video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare it directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z–SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.


2018 ◽  
Vol 18 (23) ◽  
pp. 17371-17386 ◽  
Author(s):  
Veronika Wolf ◽  
Thomas Kuhn ◽  
Mathias Milz ◽  
Peter Voelger ◽  
Martina Krämer ◽  
...  

Abstract. Ice particle and cloud properties such as particle size, particle shape and number concentration influence the net radiation effect of cirrus clouds. Measurements of these features are of great interest for the improvement of weather and climate models, especially for the Arctic region. In this study, balloon-borne in situ measurements of Arctic cirrus clouds have been analysed for the first time with respect to their origin. Eight cirrus cloud measurements have been carried out in Kiruna (68∘ N), Sweden, using the Balloon-borne Ice Cloud particle Imager (B-ICI). Ice particle diameters between 10 and 1200 µm have been found and the shape could be recognized from 20 µm upwards. Great variability in particle size and shape is observed. This cannot simply be explained by local environmental conditions. However, if sorted by cirrus origin, wind and weather conditions, the observed differences can be assessed. Number concentrations between 3 and 400 L−1 have been measured, but the number concentration has reached values above 100 L−1 only for two cases. These two cirrus clouds are of in situ origin and have been associated with waves. For all other measurements, the maximum ice particle concentration is below 50 L−1 and for one in situ origin cirrus case only 3 L−1. In the case of in situ origin clouds, the particles are all smaller than 350 µm diameter. The PSDs for liquid origin clouds are much broader with particle sizes between 10 and 1200 µm. Furthermore, it is striking that in the case of in situ origin clouds almost all particles are compact (61 %) or irregular (25 %) when examining the particle shape. In liquid origin clouds, on the other hand, most particles are irregular (48 %), rosettes (25 %) or columnar (14 %). There are hardly any plates in cirrus regardless of their origin. It is also noticeable that in the case of liquid origin clouds the rosettes and columnar particles are almost all hollow.


2018 ◽  
Author(s):  
Gwo-Jong Huang ◽  
Viswanathan N. Bringi ◽  
Andrew J. Newman ◽  
GyuWon Lee ◽  
Dmitri Moisseev ◽  
...  

Abstract. Quantitative Precipitation Estimation (QPE) of snowfall has generally been expressed in power-law form between equivalent radar reflectivity factor (Ze) and liquid equivalent snow rate (SR). It is known that there is large variability in the pre-factor of the power law due to changes in particle size distribution (PSD), density, and fall velocity whereas the variability of the exponent is considerably smaller. The dual-wavelength radar reflectivity ratio (DWR) technique can improve SR accuracy by estimating one of the PSD parameters (characteristic diameter) thus reducing the variability due to the pre-factor. The two frequencies commonly used in dual-wavelength techniques are Ku- and Ka-bands. The basic idea of DWR is that the snow particle size-to-wavelength ratio is such as to fall in the Rayleigh region at Ku-band but in the Mie region at Ka-band. We propose a method for snow rate estimation by using NASA D3R radar DWR and Ka-band reflectivity observations collected during a long-duration synoptic snow event on 30–31 January 2012 during the GCPEx (GPM Cold Season Precipitation Experiment). Since the particle mass can be estimated using 2D-video disdrometer (2DVD) fall speed data and hydrodynamic theory, we simulate the DWR and compare directly with D3R radar measurements. We also use the 2DVD-based mass to compute the 2DVD-based SR. Using three different mass estimation methods, we arrive at three respective sets of Z-SR and SR(Zh, DWR) relationships. We then use these relationships with D3R measurements to compute radar-based SR. Finally, we validate our method by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a well-shielded Pluvio gauge for the entire synoptic event.


2018 ◽  
Author(s):  
Mary Borderies ◽  
Olivier Caumont ◽  
Julien Delanoë ◽  
Véronique Ducrocq ◽  
Nadia Fourrié ◽  
...  

Abstract. This article investigates the potential of W-band radar reflectivity to improve the quality of analyses and forecasts of heavy precipitation events in the Mediterranean area. The 1D + 3DVar assimilation method, operationally employed to assimilate ground-based precipitation radar data in the Météo-France kilometre-scale NWP model AROME, has been adapted to assimilate the W-band reflectivity measured by the airborne cloud radar RASTA during a two-month period over the Mediterranean area. After applying a bias correction, vertical profiles of relative humidity are first derived via a 1D Bayesian retrieval, and then used as relative humidity pseudo-observations in the 3DVar assimilation system of AROME. The efficiency of the 1D Bayesian method in retrieving humidity fields is assessed using independent in-flight humidity measurements. To complement this study, the benefit brought by consistent thermodynamic and dynamic cloud conditions has been investigated by assimilating separately and jointly in the 3 h 3DVar assimilation system of AROME the W-band reflectivity and horizontal wind measurements collected by RASTA. The data assimilation experiments are conducted for a single heavy precipitation event, and then for 32 cases. Results indicate that the W-band reflectivity has a larger impact on the humidity, temperature and pressure fields in the analyses, compared to the assimilation of RASTA wind data alone. Besides, the analyses get closer to independent humidity observations if the W-band reflectivity is assimilated alone or jointly with RASTA wind data. Nonetheless, the impact of the W-band reflectivity decreases more rapidly as the forecast range increases, compared to the assimilation of RASTA wind data alone. Generally, the assimilation of the W-band reflectivity jointly with wind data results in the best improvement of the rainfall precipitation forecasts. Consequently, results of this study indicate that consistent thermodynamic and dynamic cloud conditions in the analysis leads to an improvement of both model initial conditions and forecasts. Even though to a less extent, the assimilation of the W-band reflectivity alone also results in a slight improvement of the rainfall precipitation forecasts.


2021 ◽  
Author(s):  
Gregor Köcher ◽  
Florian Ewald ◽  
Martin Hagen ◽  
Christoph Knote ◽  
Eleni Tetoni ◽  
...  

<p>The representation of microphysical processes in numerical weather prediction models remains a main source of uncertainty until today. To evaluate the influence of cloud microphysics parameterizations on numerical weather prediction, a convection permitting regional weather model setup has been established using 5 different microphysics schemes of varying complexity (double-moment, spectral bin, particle property prediction (P3)). A polarimetric radar forward operator (CR-SIM) has been applied to simulate radar signals consistent with the simulated particles. The performance of the microphysics schemes is analyzed through a statistical comparison of the simulated radar signals to radar measurements on a dataset of 30 convection days.</p> <p>The observational data basis is provided by two polarimetric research radar systems in the area of Munich, Germany, at C- and Ka-band frequencies and a complementary third polarimetric C-band radar operated by the German Weather Service. By measuring at two different frequencies, the<br />dual-wavelength ratio is derived that facilitates the investigation of the particle size evolution. Polarimetric radars provide in-cloud information about hydrometeor type and asphericity by measuring, e.g., the differential reflectivity ZDR.</p> <p>Within the DFG Priority Programme 2115 PROM, we compare the simulated polarimetric and dual-wavelength radar signals with radar observations of convective clouds. Deviations are found between the schemes and observations in ice and liquid phase, related to the treatment of particle size distributions. 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. Comparison of polarimetric radar signatures reveal issues of all schemes except the spectral bin scheme to correctly represent rain particle size distributions. The polarimetric information is further exploited by applying a hydrometeor classification algorithm to obtain dominant hydrometeor classes. By comparing the simulated and observed distribution of hydrometeors, as well as the frequency, intensity and area of high impact weather situations (e.g., hail or heavy convective precipitation), the influence of cloud microphysics on the ability to correctly predict high impact weather situations is examined.</p>


2021 ◽  
Vol 15 (1) ◽  
pp. 75-82
Author(s):  
Mingzi Xu ◽  
Changdong Sheng

The present work aims to develop a simple model for describing the particle size distribution (PSD) of residual fly ash from pulverized biomass combustion. The residual ash formation was modelled considering the mechanism of fragmentation and coalescence. The influences of particle shape and stochastic fragmentation on model description of the PSD of the fly ash were investigated. The results showed that biomass particle shape has a great influence on the model prediction, and a larger fragmentation number is required for cylindrical particles than that for spherical particles to get the same PSD of fly ash, and the fragment number of the particles increases with the shape factor increasing. For pulverized biomass with a wide size distribution, the model predicted ash PSD considering the stochastic fragmentation is very similar to that assuming uniform fragmentation. It implies that the simple model assuming uniform fragmentation is applicable for predicting fly ash size distribution in practical processes where biomass particles have a wide range of sizes. For the fuel with a narrower initial PSD, the stochastic fragmentation model generally predicts a coarser PSD of the residual ash than assuming uniform fragmentation. It means the stochastic fragmentation is of great influence to be considered for accurate description of ash formation from the fuel with a narrow PSD.


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