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Ricardo Reinoso-Rondinel, Christine Unal, and Herman Russchenberg

ABSTRACT

One of the most beneficial polarimetric variables may be the specific differential phase K DP because of its independence from power attenuation and radar miscalibration. However, conventional K DP estimation requires a substantial amount of range smoothing as a result of the noisy characteristic of the measured differential phase ΨDP. In addition, the backscatter differential phase δ hv component of ΨDP, significant at C- and X-band frequency, may lead to inaccurate K DP estimates. In this work, an adaptive approach is proposed to obtain accurate K DP estimates in rain from noisy ΨDP, whose δ hv is of significance, at range resolution scales. This approach uses existing relations between polarimetric variables in rain to filter δ hv from ΨDP while maintaining its spatial variability. In addition, the standard deviation of the proposed K DP estimator is mathematically formulated for quality control. The adaptive approach is assessed using four storm events, associated with light and heavy rain, observed by a polarimetric X-band weather radar in the Netherlands. It is shown that this approach is able to retain the spatial variability of the storms at scales of the range resolution. Moreover, the performance of the proposed approach is compared with two different methods. The results of this comparison show that the proposed approach outperforms the other two methods in terms of the correlation between K DP and reflectivity, and K DP standard deviation reduction.

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Ricardo Reinoso-Rondinel, Christine Unal, and Herman Russchenberg

Abstract

In radar polarimetry, the differential phase ΨDP consists of the propagation differential phase ΦDP and the backscatter differential phase δhv. While ΦDP is commonly used for attenuation correction (i.e., estimation of the specific attenuation A and specific differential phase KDP), recent studies have demonstrated that δhv can provide information concerning the dominant size of raindrops. However, the estimation of ΦDP and δhv is not straightforward given their coupled nature and the noisy behavior of ΨDP, especially over short paths. In this work, the impacts of estimating ΦDP on the estimation of A over short paths, using the extended version of the ZPHI method, are examined. Special attention is given to the optimization of the parameter α that connects KDP and A. In addition, an improved technique is proposed to compute δhv from ΨDP and ΦDP in rain. For these purposes, diverse storm events observed by a polarimetric X-band radar in the Netherlands are used. Statistical analysis based on the minimum errors associated with the optimization of α and the consistency between KDP and A showed that more accurate and stable α and A are obtained if ΦDP is estimated at range resolution, which is not possible by conventional range filtering techniques. Accurate δhv estimates were able to depict the spatial variability of dominant raindrop size in the observed storms. By following the presented study, the ZPHI method and its variations can be employed without the need for considering long paths, leading to localized and accurate estimation of A and δhv.

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Christos Gatidis, Marc Schleiss, Christine Unal, and Herman Russchenberg

Abstract

The adequacy of the gamma model to describe the variability of raindrop size distributions (DSD) is studied using observations from an optical disdrometer. Model adequacy is checked using a combination of Kolmogorov–Smirnov goodness-of-fit test and Kullback–Leibler divergence and the sensitivity of the results to the sampling resolution is investigated. A new adaptive DSD sampling technique capable of determining the highest possible temporal sampling resolution at which the gamma model provides an adequate representation of sampled DSDs is proposed. The results show that most DSDs at 30 s are not strictly distributed according to a gamma model, while at the same time they are not far away from it either. According to the adaptive DSD sampling algorithm, the gamma model proves to be an adequate choice for the majority (85.81%) of the DSD spectra at resolutions up to 300 s. At the same time, it also reveals a considerable number of DSD spectra (5.55%) that do not follow a gamma distribution at any resolution (up to 1800 s). These are attributed to transitional periods during which the DSD is not stationary and exhibits a bimodal shape that cannot be modeled by a gamma distribution. The proposed resampling procedure is capable of automatically identifying and flagging these periods, providing new valuable quality control mechanisms for DSD retrievals in disdrometers and weather radars.

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Dmitri N. Moisseev, Christine M. H. Unal, Herman W. J. Russchenberg, and Leo P. Ligthart

Abstract

Polarization properties of radar waves that are scattered from atmospheric objects are of great interest in meteorological studies. However, polarimetric radar measurements are often not sufficiently accurate for retrieving physical properties of targets. To compensate for errors, radar polarimetric calibration is applied. Typical calibrations are performed based on measurements of point targets with known scattering matrices located in the boresight of the antenna. Such calibration takes into account the polarization state of the antenna pattern only at one point. Since radar measurements of atmospheric phenomena involve distributed targets that fill the full antenna beam, point target radar calibrations are inadequate for meteorological studies.

This paper explains in detail the effects of the complete antenna patterns on weather echoes. It is shown that the conventional polarimetric calibration can be significantly improved by incorporating light-rain (<20 dBZ) zenith-pointing measurements into the calibration procedure. As a result, the sensitivity of cross-polar measurements can be improved by 7 dB on average. Also it is shown that the bias in co-cross-polar correlation coefficient can be reduced.

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Lukas Pfitzenmaier, Yann Dufournet, Christine M. H. Unal, and Herman W. J. Russchenberg

Abstract

The interaction of ice crystals with supercooled liquid droplets in mixed-phase clouds leads to an enhanced growth of ice particles. However, such processes are still not clearly understood although they are important processes for precipitation formation in midlatitudes. To better understand how ice particles grow within such clouds, changes in the microphysical parameters of a particle population falling through the cloud have to be analyzed. The Transportable Atmospheric Radar (TARA) can retrieve the full 3D Doppler velocity vector based on a unique three-beam configuration. Using the derived wind information, a new fall streak retrieval technique is proposed so that microphysical changes along those streaks can be studied. The method is based on Doppler measurements only. The shown examples measured during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) campaign demonstrate that the retrieval is able to capture the fall streaks within different cloud systems. These fall streaks can be used to study changes in a single particle population from its generation (at cloud top) until its disintegration. In this study fall streaks are analyzed using radar moments or Doppler spectra. Synergetic measurements with other instruments during ACCEPT allow the detection of liquid layers within the clouds. The estimated microphysical information is used here to get a better understanding of the influence of supercooled liquid layers on ice crystal growth. This technique offers a new perspective for cloud microphysical studies.

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