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Intercomparison of attenuation correction algorithms for single-polarized X-band radars

机译:单极化X波段雷达的衰减校正算法的相互作用

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摘要

Attenuation due to liquid water is one of the largest uncertainties in radar observations. The effects of attenuation are generally inversely proportional to the wavelength, i.e. observations from X-band radars are more affected by attenuation than those from C- or S-band systems. On the other hand, X-band radars can measure precipitation fields in higher temporal and spatial resolution and are more mobile and easier to install due to smaller antennas. A first algorithm for attenuation correction in single-polarized systems was proposed by Hitschfeld and Bordan (1954) (HB), but it gets unstable in case of small errors (e.g. in the radar calibration) and strong attenuation. Therefore, methods have been developed that restrict attenuation correction to keep the algorithm stable, using e.g. surface echoes (for space-borne radars) and mountain returns (for ground radars) as a final value (FV), or adjustment of the radar constant (C) or the coefficient a. In the absence of mountain returns, measurements from C- or S-band radars can be used to constrain the correction. All these methods are based on the statistical relation between reflectivity and specific attenuation. Another way to correct for attenuation in X-band radar observations is to use additional information from less attenuated radar systems, e.g. the ratio between X-band and C- or S-band radar measurements. Lengfeld et al. (2016) proposed such a method based isotonic regression of the ratio between X- and C-band radar observations along the radar beam. This study presents a comparison of the original HB algorithm and three algorithms based on the statistical relation between reflectivity and specific attenuation as well as two methods implementing additional information of C-band radar measurements. Their performance in two precipitation events (one mainly convective and the other one stratiform) shows that a restriction of the HB is necessary to avoid instabilities. A comparison with vertically pointing micro rain radars (MRR) reveals good performance of two of the methods based in the statistical k-Z-relation: FV and a. The C algorithm seems to be more sensitive to differences in calibration of the two systems and requires additional information from C- or S-band radars. Furthermore, a study of five months of radar observations examines the long-term performance of each algorithm. From this study conclusions can be drawn that using additional information from less attenuated radar systems lead to best results. The two algorithms that use this additional information eliminate the bias caused by attenuation and preserve the agreement with MRR observations.
机译:液态水引起的衰减是雷达观测中最大的不确定性之一。衰减的影响通常与波长成反比,即X波段雷达的观察比衰减比来自C或S频带系统的观察更大。另一方面,X波段雷达可以测量较高的时间和空间分辨率的降水场,并且由于较小的天线,由于较小的天线而更容易安装。 Hitschfeld和Bordan(1954)(HB)提出了一种用于单极化系统中的衰减校正算法,但在小错误(例如,在雷达校准)和强度衰减时,它变得不稳定。因此,已经开发了用于限制衰减校正以使算法使用例如稳定的方法。表面回波(用于空间传送雷达)和山地返回(用于地雷达)作为最终值(FV),或调整雷达常数(c)或系数a。在没有山地返回的情况下,可以使用来自C或S波段雷达的测量来限制校正。所有这些方法都基于反射率与特定衰减之间的统计关系。校正在X波段雷达观测中恢复的另一种方法是使用来自较少减毒的雷达系统的附加信息,例如, X波段和C或S波段雷达测量的比率。 Lengfeld等人。 (2016)提出了沿雷达梁的X-和C波段雷达观测之间的基于比例的基于等渗的等渗。该研究介绍了原始HB算法和三种算法的比较,基于反射率和特定衰减之间的统计关系以及实现C波段雷达测量的附加信息的两种方法。它们在两个降水事件中的性能(一个主要是对流和另一个层状)表明,Hb的限制是避免稳定性的必要条件。与垂直指向微雨雷达(MRR)的比较揭示了基于统计K-Z关系的两种方法的良好性能:Fv和a。 C算法对两个系统的校准差异更敏感,并且需要来自C或S波段雷达的附加信息。此外,对五个月的雷达观察结果研究了每种算法的长期性能。从本研究结论可以绘制的结论,使用较少减毒的雷达系统的其他信息导致最佳效果。使用此附加信息的两种算法消除了衰减引起的偏差,并与MRR观察保持协议。

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