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Preliminary investigation of the relationship between differential phase shift and path-integrated attenuation at the X band frequency in an Alpine environment

机译:初步调查高山环境中X频率X频段差分相移和路径综合衰减关系的初步研究

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The RadAlp experiment aims at developing advanced methods for rainfall and snowfall estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed since 2016 in the Grenoble region of France. It is composed of an X-band radar operated by Météo-France on top of the Moucherotte mountain (1901m above sea level; hereinafter MOUC radar). In the Grenoble valley (220m above sea level; hereinafter a.s.l.), we operate a research X-band radar called XPORT and in situ sensors (weather station, rain gauge and disdrometer). In this paper we present a methodology for studying the relationship between the differential phase shift due to propagation in precipitation (Φdp) and path-integrated attenuation (PIA) at X band. This relationship is critical for quantitative precipitation estimation (QPE) based on polarimetry due to severe attenuation effects in rain at the considered frequency. Furthermore, this relationship is still poorly documented in the melting layer (ML) due to the complexity of the hydrometeors' distributions in terms of size, shape and density. The available observation system offers promising features to improve this understanding and to subsequently better process the radar observations in the ML. We use the mountain reference technique (MRT) for direct PIA estimations associated with the decrease in returns from mountain targets during precipitation events. The polarimetric PIA estimations are based on the regularization of the profiles of the total differential phase shift (Ψdp) from which the profiles of the specific differential phase shift on propagation (Kdp) are derived. This is followed by the application of relationships between the specific attenuation (k) and the specific differential phase shift. Such k–Kdp relationships are estimated for rain by using drop size distribution (DSD) measurements available at ground level. Two sets of precipitation events are considered in this preliminary study, namely (i)?nine convective cases with high rain rates which allow us to study the ?dp–PIA relationship in rain, and (ii)?a stratiform case with moderate rain rates, for which the melting layer (ML) rose up from about 1000 up to 2500ma.s.l., where we were able to perform a horizontal scanning of the ML with the MOUC radar and a detailed analysis of the ?dp–PIA relationship in the various layers of the ML. A common methodology was developed for the two configurations with some specific parameterizations. The various sources of error affecting the two PIA estimators are discussed, namely the stability of the dry weather mountain reference targets, radome attenuation, noise of the total differential phase shift profiles, contamination due to the differential phase shift on backscatter and relevance of the k–Kdp relationship derived from DSD measurements, etc. In the end, the rain case study indicates that the relationship between MRT-derived PIAs and polarimetry-derived PIAs presents an overall coherence but quite a considerable dispersion (explained variance of 0.77). Interestingly, the nonlinear k–Kdp relationship derived from independent DSD measurements yields almost unbiased PIA estimates. For the stratiform case, clear signatures of the MRT-derived PIAs, the corresponding ?dp value and their ratio are evidenced within the ML. In particular, the averaged PIA∕?dp ratio, a proxy for the slope of a linear k–Kdp relationship in the ML, peaks at the level of the copolar correlation coefficient (ρhv) peak, just below the reflectivity peak, with a value of about 0.42dB per degree. Its value in rain below the ML is 0.33dB per degree, which is in rather good agreement with the slope of the linear k–Kdp relationship derived from DSD measurements at ground level. The PIA∕?dp ratio remains quite high in the upper part of the ML, between 0.32 and 0.38dB per degree, before tending towards 0 above the ML.
机译:利用高山地区的天气雷达遥感技术为改善水资源评估和水文风险减缓,旨在利用高山地区的天气雷达遥感技术开发降雨和降雪估计的先进方法。自2016年以来,在法国格勒诺布地区自2016年以来一直部署了独特的观察系统。它由由Météo-法国运营的X波段雷达组成,在Moucherotte Mountain(海拔1901米)上由Météo-France(在海平面上方1901米;以下制造Mouc雷达)。在格勒诺布尔山谷(海拔220米;在下文中,在下文中,我们操作了一个名为XPort和原位传感器(气象站,雨量计和Discrometer)的研究X波段雷达。在本文中,我们提出了一种用于研究由于在X波段中的降水中传播和路径集成衰减(PIA)在X频带中传播的差分相位偏移之间的关系。由于考虑频率的雨中严重的衰减效应,这种关系对于基于偏振基的定量降水估计(QPE)至关重要。此外,由于水质仪在尺寸,形状和密度方面的复杂性,这种关系仍然在熔化层(m1)中记录不足。可用的观察系统提供了有希望的功能来提高这种理解,并随后更好地处理ML中的雷达观察。我们使用山地参考技术(MRT)进行降低与降水事件中山地目标的回报的直接PIA估计。 Polariemetric Pia估计基于总差分相移(ψdp)的曲线的正则化,从中导出了传播上的特定差分相移的轮廓(KDP)的轮廓。接下来,在特定衰减(k)和特定差分相移之间的关系。通过使用地面可用的滴尺寸分布(DSD)测量来估计这种K-KDP关系。在这个初步研究中考虑了两套降水事件,即(i)?九个对流病例,具有高雨率,允许我们研究雨中的dp-pia关系,(ii)?雨率中等雨率的层状案例,熔化层(ml)上升到大约1000至2500mA.SL,在那里我们能够用MOUC雷达进行ML的水平扫描,并在各种各样的Δdp-pia关系进行详细分析毫升层。对于具有一些特定参数化的两种配置开发了一种常见的方法。讨论了影响两个PIA估计器的各种误差源,即干燥天气山参考目标的稳定性,径向衰减,总差分相移曲线的噪声,由于差分相位转移而导致的反向散射和k的相关性。 -KDP关系来自DSD测量等。最后,雨壳研究表明,MRT导出的掌梁与偏振率衍生的锁定之间的关系呈现整体相干性,但相当大的分散(解释的差异为0.77)。有趣的是,来自独立DSD测量的非线性K-KDP关系产生几乎没有偏见的PIA估计。对于层状壳体,ML在ML内证明了ML衍生粘合的透明签名,相应的ΔDP值及其比例。特别地,平均PIA /ΔDP比率,用于在M1中的线性K-KDP关系的斜率的代理,峰值在型号的相关系数(ρhv)峰值水平下,在反射率峰下方,具有值每度约0.42dB。其在ML低于ML的雨中为0.33dB,与从地面水平的DSD测量结果衍生的线性K-KDP关系的斜率相当愉快。在mL的上部,PIA /βDP比率在0.32和0.38dB之间保持相当高,在均在ML上方0之前。

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