Effect of Reconstruction Parameters on Tomographic Imaging of Rainfall Fields from Multi-Parameter Microwave Observables

S. K. Yim, T. Seliga, D. Giuli, A. Toccafondi, G. B. Gentili, Angelo Freni
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引用次数: 1

Abstract

Monitoring the temporal and spatial distribution of rainfall events is essential to the prevention and mitigation of natural hazards such as flash floods and landslides. Other applications include developing a database from which climatological behavior of storm information might be determined for improved understanding of storm dynamics of cloud physics, effects on radio Propagation links and rainfield statistics for rainfall prediction. Presently, spatial interpolation of point raingage measurements or weather radar rainfall estimates are employed for these purposes. However, these methods have limitations (such as low spatial and temporal resolution attained when using raingage networks or the loss of spatial coverage when using radar in complex terrain) which hamper their unconditional reliability. Alternatively, increasing reliability via denser raingage telemetry networks can lead to exorbitant costs associated with system complexity, maintenance and operation. Tomographic reconstruction algorithms have been prevalently used in the medical imaging field wherein a series of one-dimensional measurements or projections are transformed into a two-dimensional cross sectional image. The potential high resolution attained using these methods, coupled with their non-invasive nature, have made tomographic imaging attractive to widely diverse applications such as geophysical imaging, nondestructive testing in industrial manufacturing, and most recently, imaging ground-level rain intensities [ 11. Repeated over time, tomographic im-g of rainfall can monitor both spatial and temporal characteristics as rain events develop. For certain applications, this method possesses a significant advantage over current methods which use either raingages or weather radar, as it allows the observation of rain events in real-time (or near real-hf) with relatively high resolution over a reasonably large area (e.g. 500 km ). The original work by Giuli et al. [l] proved the feasibility of implementing tomographic imaging of rainfall fields using one-way specific attenuation measurements over a small fixed network. However, the use of specific attenuation measurements alone for tomographic reconstruction is not without limitation. Besides affirming the original techniques developed by Giuli et al. this paper explores the following issues: 1) transmitter and receiver siting as it affects accumulated and lnstantaneo us image formation; 2) inmduction of multi-parameter propagation observables (such as specific differential phase shift and specific differential attenuation) and their role in practical system implementation; 3) basis function selection in deference to physical storm Characteristics; and 4) the ability of the tomographic imaging process to adapt to different types and intensities of storms.
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重建参数对多参数微波观测降水场层析成像的影响
监测降雨事件的时空分布对于预防和减轻山洪和滑坡等自然灾害至关重要。其他应用包括开发一个数据库,从中可以确定风暴信息的气候行为,以提高对云物理的风暴动力学的理解,对无线电传播链路的影响以及用于降雨预测的雨场统计。目前,点雨量测量的空间插值或天气雷达雨量估计是用于这些目的。然而,这些方法有局限性(例如,当使用降雨网时获得的空间和时间分辨率较低,或者在复杂地形中使用雷达时失去空间覆盖),这妨碍了它们的无条件可靠性。另外,通过密集的降雨遥测网络来提高可靠性可能会导致与系统复杂性、维护和操作相关的过高成本。层析重建算法已广泛应用于医学成像领域,其中将一系列一维测量或投影转换为二维横截面图像。利用这些方法获得的潜在高分辨率,加上它们的非侵入性,使得层析成像具有广泛的应用吸引力,例如地球物理成像,工业制造中的无损检测,以及最近的地面降雨强度成像[11]。随着时间的推移,降雨的层析成像可以监测降雨事件发展的时空特征。对于某些应用,这种方法比目前使用降雨或气象雷达的方法具有显著的优势,因为它允许在相当大的区域(例如500公里)内以相对高的分辨率实时(或接近real-hf)观测降雨事件。Giuli等人[1]的原始工作证明了在小型固定网络上使用单向特定衰减测量实现降雨场层状成像的可行性。然而,仅使用特定的衰减测量进行层析重建并非没有限制。除了肯定Giuli等人开发的原始技术外,本文还探讨了以下问题:1)发射器和接收器的位置,因为它影响累积和瞬时图像的形成;2)引入多参数传播观测值(如比差相移和比差衰减)及其在实际系统实现中的作用;3)根据风暴物理特征选择基函数;4)层析成像过程对不同类型和强度风暴的适应能力。
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