Quantifying the Wind-Induced Bias of Rainfall Measurements for the Thies CLIMA Optical Disdrometer

IF 4.6 1区 地球科学 Q2 ENVIRONMENTAL SCIENCES
E. Chinchella, A. Cauteruccio, L. G. Lanza
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引用次数: 0

Abstract

The wind-induced bias of rainfall measurements obtained from non-catching instruments is addressed in this work with reference to the Laser Precipitation Monitor (LPM) optical disdrometer manufactured by Thies CLIMA. A numerical simulation approach is adopted to quantify the expected bias, involving three different models with increasing complexity. Computational Fluid-Dynamics simulation of the airflow field around the instrument with an embedded Lagrangian particle-tracking module to obtain raindrop trajectories are performed by solving the Unsteady Reynolds Averaged Navier-Stokes (URANS) equations and a Large Eddy Simulation (LES) model. URANS-uncoupled, LES-uncoupled, and LES-coupled approaches are tested to assess the impact of modeling the airflow turbulent fluctuations in detail. Due to the non-radially symmetric external shape of the instrument, various combinations of the wind speed and direction are considered. Catch ratios for monodisperse rain are obtained as a function of the particle Reynolds number and the wind direction and fitted to obtain site-independent curves to support application of the simulation results. Based on literature expressions to link the drop size distribution of real rainfall events with the rainfall intensity (which instead depend on the local rainfall climatology at the measurement site), sample collection efficiency curves are obtained from the catch ratios of monodisperse rain. The resulting adjustment curves allow rainfall measurements to be corrected using either a real-time or post-processing approach. However, at high wind speed and assuming that the wind blows parallel to the instrument sensing area, the instrument may fail to report precipitation altogether.
量化 Thies CLIMA 光学测距仪降雨量测量的风致偏差
本研究以 Thies CLIMA 公司生产的激光降水监测仪(LPM)光学分度计为参照,探讨了非捕获仪器所获降雨量测量值的风致偏差问题。采用数值模拟方法对预期偏差进行量化,其中涉及三个复杂程度不断增加的不同模型。通过求解非稳态雷诺平均纳维-斯托克斯(URANS)方程和大涡模拟(LES)模型,对仪器周围的气流场进行了计算流体力学模拟,并嵌入了拉格朗日粒子跟踪模块,以获得雨滴轨迹。测试了 URANS-非耦合、LES-非耦合和 LES-耦合方法,以评估气流湍流波动建模细节的影响。由于仪器外部形状非径向对称,因此考虑了风速和风向的各种组合。得出了单分散雨滴的捕获率与颗粒雷诺数和风向的函数关系,并对其进行拟合,以获得与现场无关的曲线,从而为模拟结果的应用提供支持。根据文献中将实际降雨事件的雨滴大小分布与降雨强度(取决于测量地点的当地降雨气候)联系起来的表达式,从单分散雨滴的捕集比中获得了样本收集效率曲线。由此得出的调整曲线可通过实时或后处理方法对降雨测量结果进行修正。不过,在风速较高的情况下,假设风向与仪器感应区域平行,仪器可能会完全无法报告降水量。
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来源期刊
Water Resources Research
Water Resources Research 环境科学-湖沼学
CiteScore
8.80
自引率
13.00%
发文量
599
审稿时长
3.5 months
期刊介绍: Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.
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