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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. Key Points: The wind‐induced bias for the Thies CLIMA LPM is investigated using time dependent and time independent numerical simulationsCollection efficiency is derived from the catch ratios of monodisperse rain by linking the drop size distribution with rainfall intensityAdjustment curves for field measurements are provided as a function of wind speed, wind direction and rainfall intensity for practical use [ABSTRACT FROM AUTHOR]

Precipitation is among the most important meteorological variables for, e.g., meteorological, hydrological, water management and climate studies. In recent years, non-catching precipitation gauges are increasingly adopted in meteorological networks. Despite such growing diffusion, calibration procedures and associated uncertainty budget are not yet standardized or prescribed in best practice documents and standards. This paper reports a metrological study aimed at proposing calibration procedures and completing the uncertainty budgets, to make non-catching precipitation gauge measurements traceable to primary standards. The study is based on the preliminary characterization of different rain drop generators, specifically developed for the investigation. Characterization of different models of non-catching rain gauges is also included.

The airflow velocity pattern generated by a widely used non-catching precipitation gauge (the Thies laser precipitation monitor or LPM) when immersed in a wind field is investigated using computational fluid dynamics (CFD). The simulation numerically solves the unsteady Reynolds-averaged Navier-Stokes (URANS) equations and the setup is validated against dedicated wind tunnel measurements. The adopted k-ω shear stress transport (SST) turbulence model closely reproduces the flow pattern generated by the complex, non-axisymmetric outer geometry of the instrument. The airflow pattern near the measuring area varies with the wind direction, the most intense recirculating flow and turbulence being observed when the wind blows from the back of the instrument. Quantitative parameters are used to discuss the magnitude of the airflow perturbations with respect to the ideal configuration where the instrument is transparent to the wind. The generated airflow pattern is expected to induce some bias in operational measurements, especially in strong wind conditions. The proposed numerical simulation framework provides a basis to develop correction curves for the wind-induced bias of non-catching gauges, as a function of the undisturbed wind speed and direction.