Bluff-body aerodynamics and transfer functions for non-catching precipitation measurement instruments.

Starting from the old and trivial technique of using a graduated cylinder to collect and manually measure precipitation, numerous advances were made for in-situ precipitation gauges. After decades of scarce innovation, a new family of in-situ precipitation gauges was developed. They are called Non-Catching Gauges (NCG) since they can measure precipitation and its microphysical and dynamic characteristics without the need to collect hydrometeors. The attention that NCGs are gathering today is quite notable, even if they represent only a small fraction of the total precipitation gauges deployed. Their use in the field is bound to continuously grow in time, due to several advantages, discussed in this work, that such instruments present over more traditional ones. However, their major disadvantage is their increased complexity, the effects of which are highlighted by the literature through evidence of calibration and correction issues. Various field intercomparison experiments showed the evidence of significant biases in NCGs measurements. The goal of this work is to investigate two main sources of bias, producing the largest impact on precipitation measurements. The first source of bias evaluated in this work is due to instrument calibration. Several attempts at developing a calibration procedure are presented both in the scientific literature and from the manufacturers. Nevertheless, those methods are hardly traceable to international standards and, in most cases, lack a suitable reference measure to compare against the instrumental output. In this work, a fully traceable calibration procedure is proposed, in analogy with the one already existing for catching type gauges. This requires drops of know diameter and fall velocity to be released over the instrument sensing area. For this reason, the Calibrated Rainfall Generator (CRG) is developed, able to release single drops on demand and measure them independently just before they reach the instrument sensing area. Detachment of drops is obtained by using an electrostatic system, while the measure of their diameter and fall velocity is performed by means of a photogrammetric approach. The Thies Laser Precipitation Monitor (LPM) was tested using the CRG considering two different output telegrams. The first one provides the raw measure of each drop sensed by the instrument while the second one provides the Particle Size and fall Velocity Distribution (PSVD) matrix. Both telegrams show a tendency to underestimate the drop diameter that increases with decreasing the drop size, while errors in the fall velocity measurements have a less definite trend. Furthermore, tests also show a large standard deviation of the measurements, significantly higher than the one of the reference measurements. The underestimation of drop size and fall velocity is also reflected into the RI measurements provided by the instrument, with a resulting underestimation that decreases with increasing the precipitation intensity. The difference between the two telegrams considered is large and may only be explained by differences in the instrument internal processing for the two telegrams. The second instrument tested using the CRG is the Biral VPF-750, a light scatter gauge. Results show a tendency to underestimate both the drop diameter and fall velocity. In the first case, the error decreases with increasing the drops size, similarly to the Thies LPM. However, the error in the fall velocity is considerably higher and instead increases with increasing the drop sizes. In terms of Rainfall Intensity (RI), the instrument shows a strong underestimation that, due to the opposite trend observed for drop diameter and fall velocity, is almost constant with the precipitation intensity. Both instruments show significant biases, corroborated by field intercomparison results from the literature, that is often larger than 10% for the investigated variables. This means that both gauges cannot be classified according to the guidelines proposed in this work for the development of a standard calibration procedure, derived from those already existing for CGs. The second source of bias is wind, a well-established source of environmental error for traditional Catching-type Gauges (CG) but also affecting NCGs. The wind-induced bias is investigated using a numerical approach, combining Computational Fluid Dynamics (CFD) and Lagrangian Particle Tracking (LPT) models. Two different CFD models were tested, the first providing a time-independent steady state solution, while the other is fully time-dependent. Both were compared against wind tunnel results, showing a good agreement with the experimental data, and proving their ability to capture the complex aerodynamic response of instruments when impacted by the wind. The Thies Laser Precipitation Monitor (LPM) is first chosen as a test instrument, being representative of the typical NCGs that are currently deployed in the field. CFD simulations show that wind direction is the primary factor determining the aerodynamic disturbance close to the instrument sensing area. Similar results were found for the OTT Parsivel2, that is another widely diffused NCG. For wind flow parallel to the laser beam, strong disturbance close to the gauge sensing area is observed. Meanwhile, wind coming perpendicular to the laser beam produces minimal flow disturbance. The wind-induced bias is also investigated for the Vaisala WXT-520, an impact disdrometer. This gauge is smaller ad has a more regular shape if compared to the optical disdrometers, but its measuring principle is based on the detection of the drop kinetic energy, while the size and fall velocity are indirectly obtained. CFD simulations show limited disturbance close to the sensing area of the instrument and a negligeable dependency on the wind direction (due to a more radially symmetric geometry). The instrument body further provide minimal shielding of the sensing area. Strong updraft however occurs upstream of the instrument for all wind directions, significantly affecting the fall velocity of the smaller and lighter drops. Using these results, three different LPT models are also tested. The first is an uncoupled model based on the time-independent CFD results and is used to evaluate the instrument performance for all wind speeds and directions considered. The other two models, due to their high computational requirements, are applied only to a selected number of combinations of wind speed and direction for the Thies LPM. Results show a good agreement and allow concluding that the significant increase in computational burden of the latter two models does not significantly improve the accuracy of the results. However, the one-way coupled model highlights the role of turbulence, that may have a significant impact on the instrumental performance when strong recirculation is present near its sensing area. In the case of the two other gauges, only the uncoupled LPT model in combination with the time-independent CFD model is used, this being the best compromise between numerical accuracy and computational cost. Results of the LPT model are presented in terms of variation in the retrieval of precipitation microphysical properties, Catch Ratios (CR), Collection Efficiency (CE) and Radar Retrieval Efficiency (RRE). For the three gauges considered, it is shown that smaller hydrometeors fall velocity close to the instrument sensing area is strongly affected by wind and is – in general – reduced. A significant wind-induced bias is also evident in the Drop Size Distribution (DSD) measured by the gauges. Optical gauges may report a significant lower number of small hydrometeors even at moderate wind speed. Due to the gauge body partially shielding the sensing area. Impact gauge DSD is also strongly influenced by wind, since hydrometeors with high kinetic energy are sensed as having a large diameter. The DSD is therefore shifted towards larger diameters and the instrument tends to overestimate the number of hydrometeors of all sizes. This suggests that the different shapes of the DSD function reported in the field by different instruments may be due, at least partially, to wind-induced biases. In terms of integral precipitation characteristics, the wind direction is the primary factor in determining the performance of optical gauges in windy conditions. For wind parallel to the laser beam, the instrument senses less and less precipitation with increasing the wind speed, with no hydrometeors even reaching the sensing area in some configurations . On the other hand, when the wind is perpendicular to the laser beam, the instrument performs similarly for all wind speeds, with CR and CE values close to one and only a moderate amount of overcatch being observed at high wind speed. Only for the OTT Parsivel2 a non negligeable overcatch is also evident for wind coming at a 45° angle with respect to the beam direction. For the Vaisala WXT-520 the Kinetic Catch Ratio (KCR) and Kinetic Collection Efficiency (KCE) are defined as substitutes for the CR and CE. At low wind speed, the KCR is below unity, due to the reduction in fall velocity produced by the updraft. However, with increasing wind speed, the kinetic energy of hydrometeors carried by wind increases considerably, overcoming the reduction caused by the updraft close to the gauge. For this reason, KCR values becomes much higher than unity, especially for small size hydrometeors. The increase in kinetic energy is reflected into increased KCE values, that are close to unity at low wind speed, but rapidly grow with increasing the wind speed. Wind direction has instead very limited influence on the measurements. In terms of RRE, optical gauges present limited bias for all combinations of wind speed and direction, except for the highest wind speed and flow parallel to the laser beam. This is because a large portion of the radar reflectivity factor (dBZ) is due to medium and large size hydrometeors, that are less influenced by wind. In the case of the impact disdrometer instead, RRE behaves very similarly to the CE, with values that increases with increasing wind speed. This is due to the shift toward larger diameters noted in the DSD that occurs when hydrometeors kinetic energy is increased by wind

Calibration Uncertainty of Non-Catching Precipitation Gauges

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