Matteo Colli

An Improved Trajectory Model to Evaluate the Collection Performance of Snow Gauges

Recent studies have used numerical models to estimate the collection efficiency of solid precipitation gauges when exposed to the wind in both shielded and unshielded configurations. The models used computational fluid dynamics (CFD) simulations of the airflow pattern generated by the aerodynamic response to the gauge‐shield geometry. These are used as initial conditions to perform Lagrangian tracking of solid precipitation particles. Validation of the results against field observations yielded similarities in the overall behavior, but the model output only approximately reproduced the dependence of the experimental collection efficiency on wind speed. This paper presents an improved snowflake trajectory modeling scheme due to the inclusion of a dynamically determined drag coefficient. The drag coefficient was estimated using the local Reynolds number as derived from CFD simulations within a time-independent Reynoldsaveraged Navier‐Stokes approach. The proposed dynamic model greatly improves the consistency of results with the field observations recently obtained at the Marshall Field winter precipitation test bed in Boulder, Colorado.

The Collection Efficiency of Shielded and Unshielded Precipitation Gauges. Part II: Modeling Particle Trajectories

AbstractThe use of windshields to reduce the impact of wind on snow measurements is common. This paper investigates the catching performance of shielded and unshielded gauges using numerical simulations. In Part II, the role of the windshield and gauge aerodynamics, as well as the varying flow field due to the turbulence generated by the shield–gauge configuration, in reducing the catch efficiency is investigated. This builds on the computational fluid dynamics results obtained in Part I, where the airflow patterns in the proximity of an unshielded and single Alter shielded Geonor T-200B gauge are obtained using both time-independent [Reynolds-averaged Navier–Stokes (RANS)] and time-dependent [large-eddy simulation (LES)] approaches. A Lagrangian trajectory model is used to track different types of snowflakes (wet and dry snow) and to assess the variation of the resulting gauge catching performance with the wind speed. The collection efficiency obtained with the LES approach is generally lower than the on...

The Collection Efficiency of Shielded and Unshielded Precipitation Gauges. Part I: CFD Airflow Modeling

AbstractThe aerodynamic response of snow gauges when exposed to the wind is responsible for a significant reduction of their collection performance. The modifications induced by the gauge and the windshield onto the space–time patterns of the undisturbed airflow deviate the snowflake trajectories. In Part I, the disturbed air velocity field in the vicinity of shielded and unshielded gauge configurations is investigated. In Part II, the airflow is the basis for a particle tracking model of snowflake trajectories to estimate the collection efficiency. A Geonor T-200B gauge inside a single Alter shield is simulated for wind speeds varying from 1 to 8 m s−1. Both time-averaged and time-dependent computational fluid dynamics simulations are performed, based on Reynolds-averaged Navier–Stokes (RANS) and large-eddy simulation (LES) models, respectively. A shear stress tensor k–Ω model (where k is the turbulent kinetic energy and Ω is the turbulent specific dissipation rate) is used for the RANS formulation and s...

Impact of Wind Direction, Wind Speed, and Particle Characteristics on the Collection Efficiency of the Double Fence Intercomparison Reference

The accurate measurement of snowfall is important in various fields of study such as climate variability, transportation, and water resources. A major concern is that snowfall measurements are difficult and can result in significant errors. For example, collection efficiency of most gauge–shield configurations generally decreases with increasing wind speed. In addition, much scatter is observed for a given wind speed, which is thought to be caused by the type of snowflake. Furthermore, the collection efficiency depends strongly on the reference used to correct the data, which is often the Double Fence Intercomparison Reference (DFIR) recommended by the World Meteorological Organization. The goal of this study is to assess the impact of weather conditions on the collection efficiency of the DFIR. Note that the DFIR is defined as a manual gauge placed in a double fence. In this study, however, only the double fence is being investigated while still being called DFIR. To address this issue, a detailed analysis of the flow field in the vicinity of the DFIR is conducted using computational fluid dynamics. Particle trajectories are obtained to compute the collection efficiency associated with different precipitation types for varying wind speed. The results show that the precipitation reaching the center of the DFIR can exceed 100% of the actual precipitation, and it depends on the snowflake type, wind speed, and direction. Overall, this study contributes to a better understanding of the sources of uncertainty associated with the use of the DFIR as a reference gauge to measure snowfall.

Quantifying and Mitigating Wind‐Induced Undercatch in Rainfall Measurements

Despite the apparent simplicity, it is notoriously difficult to measure rainfall accurately because of the challenging environment within which it is measured. Systematic bias caused by wind is inherent in rainfall measurement and introduces an inconvenient unknown into hydrological science that is generally ignored. This paper examines the role of rain gauge shape and mounting height on catch efficiency (CE), where CE is defined as the ratio between nonreference and reference rainfall measurements. Using a pit gauge as a reference, we have demonstrated that rainfall measurements from an exposed upland site, recorded by an adjacent conventional cylinder rain gauge mounted at 0.5 m, were underestimated by more than 23% on average. At an exposed lowland site, with lower wind speeds on average, the equivalent mean undercatch was 9.4% for an equivalent gauge pairing. An improved-aerodynamic gauge shape enhanced CE when compared to a conventional cylinder gauge shape. For an improved-aerodynamic gauge mounted at 0.5 m above the ground, the mean undercatch was 11.2% at the upland site and 3.4% at the lowland site. The mounting height of a rain gauge above the ground also affected CE due to the vertical wind gradient near to the ground. Identical rain gauges mounted at 0.5 and 1.5 m were compared at an upland site, resulting in a mean undercatch of 11.2% and 17.5%, respectively. By selecting three large rainfall events and splitting them into shorter-duration intervals, a relationship explaining 81% of the variance was established between CE and wind speed. Plain Language Summary This study was motivated by how challenging it is to measure rainfall accurately, despite it appearing to be very simple. Rainfall measurement is important to society because it has so many everyday uses, such as food production and weather forecasting, and applications that are critical to life, such as flood warning and effective management of water resources. Rainfall is difficult to measure because it varies so much in time and space, and the measurement of rain is highly affected by how windy it is, which also varies in time and space. Therefore, when it rains at the same time as being very windy, which is common during many storms, rainfall measurements are greatly underestimated. The uplands generally receive more rainfall and higher wind speeds than the lowlands, therefore it follows that we underestimate rainfall by more in the uplands. This is important because rainfall measurements in the uplands are sparse, yet it is in such areas where many floods originate. This study shows that the underestimation of rainfall at a site in the windy Scottish uplands was more than 23% on average. It then suggests some techniques that can be implemented to improve the measurement of rainfall.