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It has been known for a long time that the shape of ice crystals depends on both the air temperature and the relative humidity of the environment. The relationships among these factors have been summarized in classification diagrams and are intensively referred to in the cloud physics literature. To put in perspective the atmospheric conditions in which the different ice crystal habits grow with respect to the level of saturation in the atmosphere, the vapor density excess and supersaturation with respect to ice at liquid water saturation have been included on those diagrams as a function of air temperature. Over the years, the definition of the water saturation included in those types of diagrams has been misdefined. The goal of this study is to show that an error has been introduced in the definition of the excess of water vapor with respect to ice.
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Abstract This article examines the types of winter precipitation that occur near 0°C, specifically rain, freezing rain, freezing drizzle, ice pellets, snow pellets, and wet snow. It follows from a call by M. Ralph et al. for more attention to be paid to this precipitation since it represents one of the most serious wintertime quantitative precipitation forecasting (QPF) issues. The formation of the many precipitation types involves ice-phase and/or liquid-phase processes, and thresholds in the degree of melting and/or freezing often dictate the types occurring at the surface. Some types can occur simultaneously so that, for example, ensuing collisions between supercooled raindrops and ice pellets that form ice pellet aggregates can lead to substantial reductions in the occurrence of freezing rain at the surface, and ice crystal multiplication processes can lead to locally produced ice crystals in the subfreezing layer below inversions. Highly variable fall velocities within the background temperature and wind fields of precipitation-type transition regions lead to varying particle trajectories and significant alterations in the distribution of precipitation amount and type at the surface. Physically based predictions that account for at least some of the phase changes and particle interactions are now in operation. Outstanding issues to be addressed include the impacts of accretion on precipitation-type formation, quantification of melting and freezing rates of the highly variable precipitation, the consequences of collisions between the various types, and the onset of ice nucleation and its effects. The precipitation physics perspective of this article furthermore needs to be integrated into a comprehensive understanding involving the surrounding and interacting environment.
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Abstract 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 Reynolds-averaged 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.
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Abstract 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.