Analysis of a seeder-feeder and freezing drizzle event

• Published in: Journal of geophysical research. Atmospheres 2015-05, Vol.120 (9), p.3984-3999
• Main Authors: Fernández-González, S., Valero, F., Sánchez, J. L., Gascón, E., López, L., García-Ortega, E., Merino, A.
• Format: Article
• Language: English
• Subjects: Climatology; Clouds; Freezing; freezing drizzle; Geophysics; Glaciation; Icing; in-cloud icing; Mathematical models; Meteorology; Mountains; Precipitation; Prediction models; Risk; Risk reduction; seeder-feeder; snowfall; Weather; Weather forecasting; WRF
• ISSN: 2169-897X; 2169-8996
• DOI: 10.1002/2014JD022916

Surface icing can cause dramatic consequences on human activities. What is more, numerical weather prediction models are not very accurate in determining freezing drizzle, which creates uncertainty when forecasting this type of weather phenomenon. Therefore, it is essential to improve the forecast accuracy of these models for such phenomena to mitigate risks caused by unforeseen freezing drizzle events. On 5 February 2012, an episode of freezing drizzle took place in the Guadarrama Mountains, at the center of the Iberian Peninsula. This episode was preceded by weak snowfall. After the freezing drizzle, moderate snowfall was recorded in the study area. This event was simulated using the Weather Research and Forecasting model. Through this analysis, we identified the meteorological factors at both synoptic scale and mesoscale that caused this episode. Wind perpendicular to an orographic barrier‐generated updrafts and retention of moisture upwind, which caused orographic clouds to appear on the north side of the Guadarrama Mountains. Atmospheric stability prevented cloud formation at midlevels at the time of the freezing drizzle, which maintained cloud top temperatures warmer than −15°C during the episode. The entrance of moisture and instability at midlevels caused cloud top temperatures substantially colder than −15°C, which coincided with snow in the mountain range. Cloud top temperature and thickness control the efficiency of the glaciation process, thereby determining the type of precipitation at the surface. Freezing drizzle risk and in‐cloud icing algorithms were developed with the aim of predicting similar events in the study area, which could mitigate impacts on human activities. Key Points A seeder‐feeder and freezing drizzle episodes was registered This episode has been analyzed with the WRF model Cloud top temperature is strongly connected with precipitation type