Freezing fraction in freezing rain

Freezing rain can cause significant tree damage with fallen trees and branches blocking roads and taking power distribution lines out of service. Power transmission lines are designed for ice loads from freezing rain, using models to estimate equivalent radial ice thicknesses from historical weather data. The conservative simple flux model assumes that all the freezing rain that impinges on a horizontal cylinder, representing vegetation or components of the built infrastructure, freezes. Here I present a simplified heat-balance formulation to calculate the fraction of the impinging precipitation that freezes, using parameters measured at ASOS weather stations and an estimate of solar heating. Radial ice thickness estimates from this approach are compared with the simple model and those generated from the ASOS icing sensor. These estimates can all be tested by comparing to measurements on cylinders at weather stations. A link to an Excel spreadsheet that calculates freezing fraction using user-input weather data is provided. In forecast freezing rain events, this tool could be used by utility crews and emergency response teams to estimate the likely range of equivalent radial ice thicknesses over the affected region and plan their response accordingly.

The Extended Period Precursory Signals of Strong Persistent Freezing Rain and Snow Events in Southwest China

In this study, daily temperature and precipitation data between 1950 and 2018 from 753 stations from National Meteorological Information Center, and NCEP/NCAR reanalysis data were used to screen freezing rain and snow events that occurred in the winters of 1951–2017 in southwest China (100°E–110°E, 22.5°N–32.5°N), in order to search for extended period warning signs of events. The combined anomalies index PCA ,established by the Mongolian Geopotential height pressure intensity, north–south position index and the southern trough intensity index, is closely related to the freezing rain and snow events in southwest China, and can be used as a link to explore the precursory signals of persistent freezing rain and snow events. The 1000-hPa height field of Iceland (60°N–80°N, 10°W–50°W), the North Atlantic (25°N–45°N; 20°W–60°W) and the Caspian Sea (30°N–50°N; 30°E–70°E) in the early mid-latitude was significantly correlated with PCA . The high disturbance signal in the upstream dispersed to the downstream 15–20 days in advance, which intensified the Mongolian high and deepened the southern trough. The combination anomaly of the Mongolian high and southern trough finally led to the strong persistent freezing rain and snow events in southwest China. The extended period forecast index of strong persistent freezing rain and snow events in southwest China was established according to the average geopotential height of key atmospheric regions 15 days ahead of the event. These findings provide a reference for the prediction of winter disaster events extension-period forecast in southern China.

Changes in Freezing Rain Occurrence Over Eastern Canada Using Convection-Permitting Climate Simulations

Freezing precipitation have major consequences for ground and air transportation, the health of citizens, and power networks. Previous studies using coarse resolution climate models have shown a northward migration of freezing rain in the future. Increased model resolution can better define local topography leading to improved representation of conditions that are favorable for freezing rain. The goal of this study is to examine the climatology and characteristics of future freezing rain events using very-high resolution climate models. Historical and pseudo-global warming simulations with a 4-km horizontal resolution were used and compared with available observations. Simulations revealed a northerly shift of freezing rain occurrence, and an increase in the winter. Freezing rain was still shown to occur in the Saint-Lawrence River Valley in a warmer climate, primarily due to stronger wind channeling. Up to 50% of the future freezing rain events also occurred in the historical simulation within 12 h of each other. In northern Maine, they are typically shorter than 6 h in current climate and longer than 6 h in warmer conditions due to the timing of low-pressure systems. The occurrence of freezing rain also locally increases slightly north of Québec City in a warmer climate because of freezing rain that is produced by warm rain processes. Overall, the study shows that high-resolution, regional climate simulations are needed to study freezing rain events in warmer climate conditions, because high resolutions better define the atmospheric conditions aloft and near the surface that strongly influence these events.

Enhancing Icing Detection and Characterization using the New York State Mesonet

The accurate detection and monitoring of freezing rain and icing conditions at the surface is a notoriously challenging but important problem. This work attempts to enhance icing detection and characterization utilizing data from the New York State Mesonet (NYSM). NYSM is the first operational network measuring winds at 10 meters from two independent sensors: propeller and sonic anemometers. During and after freezing rain events, large wind speed differences are frequently reported between the two anemometers because the propeller develops a coating of ice, thus either stopping or slowing its rotation. Such errors of propeller data provide a signal for identifying icing conditions. An automated method for identifying “active freezing rain” (AFR) and a continuation of “frozen surface” (FS) conditions is developed. Hourly maps of AFR and FS sites are generated using four criteria: (1) a wind speed difference (sonic – propeller) of > 1 m s-1 or 0 m s-1 propeller wind speed for at least half hour, (2) a temperature threshold of -5°C to 2°C for AFR and less than 2°C for FS, (3) insignificant hourly snow accumulation, and (4) with (or without) significant hourly precipitation accumulation for AFR (or FS). The AFR events detected by the automated method for last four winters (2017-2021) show very good agreements in starting and ending times with that from ASOS data. A case study of the ice storm during 14-16 April 2018 further demonstrates the validity of the methodology and highlights the benefit of NYSM profiler and camera data.

Synoptic–Dynamic and Airmass Characteristics Distinguishing Long- and Short-Duration Freezing Rain Events in the South-Central United States

Though prolonged freezing rain events are rare, they can result in substantial damage when they occur. While freezing rain occurs less frequently in the south-central United States than in some regions of North America, a large number of extremely long-duration events lasting at least 18 h have been observed there. We explore the key synoptic–dynamic conditions that lead to these extreme events through a comparison with less severe short-duration events. We produce synoptic–dynamic composites and 7-day backward trajectories for parcels ending in the warm and cold layers for each event category. The extremely long-duration events are preferentially associated with a deeper and more stationary 500-hPa longwave trough centered over the southwestern United States at event onset. This trough supports sustained flow of warm, moist air from within the planetary boundary layer over the Gulf of Mexico northward into the warm layer. The short-duration cases are instead characterized by a more transient upper-level trough axis centered over the south-central U.S. region at onset. Following event onset, rapid passage of the trough leads to quasigeostrophic forcing for descent and the advection of cold, dry air that erodes the warm layer and ends precipitation. While trajectories ending in the cold layer are very similar between the two categories, those ending in the warm layer have a longer history over the Gulf of Mexico in the extreme cases compared with the short-duration ones, resulting in warmer and moister onset warm layers.

Differentiating Freezing Drizzle and Freezing Rain in HRRR Model Forecasts

Supercooled large drop (SLD) icing poses a unique hazard for aircraft and has resulted in new regulations regarding aircraft certification to fly in regions of known or forecast SLD icing conditions. The new regulations define two SLD icing categories based upon the maximum supercooled liquid water drop diameter (Dmax): freezing drizzle (100–500 μm) and freezing rain (> 500 μm). Recent upgrades to U.S. operational numerical weather prediction models lay a foundation to provide more relevant aircraft icing guidance including the potential to predict explicit drop size. The primary focus of this paper is to evaluate a proposed method for estimating the maximum drop size from model forecast data to differentiate freezing drizzle from freezing rain conditions. Using in-situ cloud microphysical measurements collected in icing conditions during two field campaigns between January and March 2017, this study shows that the High-Resolution Rapid Refresh model is capable of distinguishing SLD icing categories of freezing drizzle and freezing rain using a Dmax extracted from the rain category of the microphysics output. It is shown that the extracted Dmax from the model correctly predicted the observed SLD icing category as much as 99% of the time when the HRRR accurately forecast SLD conditions; however, performance varied by the method to define Dmax and by the field campaign dataset used for verification.