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Robert Tardif
and
Roy M. Rasmussen

Abstract

An analysis of the environmental conditions associated with precipitation fog events is presented using 20 yr of historical observations taken in a region centered on New York, New York. The objective is to determine the preferred weather scenarios and identify physical processes influencing the formation of fog during precipitation. Salient synoptic-scale features are identified using NCEP–NCAR reanalyses. Local environmental parameters, such as wind speed and direction, temperature, and humidity, are analyzed using surface observations, while the vertical structure of the lower atmosphere is examined using available rawinsonde data. The analysis reveals that precipitation fog mostly occurs as a result of the gradual lowering of cloud bases as continuous light rain or light drizzle is observed. Such scenarios occur under various synoptic weather patterns in areas characterized by large-scale uplift, differential temperature advection, and positive moisture advection. Precipitation fog onset typically occurs with winds from the northeast at inland locations and onshore flow at coastal locations, with flows from the south to southwest aloft. A majority of the cases showed the presence of a sharp low-level temperature inversion resulting from differential temperature advection or through the interaction of warm air flowing over a cold surface in onshore flow conditions. This suggests a common scenario of fog formation under moistening conditions resulting from precipitation evaporating into colder air near the surface. A smaller number of events formed with cooling of the near-saturated or saturated air. Evidence is also presented of the possible role of shear-induced turbulent mixing in the production of supersaturation and fog formation during precipitation.

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Robert Tardif
and
Roy M. Rasmussen

Abstract

The character of fog in a region centered on New York City, New York, is investigated using 20 yr of historical data. Hourly surface observations are used to identify fog events at 17 locations under the influence of various physiographic features, such as land–water contrasts, land surface character (urban, suburban, and rural), and terrain. Fog events at each location are classified by fog types using an objective algorithm derived after extensive examination of fog formation processes. Events are characterized according to frequency, duration, and intensity. A quantitative assessment of the likelihood with which mechanisms leading to fog formation are occurring in various parts of the region is obtained. The spatial, seasonal, and diurnal variability of fog occurrences are examined and results are related to regional and local influences. The results show that the likelihood of fog occurrence is influenced negatively by the presence of the urban heat island of New York City, whereas it is enhanced at locations under the direct influence of the marine environment. Inland suburban and rural locations also experience a considerable amount of fog. As in other areas throughout the world, the overall fog phenomenon is a superposition of various types. Precipitation fog, which occurs predominantly in winter, is the most common type. Fog resulting from cloud-base lowering also occurs frequently across the region, with an enhanced likelihood in winter and spring. A considerable number of advection fog events occur in coastal areas, mostly during spring, whereas radiation fog occurs predominantly at suburban and rural locations during late summer and early autumn but also occurs during the warm season in the coastal plain of New Jersey as advection–radiation events.

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George D. Modica
,
Scot T. Heckman
, and
Roy M. Rasmussen

Abstract

A hydrostatic regional prediction model is modified to permit the existence of both liquid and ice hydrometeors within the same grid volume. The modified model includes an efficient ice-water saturation adjustment and a simple procedure to create or remove cloud water or ice. The objective was to determine whether such a model could provide deterministic forecasts of aircraft icing conditions in the 6–36-h period. The model was used to simulate an orographically forced icing event (the Valentine's Day storm of 12–14 February 1990) that occurred during the 1990 phase of the Winter Icing and Storms Project (WISP-90). Output from a 24-h nested-grid integration of the model was compared to observations taken during WISP-90. The model produced a thin (∼1-2 km deep) supercooled liquid water (SLW) cloud that was in good agreement with observations in terms of initiation, duration, liquid water content, and location. Results of the simulation also suggest that slantwise ascent can be an important component in the production of SLW.

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Roy M. Rasmussen
,
Jothiram Vivekanandan
,
Jeffrey Cole
,
Barry Myers
, and
Charles Masters

Abstract

The relationship between liquid equivalent snowfall rate and visibility is investigated using data collected at the National Center for Atmospheric Research Marshall Snowfall Test Site during two winter field seasons and using theoretical relationships. The observational data include simultaneous liquid equivalent snowfall rate, crystal types, and both automated and manual visibility measurements. Theoretical relationships between liquid equivalent snowfall rate and visibility are derived for 27 crystal types, and for “dry” and “wet” aggregated snowflakes. Both the observations and theory show that the relationship between liquid equivalent snowfall rate and visibility depends on the crystal type, the degree of riming, the degree of aggregation, and the degree of wetness of the crystals, leading to a large variation in the relationship between visibility and snowfall rate. Typical variations in visibility for a given liquid equivalent snowfall rate ranged from a factor of 3 to a factor of 10, depending on the storm. This relationship is shown to have a wide degree of scatter from storm to storm and also during a given storm. The main cause for this scatter is the large variation in cross-sectional area to mass ratio and terminal velocity for natural snow particles.

It also is shown that the visibility at night can be over a factor of 2 greater than the visibility during the day for the same atmospheric extinction coefficient. Since snowfall intensity is defined by the U.S. National Weather Service using visibility, this day/night difference in visibility results in a change in snowfall intensity category caused by only whether it is day or night. For instance, a moderate snowfall intensity during the day will change to a light snowfall intensity at night, and a heavy snowfall intensity during the day will change to a moderate snowfall intensity at night, for the same atmospheric extinction coefficient.

Thus, the standard relationship between snowfall intensity and visibility used by many national weather services (1/4 mile or less visibility corresponds to heavy snowfall intensity, between 5/16 and 5/8 mile corresponds to moderate intensity, and greater than 5/8 mile corresponds to light intensity) does not always provide the correct indication of actual liquid equivalent snowfall rate because of the variations in snow type and the differences in the nature of visibility targets during day and night. This false indication may have been a factor in previous ground-deicing accidents in which light snow intensity was reported based on visibility, when in fact the actual measured liquid equivalent snowfall rate was moderate to heavy.

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Julie M. Thériault
,
Roy Rasmussen
,
Kyoko Ikeda
, and
Scott Landolt

Abstract

Accurate snowfall measurements are critical for a wide variety of research fields, including snowpack monitoring, climate variability, and hydrological applications. It has been recognized that systematic errors in snowfall measurements are often observed as a result of the gauge geometry and the weather conditions. The goal of this study is to understand better the scatter in the snowfall precipitation rate measured by a gauge. To address this issue, field observations and numerical simulations were carried out. First, a theoretical study using finite-element modeling was used to simulate the flow around the gauge. The snowflake trajectories were investigated using a Lagrangian model, and the derived flow field was used to compute a theoretical collection efficiency for different types of snowflakes. Second, field observations were undertaken to determine how different types, shapes, and sizes of snowflakes are collected inside a Geonor, Inc., precipitation gauge. The results show that the collection efficiency is influenced by the type of snowflakes as well as by their size distribution. Different types of snowflakes, which fall at different terminal velocities, interact differently with the airflow around the gauge. Fast-falling snowflakes are more efficiently collected by the gauge than slow-falling ones. The correction factor used to correct the data for the wind speed is improved by adding a parameter for each type of snowflake. The results show that accurate measure of snow depends on the wind speed as well as the type of snowflake observed during a snowstorm.

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Jaclyn M. Ritzman
,
Terry Deshler
,
Kyoko Ikeda
, and
Roy Rasmussen

Abstract

Annual precipitation increases of 10% or more are often quoted for the impact of winter orographic cloud seeding; however, establishing the basis for such values is problematic for two reasons. First, the impact of glaciogenic seeding of candidate orographic storms has not been firmly established. Second, not all winter precipitation is produced by candidate “seedable” storms. Addressing the first question motivated the Wyoming state legislature to fund a multiyear, crossover, randomized cloud-seeding experiment in southeastern Wyoming to quantify the impact of glaciogenic seeding of wintertime orographic clouds. The crossover design requires two barriers, one randomly selected for seeding, for comparisons of seeded and nonseeded precipitation under relatively homogeneous atmospheric conditions. Addressing the second question motivated the work here. The seeding criteria—700-hPa temperatures ≤−8°C, 700-hPa winds between 210° and 315°, and the presence of supercooled liquid water—were applied to eight winters to determine the percent of winter precipitation that may fall under the seeding criteria. Since no observational datasets provide precipitation and all of the atmospheric variables required for this study, a regional climate model dynamical downscaling of historical data over 8 years was used. The accuracy of the model was tested against several measurements, and the small model biases were removed. On average, ~26% of the time between 15 November and 15 April atmospheric conditions were seedable over the barriers in southeastern Wyoming. These seedable conditions were accompanied by precipitation ~12%–14% of the time, indicating that ~27%–30% of the winter precipitation resulted from seedable clouds.

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Kyoko Ikeda
,
Roy M. Rasmussen
,
Edward Brandes
, and
Frank McDonough

Abstract

This study describes a freezing drizzle detection algorithm based on the Weather Surveillance Radar-1988 Doppler (WSR-88D) measured radar reflectivity. Although radar returns from freezing drizzle and light snow are similar—<5 dBZ and spatially uniform—freezing drizzle can be identified using feature parameters computed from radar reflectivity, such as local and global standard deviations and reflectivity texture weighted with a fuzzy-logic scheme. Algorithm results agree well with surface precipitation reports. The proposed algorithm can serve as one component of automated decision-support schemes for icing hazard detection and/or hydrometeor identification.

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Ben C. Bernstein
,
Roy M. Rasmussen
,
Frank McDonough
, and
Cory Wolff

Abstract

Using observations from research aircraft flights over the Great Lakes region, synoptic and mesoscale environments that appear to drive a relationship between liquid water content, drop concentration, and drop size are investigated. In particular, conditions that fell within “small drop” and “large drop” regimes are related to cloud and stability profiles, providing insight regarding whether the clouds are tied to the local boundary layer. These findings are supported by analysis of flight data from other parts of North America and used to provide context for several icing incidents and accidents where large-drop icing was noted as a contributing factor. The relationships described for drop size discrimination in continental environments provide clues that can be applied for both human- and model-generated icing forecasts, as well as automated icing algorithms.

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Roy M. Rasmussen
,
Ben C. Bernstein
,
Masataka Murakami
,
Greg Stossmeister
,
Jon Reisner
, and
Boba Stankov

Abstract

The mesoscale and microscale structure and evolution of a shallow, upslope cloud is described using observations obtained during the Winter Icing and Storms Project (WISP) and model stimulations. The upslope cloud formed within a shallow arctic air mass that moved into the region east of the Rocky Mountains between 12 and 16 February and contained significant amounts of supercooled liquid water for nearly 30 h. Two distinct layers were evident in the cloud. The lower layer was near neutral stability (boundary layer air) and contained easterly upslope flow. The upper layer (frontal transition zone) was thermodynamically stable and contained southerly flow. Overlying the upslope cloud was a dry, southwesterly flow of 20–25 m s −1, resulting in strong wind shear near cloud top. Within 10 km of the Rocky Mountain barrier, easterly low-level flow was lifted up and over the mountains. The above-described kinematic and thermodynamic structure produced three distinct mechanisms leading to the production of supercooled liquid water: 1) upslope flow over the gently rising terrain leading into the Colorado Front Range, up the slopes of the Rocky Mountains and over local ridges, 2)upglide flow within a frontal transition zone, and 3) turbulent mixing in the boundary layer. Supercooled liquid water was also produced by 1) upward motion at the leading edge of three cold surges and 2) vertical motion produced by low-level convergence in the surface wind field. Large cloud droplets were present near the top of this cloud (approximately 50-µm diameter), which grew by a direct coalescence process into freezing drizzle in regions of the storm where the liquid water content was greater than 0.25 g m −3 and vertical velocity was at 10 cm s −1

Ice crystal concentrations greater than 1 L−1 were observed in the lower cloud layer containing boundary layer air when the top of the boundary layer air when the top of the boundary layer was colder than −12°C. The upper half of the cloud was ice-free despite temperatures as low as −15°C, resulting in long-lived supercooled liquid water in this region of the cloud.

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Edward A. Brandes
,
Kyoko Ikeda
,
Guifu Zhang
,
Michael Schönhuber
, and
Roy M. Rasmussen

Abstract

Winter-storm hydrometeor distributions along the Front Range in eastern Colorado are studied with a ground-based two-dimensional video disdrometer. The instrument provides shape, size, and terminal velocity information for particles that are larger than about 0.4 mm. The dataset is used to determine the form of particle size distributions (PSDs) and to search for useful interrelationships among the governing parameters of assumed distribution forms and environmental factors. Snowfalls are dominated by almost spherical aggregates having near-exponential or superexponential size distributions. Raindrop size distributions are more peaked than those for snow. A relation between bulk snow density and particle median volume diameter is derived. The data suggest that some adjustment may be needed in relationships found previously between temperature and the concentration and slope parameters of assumed exponential PSDs. A potentially useful relationship is found between the slope and shape terms of the gamma PSD model.

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