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Edward A. Brandes and Kyoko Ikeda

Abstract

A simple empirical procedure for determining freezing levels with polarimetric radar measurements is described. The algorithm takes advantage of the strong melting-layer signatures and the redundancy provided by the suite of polarimetric radar measurements—in particular, radar reflectivity, linear depolarization ratio, and cross-correlation coefficient. Freezing-level designations can be made with all volumetric scanning strategies. Application to uniform (stratiform) precipitation within 60 km of the radar and with brightband reflectivity maxima of greater than 25 dBZ suggests an accuracy of 100–200 m.

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Kyoko Ikeda, Matthias Steiner, and Gregory Thompson

Abstract

Accurate prediction of mixed-phase precipitation remains challenging for numerical weather prediction models even at high resolution and with a sophisticated explicit microphysics scheme and diagnostic algorithm to designate the surface precipitation type. Since mixed-phase winter weather precipitation can damage infrastructure and produce significant disruptions to air and road travel, incorrect surface precipitation phase forecasts can have major consequences for local and statewide decision-makers as well as the general public. Building upon earlier work, this study examines the High-Resolution Rapid Refresh (HRRR) model’s ability to forecast the surface precipitation phase, with a particular focus on model-predicted vertical temperature profiles associated with mixed-phase precipitation, using upper-air sounding observations as well as the Automated Surface Observing Systems (ASOS) and Meteorological Phenomena Identification Near the Ground (mPING) observations. The analyses concentrate on regions of mixed-phase precipitation from two winter season events. The results show that when both the observational and model data indicated mixed-phase precipitation at the surface, the model represents the observed temperature profile well. Overall, cases where the model predicted rain but the observations indicated mixed-phase precipitation generally show a model surface temperature bias of <2°C and a vertical temperature profile similar to the sounding observations. However, the surface temperature bias was ~4°C in weather systems involving cold-air damming in the eastern United States, resulting in an incorrect surface precipitation phase or the duration (areal coverage) of freezing rain being much shorter (smaller) than the observation. Cases with predicted snow in regions of observed mixed-phase precipitation present subtle difference in the elevated layer with temperatures near 0°C and the near-surface layer.

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Kyoko Ikeda, Roy M. Rasmussen, William D. Hall, and Gregory Thompson

Abstract

Observations of supercooled drizzle aloft within two storms impacting the Oregon Cascades during the second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) field project are presented. The storms were characterized by a structure and evolution similar to the split-front model of synoptic storms. Both storms were also characterized by strong cross-barrier flow. An analysis of aircraft and radar data indicated the presence of supercooled drizzle during two distinct storm periods: 1) the intrafrontal period immediately following the passage of an upper cold front and 2) the postfrontal period. The conditions associated with these regions of supercooled drizzle included 1) temperatures between −3° and −19°C, 2) ice crystal concentrations between 1 and 2 L−1, and 3) bimodal cloud droplet distributions of low concentration [cloud condensation nuclei (CCN) concentration between 20 and 30 cm−3 and cloud drop concentration <35 cm−3].

Unique to this study was the relatively cold cloud top (<−15°C) and relatively high ice crystal concentrations in the drizzle region. These conditions typically hinder drizzle formation and survival; however, the strong flow over the mountain barrier amplified vertical motions (up to 2 m s−1) above local ridges, the mountain crest, and updrafts in embedded convection. These vertical motions produced high condensate supply rates that were able to overcome the depletion by the higher ice crystal concentrations. Additionally, the relatively high vertical motions resulted in a near balance of ice crystal fall speed (0.5–1.0 m s−1), leading to nearly terrain-parallel trajectories of the ice particles and a reduction of the flux of ice crystals from the higher levels into the low-level moisture-rich cloud, allowing the low-level cloud water and drizzle to be relatively undepleted.

One of the key observations in the current storms was the persistence of drizzle drops in the presence of significant amounts of ice crystals over the steepest portion of the mountain crest. Despite the high radar reflectivity produced by the ice crystals (>15 dBZ) in this region, the relatively high condensate supply rate led to hazardous icing conditions. The current study reveals that vertical motions generated by local topographic features are critical in precipitation processes such as drizzle formation and thus it is essential that microphysical models predict these motions.

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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, Matthias Steiner, James Pinto, and Curtis Alexander

Abstract

The hourly updating High-Resolution Rapid Refresh (HRRR) model is evaluated with regard to its ability to predict the areal extent of cold-season precipitation and accurately depict the timing and location of regions of snow, rain, and mixed-phase precipitation on the ground. Validation of the HRRR forecasts is performed using observations collected by the Automated Surface Observing System (ASOS) stations across the eastern two-thirds of the United States during the 2010–11 cold season. The results show that the HRRR is able to reliably forecast precipitation extent during the cold season. In particular, the location and areal extent of both snow and rain are very well predicted. Depiction of rain-to-snow transitions and freezing rain is reasonably good; however, the associated evaluation scores are significantly lower than for either snow or rain. The analyses suggest the skill in accurately depicting precipitation extent and phase (i.e., rain, snow, and mixed phase) depends on the size and organization of a weather system. Typically, larger synoptically forced weather systems are better predicted than smaller weather systems, including the associated rain-to-snow transition or freezing-rain areas. Offsets in space or time (i.e., causing misses and false alarms) have a larger effect on the model performance for smaller weather systems.

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Changhai Liu, Kyoko Ikeda, Gregory Thompson, Roy Rasmussen, and Jimy Dudhia

Abstract

An investigation was conducted on the effects of various physics parameterizations on wintertime precipitation predictions using a high-resolution regional climate model. The objective was to evaluate the sensitivity of cold-season mountainous snowfall to cloud microphysics schemes, planetary boundary layer (PBL) schemes, land surface schemes, and radiative transfer schemes at a 4-km grid spacing applicable to the next generation of regional climate models.

The results indicated that orographically enhanced precipitation was highly sensitive to cloud microphysics parameterizations. Of the tested 7 parameterizations, 2 schemes clearly outperformed the others that overpredicted the snowfall amount by as much as ~30%–60% on the basis of snow telemetry observations. Significant differences among these schemes were apparent in domain averages, spatial distributions of hydrometeors, latent heating profiles, and cloud fields. In comparison, model results showed relatively weak dependency on the land surface, PBL, and radiation schemes, roughly in the order of decreasing level of sensitivity.

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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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Kyoko Ikeda, Edward A. Brandes, and Roy M. Rasmussen

Abstract

An unusual multiple freezing-level event observed with polarimetric radar during the second phase of the Improvement of Microphysical Parameterization through Observational Verification Experiments (IMPROVE-2) field program is described. The event occurred on 28 November 2001 when a warm front moved over the Oregon Cascade Mountains. As the front approached, an elevated melting layer formed above a preexisting melting layer near ground. Continued warming of the lower atmosphere eventually dissipated the lower melting layer.

The polarimetric measurements are used to estimate the height of the freezing levels, document their evolution, and deduce hydrometeor habits. The measurements indicate that when the two freezing levels were first observed melting was incomplete in the upper melting layer and characteristics of particles that passed through the two melting layers were similar. As warming progressed, the character of particles entering the lower melting layer changed, possibly becoming ice pellets or frozen drops. Eventually, the refreezing of particles ended and only rain occurred below the elevated melting layer.

The Doppler radial winds showed a well-defined wind maximum apparently associated with a “warm conveyor belt.” The jet intensified and descended through the elevated melting layer with time. However, the increase in wind speed did not appear connected with melting or result in precipitation enhancement.

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Hugh Morrison, Sarah A. Tessendorf, Kyoko Ikeda, and Gregory Thompson

Abstract

This paper describes idealized simulations of a squall line observed on 20 June 2007, in central Oklahoma. Results are compared with measurements from dual-polarization radar and surface disdrometer. The baseline model configuration qualitatively reproduces key storm features, but underpredicts precipitation rates and generally overpredicts median volume raindrop diameter. The sensitivity of model simulations to parameterization of raindrop breakup is tested under different low-level (0–2.5 km) environmental vertical wind shears. Storm characteristics exhibit considerable sensitivity to the parameterization of breakup, especially for moderate (0.0048 s−1) shear. Simulations with more efficient breakup tend to have higher domain-mean precipitation rates under both moderate and higher (0.0064 s−1) shear, despite the smaller mean drop size and hence lower mass-weighted fall speed and higher evaporation rate for a given rainwater content. In these runs, higher evaporation leads to stronger cold pools, faster propagation, larger storm size, greater updraft mass flux (but weaker convective updrafts at mid- and upper levels), and greater total condensation that compensates for the increased evaporation to give more surface precipitation. The impact of drop breakup on mass-weighted fall speed is also important and leads to a nonmonotonic response of storm characteristics (surface precipitation, cold pool strength, etc.) to changes in breakup efficiency under moderate wind shear. In contrast, the response is generally monotonic at higher wind shear. Interactions between drop breakup, convective dynamics, cold pool intensity, and low-level environmental wind shear are also described in the context of “Rotunno–Klemp–Weisman (RKW) theory,” which addresses how density currents evolve in sheared environments.

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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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