Precipitation Type Distribution and Microphysical Processes During the 1998 Ice Storm Simulated Under Pseudo‐Warmer Conditions

2021 ◽  
Author(s):  
M. Cholette ◽  
J. M. Thériault
Keyword(s):  
Ice Storm ◽  
Type Distribution ◽  
Precipitation Type ◽  
Microphysical Processes

Classification of Precipitation Types during Transitional Winter Weather Using the RUC Model and Polarimetric Radar Retrievals

2012 ◽  
Vol 51 (4) ◽  
pp. 763-779 ◽  
Author(s):  
Terry J. Schuur ◽  
Hyang-Suk Park ◽  
Alexander V. Ryzhkov ◽  
Heather D. Reeves
Keyword(s):  
Numerical Models ◽  
Radar Data ◽  
Storm Event ◽  
Model Output ◽  
Polarimetric Radar ◽  
Radar Observations ◽  
Precipitation Type ◽  
Microphysical Processes ◽  
Using Data

AbstractA new hydrometeor classification algorithm that combines thermodynamic output from the Rapid Update Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely solely on polarimetric radar observations by using thermodynamic information to help to diagnose microphysical processes (such as melting or refreezing) that might occur aloft. This added information is especially important for transitional weather events for which past studies have shown radar-only techniques to be deficient. The algorithm first uses vertical profiles of wet-bulb temperature derived from the RUC model output to provide a background precipitation classification type. According to a set of empirical rules, polarimetric radar data are then used to refine precipitation-type categories when the observations are found to be inconsistent with the background classification. Using data from the polarimetric KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman, Oklahoma, the algorithm is tested on a transitional winter-storm event that produced a combination of rain, freezing rain, ice pellets, and snow as it passed over central Oklahoma on 30 November 2006. Examples are presented in which the presence of a radar bright band (suggesting an elevated warm layer) is observed immediately above a background classification of dry snow (suggesting the absence of an elevated warm layer in the model output). Overall, the results demonstrate the potential benefits of combining polarimetric radar data with thermodynamic information from numerical models, with model output providing widespread coverage and polarimetric radar data providing an observation-based modification of the derived precipitation type at closer ranges.

A Parameterization of the Microphysical Processes Forming Many Types of Winter Precipitation

2010 ◽  
Vol 67 (5) ◽  
pp. 1492-1508 ◽  
Author(s):  
Julie M. Thériault ◽  
Ronald E. Stewart
Keyword(s):  
Liquid Fraction ◽  
Winter Precipitation ◽  
The Other ◽  
Mass Content ◽  
Microphysics Scheme ◽  
Winter Storms ◽  
Precipitation Characteristics ◽  
Wet Snow ◽  
Precipitation Type ◽  
Microphysical Processes

Abstract Several types of precipitation, such as freezing rain, ice pellets, and wet snow, are commonly observed during winter storms. The objective of this study is to better understand the formation of these winter precipitation types. To address this issue, detailed melting and refreezing of precipitation was added onto an existing bulk microphysics scheme. These modifications allow the formation of mixed-phase particles and these particles in turn lead to, or affect, the formation of many of the other types of precipitation. The precipitation type characteristics, such as the mass content, liquid fraction, and threshold diameters formed during a storm over St John’s, Newfoundland, Canada, are studied and compared with observations. Many of these features were reproduced by the model. Sensitivity experiments with the model were carried out to examine the dependence of precipitation characteristics in this event on thresholds of particle evolution in the new parameterization.

scholarly journals Investigation of the Effects of Anthropogenic Pollution on Typhoon Precipitation and Microphysical Processes Using WRF-Chem

2016 ◽  
Vol 73 (4) ◽  
pp. 1593-1610 ◽  
Author(s):  
Baolin Jiang ◽  
Bo Huang ◽  
Wenshi Lin ◽  
Suishan Xu
Keyword(s):  
Anthropogenic Pollution ◽  
Cloud Water ◽  
Precipitation Rate ◽  
Convective Precipitation ◽  
Weather Research And Forecasting ◽  
Forecasting Model ◽  
Anthropogenic Aerosols ◽  
Stratiform Precipitation ◽  
Precipitation Type ◽  
Microphysical Processes

Abstract Taking Typhoon Usagi (2013) as an example, this study used the Weather Research and Forecasting Model with Chemistry to investigate the influence of anthropogenic aerosols on typhoons. Three simulations (CTL, CLEAN, EXTREME) were designed according to the emission intensity of the anthropogenic pollution. The results showed that although anthropogenic pollution did not demonstrate clear influence on the track and strength of the typhoon, it clearly changed the precipitation, distribution of water hydrometeors, and microphysical processes. In the CLEAN experiment, the precipitation rate declined because cloud water collected by the rain decreased. Similarly, the precipitation rate decreased in the EXTREME experiment, because the autoconversion of cloud water to rain was restrained. Regarding precipitation type, the rate of stratiform precipitation in both the CLEAN and the EXTREME simulations was suppressed because the ice-phase microphysical processes weakened. Compared with the CTL run, the rate of stratiform precipitation at the periphery of the typhoon was reduced by about 28% in both the CLEAN and the EXTREME simulations. Moreover, the rate of convective precipitation within 140–160 km of the center of the typhoon in the EXTREME experiment was about 33% greater than in the CTL simulation. This increase was triggered by new convection at the periphery in the EXTREME simulation related to cloud water reevaporation. Finally, compared with the CTL experiment, the peaks of both convective and mixed precipitation in the CLEAN and EXTREME experiments shifted 10 km toward the typhoon periphery.

A Polarimetric and Microphysical Investigation of the Northeast Blizzard of 8–9 February 2013

2014 ◽  
Vol 29 (6) ◽  
pp. 1271-1294 ◽  
Author(s):  
Erica M. Griffin ◽  
Terry J. Schuur ◽  
Alexander V. Ryzhkov ◽  
Heather D. Reeves ◽  
Joseph C. Picca
Keyword(s):  
New York ◽  
Transition Line ◽  
Model Output ◽  
Heavy Snowfall ◽  
Weather Event ◽  
Surface Precipitation ◽  
Wet Snow ◽  
Precipitation Type ◽  
Radar Measurements ◽  
Microphysical Processes

Abstract On 8–9 February 2013, the northeastern United States experienced a historic winter weather event ranking among the top five worst blizzards in the region. Heavy snowfall and blizzard conditions occurred from northern New Jersey, inland to New York, and northward through Maine. Storm-total snow accumulations of 30–61 cm were common, with maximum accumulations up to 102 cm and snowfall rates exceeding 15 cm h−1. Dual-polarization radar measurements collected for this winter event provide valuable insights into storm microphysical processes. In this study, polarimetric data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) in Upton, New York (KOKX), are investigated alongside thermodynamic analyses from the 13-km Rapid Refresh model and surface precipitation type observations from both Meteorological Phenomena Identification Near the Ground (mPING) and the National Weather Service (NWS) Forecast Office in Upton, New York, for interpretation of polarimetric signatures. The storm exhibited unique polarimetric signatures, some of which have never before been documented for a winter system. Reflectivity values were unusually large, reaching magnitudes >50 dBZ in shallow regions of heavy wet snow near the surface. The 0°C transition line was exceptionally distinct in the polarimetric imagery, providing detail that was often unmatched by the numerical model output. Other features include differential attenuation of magnitudes typical of melting hail, depolarization streaks that provide evidence of electrification, nonuniform beamfilling, a “snow flare” signature, and localized downward excursions of the melting-layer bright band collocated with observed transitions in surface precipitation types. In agreement with previous studies, widespread elevated depositional growth layers, located at temperatures near the model-predicted −15°C isotherm, appear to be correlated with increased snowfall and large reflectivity factors ZH near the surface.

Mapping the Precipitation Type Distribution Over the Contiguous United States Using NOAA/NSSL National Multi-Sensor Mosaic QPE

2015 ◽  
Vol 53 (8) ◽  
pp. 4434-4443 ◽  
Author(s):  
Sheng Chen ◽  
Jian Zhang ◽  
Esther Mullens ◽  
Yang Hong ◽  
Ali Behrangi ◽  
...  
Keyword(s):  
United States ◽  
Type Distribution ◽  
Precipitation Type

Perceptual Characteristics of Consonant Production in Apraxia of Speech and Aphasia

2019 ◽  
Vol 28 (4) ◽  
pp. 1411-1431 ◽  
Author(s):  
Lauren Bislick ◽  
William D. Hula
Keyword(s):  
Error Rate ◽  
Error Rates ◽  
Group Differences ◽  
Diagnostic Process ◽  
Apraxia Of Speech ◽  
Contextual Variables ◽  
Error Type ◽  
Type Distribution ◽  
Phonetic Features ◽  
Syllable Position

Purpose This retrospective analysis examined group differences in error rate across 4 contextual variables (clusters vs. singletons, syllable position, number of syllables, and articulatory phonetic features) in adults with apraxia of speech (AOS) and adults with aphasia only. Group differences in the distribution of error type across contextual variables were also examined. Method Ten individuals with acquired AOS and aphasia and 11 individuals with aphasia participated in this study. In the context of a 2-group experimental design, the influence of 4 contextual variables on error rate and error type distribution was examined via repetition of 29 multisyllabic words. Error rates were analyzed using Bayesian methods, whereas distribution of error type was examined via descriptive statistics. Results There were 4 findings of robust differences between the 2 groups. These differences were found for syllable position, number of syllables, manner of articulation, and voicing. Group differences were less robust for clusters versus singletons and place of articulation. Results of error type distribution show a high proportion of distortion and substitution errors in speakers with AOS and a high proportion of substitution and omission errors in speakers with aphasia. Conclusion Findings add to the continued effort to improve the understanding and assessment of AOS and aphasia. Several contextual variables more consistently influenced breakdown in participants with AOS compared to participants with aphasia and should be considered during the diagnostic process. Supplemental Material https://doi.org/10.23641/asha.9701690

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