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Dive into the research topics where Gregory Thompson is active.

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Featured researches published by Gregory Thompson.


Monthly Weather Review | 2008

Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part II: Implementation of a New Snow Parameterization

Gregory Thompson; P Aul R. Field; R Oy M. Rasmussen; William D. Hall

A new bulk microphysical parameterization (BMP) has been developed for use with the Weather Research and Forecasting (WRF) Model or other mesoscale models. As compared with earlier single-moment BMPs, the new scheme incorporates a large number of improvements to both physical processes and computer coding, and it employs many techniques found in far more sophisticated spectral/bin schemes using lookup tables. Unlike any other BMP, the assumed snow size distribution depends on both ice water content and temperature and is represented as a sum of exponential and gamma distributions. Furthermore, snow assumes a nonspherical shape with a bulk density that varies inversely with diameter as found in observations and in contrast to nearly all other BMPs that assume spherical snow with constant density. The new scheme’s snow category was readily modified to match previous research in sensitivity experiments designed to test the sphericity and distribution shape characteristics. From analysis of four idealized sensitivity experiments, it was determined that the sphericity and constant density assumptions play a major role in producing supercooled liquid water whereas the assumed distribution shape plays a lesser, but nonnegligible, role. Further testing using numerous case studies and comparing model results with in situ and other observations confirmed the results of the idealized experiments and are briefly mentioned herein, but more detailed, microphysical comparisons with observations are found in a companion paper in this series (Part III, forthcoming).


Monthly Weather Review | 2009

Impact of Cloud Microphysics on the Development of Trailing Stratiform Precipitation in a Simulated Squall Line: Comparison of One- and Two-Moment Schemes

Hugh Morrison; Gregory Thompson; V. Tatarskii

A new two-moment cloud microphysics scheme predicting the mixing ratios and number concentrations of five species (i.e., cloud droplets, cloud ice, snow, rain, and graupel) has been implemented into the Weather Research and Forecasting model (WRF). This scheme is used to investigate the formation and evolution of trailing stratiform precipitation in an idealized two-dimensional squall line. Results are compared to those using a one-moment version of the scheme that predicts only the mixing ratios of the species, and diagnoses the number concentrations from the specified size distribution intercept parameter and predicted mixing ratio. The overall structure of the storm is similar using either the one- or two-moment schemes, although there are notable differences. The two-moment (2-M) scheme produces a widespread region of trailing stratiform precipitation within several hours of the storm formation. In contrast, there is negligible trailing stratiform precipitation using the one-moment (1-M) scheme. The primary reason for this difference are reduced rain evaporation rates in 2-M compared to 1-M in the trailing stratiform region, leading directly to greater rain mixing ratios and surface rainfall rates. Second, increased rain evaporation rates in 2-M compared to 1-M in the convective region at midlevels result in weaker convective updraft cells and increased midlevel detrainment and flux of positively buoyant air from the convective into the stratiform region. This flux is in turn associated with a stronger mesoscale updraft in the stratiform region and enhanced ice growth rates. The reduced (increased) rates of rain evaporation in the stratiform (convective) regions in 2-M are associated with differences in the predicted rain size distribution intercept parameter (which was specified as a constant in 1-M) between the two regions. This variability is consistent with surface disdrometer measurements in previous studies that show a rapid decrease of the rain intercept parameter during the transition from convective to stratiform rainfall.


Monthly Weather Review | 2004

Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part I: Description and Sensitivity Analysis

Gregory Thompson; Roy Rasmussen; Kevin W. Manning

Abstract This study evaluates the sensitivity of winter precipitation to numerous aspects of a bulk, mixed-phase microphysical parameterization found in three widely used mesoscale models [the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), the Rapid Update Cycle (RUC), and the Weather Research and Forecast (WRF) model]. Sensitivities of the microphysics to primary ice initiation, autoconversion, cloud condensation nuclei (CCN) spectra, treatment of graupel, and parameters controlling the snow and rain size distributions are tested. The sensitivity tests are performed by simulating various cloud depths (with different cloud-top temperatures) using flow over an idealized two-dimensional mountain. The height and width of the two-dimensional barrier are designed to reproduce an updraft pattern with extent and magnitude consistent with documented freezing-drizzle cases. By increasing the moisture profile to saturation at low temperatures, a deep, ...


Bulletin of the American Meteorological Society | 2003

Improvement of Microphysical Parameterization through Observational Verification Experiment

Mark T. Stoelinga; Peter V. Hobbs; Clifford F. Mass; John D. Locatelli; Brian A. Colle; Robert A. Houze; Arthur L. Rangno; Nicholas A. Bond; Bradley F. Smull; Roy Rasmussen; Gregory Thompson; Bradley R. Colman

Abstract Despite continual increases in numerical model resolution and significant improvements in the forecasting of many meteorological parameters, progress in quantitative precipitation forecasting (QPF) has been slow. This is attributable in part to deficiencies in the bulk microphysical parameterization (BMP) schemes used in mesoscale models to simulate cloud and precipitation processes. These deficiencies have become more apparent as model resolution has increased. To address these problems requires comprehensive data that can be used to isolate errors in QPF due to BMP schemes from those due to other sources. These same data can then be used to evaluate and improve the microphysical processes and hydrometeor fields simulated by BMP schemes. In response to the need for such data, a group of researchers is collaborating on a study titled the Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE). IMPROVE has included two field campaigns carried out in th...


Journal of the Atmospheric Sciences | 2014

A Study of Aerosol Impacts on Clouds and Precipitation Development in a Large Winter Cyclone

Gregory Thompson; Trude Eidhammer

AbstractAerosols influence cloud and precipitation development in complex ways due to myriad feedbacks at a variety of scales from individual clouds through entire storm systems. This paper describes the implementation, testing, and results of a newly modified bulk microphysical parameterization with explicit cloud droplet nucleation and ice activation by aerosols. Idealized tests and a high-resolution, convection-permitting, continental-scale, 72-h simulation with five sensitivity experiments showed that increased aerosol number concentration results in more numerous cloud droplets of overall smaller size and delays precipitation development. Furthermore, the smaller droplet sizes cause the expected increased cloud albedo effect and more subtle longwave radiation effects. Although increased aerosols generally hindered the warm-rain processes, regions of mixed-phase clouds were impacted in slightly unexpected ways with more precipitation falling north of a synoptic-scale warm front. Aerosol impacts to reg...


Journal of Climate | 2012

A comparison of statistical and dynamical downscaling of winter precipitation over complex terrain

Ethan D. Gutmann; Roy Rasmussen; Changhai Liu; Kyoko Ikeda; David J. Gochis; Martyn P. Clark; Jimy Dudhia; Gregory Thompson

AbstractStatistical downscaling is widely used to improve spatial and/or temporal distributions of meteorological variables from regional and global climate models. This downscaling is important because climate models are spatially coarse (50–200 km) and often misrepresent extremes in important meteorological variables, such as temperature and precipitation. However, these downscaling methods rely on current estimates of the spatial distributions of these variables and largely assume that the small-scale spatial distribution will not change significantly in a modified climate. In this study the authors compare data typically used to derive spatial distributions of precipitation [Parameter-Elevation Regressions on Independent Slopes Model (PRISM)] to a high-resolution (2 km) weather model [Weather Research and Forecasting model (WRF)] under the current climate in the mountains of Colorado. It is shown that there are regions of significant difference in November–May precipitation totals (>300 mm) between th...


Monthly Weather Review | 2011

High-Resolution Simulations of Wintertime Precipitation in the Colorado Headwaters Region: Sensitivity to Physics Parameterizations

Changhai Liu; Kyoko Ikeda; Gregory Thompson; Roy Rasmussen; Jimy Dudhia

AbstractAn 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 surfa...


Journal of the Atmospheric Sciences | 2015

Parameterization of Cloud Microphysics Based on the Prediction of Bulk Ice Particle Properties. Part II: Case Study Comparisons with Observations and Other Schemes

Hugh Morrison; Jason A. Milbrandt; George H. Bryan; Kyoko Ikeda; Sarah A. Tessendorf; Gregory Thompson

AbstractA new microphysics scheme has been developed based on the prediction of bulk particle properties for a single ice-phase category, in contrast to the traditional approach of separating ice into various predefined species (e.g., cloud ice, snow, and graupel). In this paper, the new predicted particle properties (P3) scheme, described in Part I of this series, is tested in three-dimensional simulations using the Weather Research and Forecasting (WRF) Model for two contrasting well-observed cases: a midlatitude squall line and winter orographic precipitation. Results are also compared with simulations using other schemes in WRF. Simulations with P3 can produce a wide variety of particle characteristics despite having only one free ice-phase category. For the squall line, it produces dense, fast-falling, hail-like ice near convective updraft cores and lower-density, slower-falling ice elsewhere. Sensitivity tests show that this is critical for simulating high precipitation rates observed along the lead...


Bulletin of the American Meteorological Society | 1994

Real-Time Mesoscale Prediction on Workstations

William R. Cotton; Gregory Thompson; Paul W. Mielke

Abstract Experience in performing real-time mesoscale numerical prediction forecasts using the Regional Atmospheric Modeling System (RAMS) over Colorado for a winter season on high-performance workstations is summarized. Performance evaluation is done for specific case studies and, statistically, for the entire winter season. RAMS forecasts are also compared with nested grid model forecasts. In addition, RAMS precipitation forecasts with a simple “dump bucket” scheme are compared with explicit, bulk microphysics parameterization schemes. The potential applications and political/ social problems of having a readily accessible, real-time mesoscale forecasting capability on low-cost, high-performance workstations is discussed.


Weather and Forecasting | 1997

Intercomparison of In-Flight Icing Algorithms. Part II: Statistical Verification Results

Barbara G. Brown; Gregory Thompson; Roelof T. Bruintjes; Randy Bullock; Tressa L. Kane

Abstract Recent research to improve forecasts of in-flight icing conditions has involved the development of algorithms to apply to the output of numerical weather prediction models. The abilities of several of these algorithms to predict icing conditions, as verified by pilot reports (PIREPs), are compared for two numerical weather prediction models (Eta and the Mesoscale Analysis and Prediction System) for the Winter Icing and Storms Program 1994 (WISP94) time period (25 January–25 March 1994). Algorithms included in the comparison were developed by the National Aviation Weather Advisory Unit [NAWAU, now the Aviation Weather Center (AWC)], the National Center for Atmospheric Research’s Research Applications Program (RAP), and the U.S. Air Force. Operational icing forecasts (AIRMETs) issued by NAWAU for the same time period are evaluated to provide a standard of comparison. The capabilities of the Eta Model’s explicit cloud liquid water estimates for identifying icing regions are also evaluated and compar...

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Roy Rasmussen

National Center for Atmospheric Research

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Kyoko Ikeda

National Center for Atmospheric Research

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Hugh Morrison

National Center for Atmospheric Research

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Changhai Liu

National Center for Atmospheric Research

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Jimy Dudhia

National Center for Atmospheric Research

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Trude Eidhammer

National Center for Atmospheric Research

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Lulin Xue

National Center for Atmospheric Research

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Marcia K. Politovich

National Center for Atmospheric Research

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Sarah A. Tessendorf

National Center for Atmospheric Research

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