Jason A. Milbrandt

THE FOG REMOTE SENSING AND MODELING FIELD PROJECT

The main purpose of this work is to describe a major field project on fog and summarize the preliminary results. Three field phases of the Fog Remote Sensing and Modeling (FRAM) project were conducted over the following two regions of Canada: 1) the Center for Atmospheric Research Experiments (CARE), in Toronto, Ontario (FRAM-C), during the winter of 2005/06, and 2) Lunenburg, Nova Scotia (FRAM-L), during June 2006 and June 2007. Fog conditions observed during FRAM-C were continental in nature, while those conditions observed during FRAM-L were of marine origin. The main objectives of the project were to attain 1) a better description of fog environments, 2) the development of microphysical parameterizations for model applications, 3) the development of remote sensing methods for fog nowcasting/forecasting, 4) an understanding of issues related to instrument capabilities and improvement of the analysis, and 5) an integration of model data with observations to predict and detect fog areas and particle phas...

Comparison of Two-Moment Bulk Microphysics Schemes in Idealized Supercell Thunderstorm Simulations

AbstractIdealized three-dimensional supercell simulations were performed using the two-moment bulk microphysics schemes of Morrison and Milbrandt–Yau in the Weather Research and Forecasting (WRF) model. Despite general similarities in these schemes, the simulations were found to produce distinct differences in storm structure, precipitation, and cold pool strength. In particular, the Morrison scheme produced much higher surface precipitation rates and a stronger cold pool, especially in the early stages of storm development. A series of sensitivity experiments was conducted to identify the primary differences between the two schemes that resulted in the large discrepancies in the simulations.Different approaches in treating graupel and hail were found to be responsible for many of the key differences between the baseline simulations. The inclusion of hail in the baseline simulation using the Milbrant–Yau scheme with two rimed-ice categories (graupel and hail) had little impact, and therefore resulted in a...

Parameterization of cloud microphysics based on the prediction of bulk ice particle properties. Part I: Scheme description and idealized tests

A method for the parameterization of ice-phase microphysics is proposed and used to develop a new bulk microphysics scheme. All ice-phase particles are represented by several physical properties that evolve freely in time and space. The scheme prognoses four ice mixing ratio variables, total mass, rime mass, rime volume, and number, allowing 4 degrees of freedom for representing the particle properties using a single category. This approach represents a significant departure from traditional microphysics schemes in which ice-phase hydrometeors are partitioned into various predefined categories (e.g., cloud ice, snow, and graupel) with prescribed characteristics. The liquid-phase component of the new scheme uses a standard two-moment, twocategory approach. The proposed method and a complete description of the new predicted particle properties (P3) scheme are provided. Results from idealized model simulations of a two-dimensional squall line are presented that illustrate overall behavior of the scheme. Despite its use of a single ice-phase category, the scheme simulates a realistically wide range of particle characteristics in different regions of the squall line, consistent with observed ice particles in real squall lines. Sensitivity tests show that both the prediction of the rime mass fraction and the rime density are important for the simulation of the squall-line structure and precipitation.

Sensitivity of Idealized Squall-Line Simulations to the Level of Complexity Used in Two-Moment Bulk Microphysics Schemes

AbstractThis paper investigates the level of complexity that is needed within bulk microphysics schemes to represent the essential features associated with deep convection. To do so, the sensitivity of surface precipitation is evaluated in two-dimensional idealized squall-line simulations with respect to the level of complexity in the bulk microphysics schemes of H. Morrison et al. and of J. A. Milbrandt and M. K. Yau. Factors examined include the number of predicted moments for each of the precipitating hydrometeors, the number and nature of ice categories, and the conversion term formulations. First, it is shown that simulations of surface precipitation and cold pools are not only a two-moment representation of rain, as suggested by previous research, but also by two-moment representations for all precipitating hydrometeors. Cold pools weakened when both rain and graupel number concentrations were predicted, because size sorting led to larger graupel particles that melted into larger raindrops and cause...

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

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...

Prediction of Graupel density in a bulk microphysics scheme

AbstractA method to predict the bulk density of graupel ρg has been added to the two-moment Milbrandt–Yau bulk microphysics scheme. The simulation of graupel using the modified scheme is illustrated through idealized simulations of a mesoscale convective system using a 2D kinematic model with a prescribed flow field and different peak updraft speeds. To examine the relative impact of the various approaches to represent rimed ice, simulations were run for various graupel-only and graupel-plus-hail configurations.Because of the direct feedback of ρg to terminal fall speeds, the modified scheme produces a much different spatial distribution of graupel, with more mass concentrated in the convective region resulting in changes to the surface precipitation at all locations. With a strong updraft, the model can now produce solid precipitation at the surface in the convective region without a separate hail category. It is shown that a single rimed-ice category is capable of representing a realistically wide range...

Ice Fog in Arctic During FRAM–Ice Fog Project: Aviation and Nowcasting Applications

Ice fog and frost occur commonly (at least 26% of the time) in the northern latitudes and Arctic regions during winter at temperatures usually less than about –15°C. Ice fog is strongly related to frost formation—a major aviation hazard in the northern latitudes. In fact, it may be considered a more dangerous event than snow because of the stronger aircraft surface adhesion compared to snow particles. In the winter of 2010/11, the Fog Remote Sensing and Modeling–Ice Fog (FRAM-IF) project was organized near Yellowknife International Airport, Northwest Territories, Canada, with the main goals of advancing understanding of ice fog microphysical and visibility characteristics, and improving its prediction using forecast models and remotesensing retrievals. Approximately 40 different sensors were used to measure visibility, precipitation, ice particle spectra, vertical thermodynamic profiles, and ceiling height. Fog coverage and visibility parameters were estimated using both Geostationary Operational Environm...

Environment Canada's Experimental Numerical Weather Prediction Systems for the Vancouver 2010 Winter Olympic and Paralympic Games

The 2010 Winter Olympic and Paralympic Games took place in Vancouver, British Columbia, Canada, on 12–28 February and 12–21 March 2010, respectively. Weather forecasting presents specific challenges at the various Olympic venues, which are located in complex coastal terrain and are often characterized by tricky weather conditions, such as high winds, low visibility, and rapidly varying precipitation types and intensity. In addition to its current operational products, and in order to provide the best possible guidance and support to the Olympic Forecast Team, Environment Canada has developed several experimental numerical weather prediction systems for the games. These include 1) a regional ensemble prediction system (REPS), 2) high-resolution numerical modeling (down to 1-km horizontal grid spacing), and 3) surface modeling at the microscales (100-m grid spacing). The REPS is based on the limited-area version of the Global Environmental Multiscale model (GEM-LAM), with 20 members at 33-km horizontal grid...

An Experimental High-Resolution Forecast System During the Vancouver 2010 Winter Olympic and Paralympic Games

Environment Canada ran an experimental numerical weather prediction (NWP) system during the Vancouver 2010 Winter Olympic and Paralympic Games, consisting of nested high-resolution (down to 1-km horizontal grid-spacing) configurations of the GEM–LAM model, with improved geophysical fields, cloud microphysics and radiative transfer schemes, and several new diagnostic products such as density of falling snow, visibility, and peak wind gust strength. The performance of this experimental NWP system has been evaluated in these winter conditions over complex terrain using the enhanced mesoscale observing network in place during the Olympics. As compared to the forecasts from the operational regional 15-km GEM model, objective verification generally indicated significant added value of the higher-resolution models for near-surface meteorological variables (wind speed, air temperature, and dewpoint temperature) with the 1-km model providing the best forecast accuracy. Appreciable errors were noted in all models for the forecasts of wind direction and humidity near the surface. Subjective assessment of several cases also indicated that the experimental Olympic system was skillful at forecasting meteorological phenomena at high-resolution, both spatially and temporally, and provided enhanced guidance to the Olympic forecasters in terms of better timing of precipitation phase change, squall line passage, wind flow channeling, and visibility reduction due to fog and snow.

Simulation of an Orographic Precipitation Event during IMPROVE-2. Part II: Sensitivity to the Number of Moments in the Bulk Microphysics Scheme

Abstract This is the second in a series of papers examining the behavior of the Milbrandt–Yau multimoment bulk microphysics scheme for the simulation of the 13–14 December 2001 case of orographically enhanced precipitation observed during the second Improvement of Microphysical Parameterization through Observational Verification Experiment (IMPROVE-2) experiment. The sensitivity to the number of predicted moments of the hydrometeor size spectra in the bulk scheme was investigated. The triple-moment control simulations presented in Part I were rerun using double- and single-moment configurations of the multimoment scheme as well the single-moment Kong–Yau scheme. Comparisons of total precipitation and in-cloud hydrometeor mass contents were made between the simulations and observations, with the focus on a 2-h quasi-steady period of heavy stratiform precipitation. The double- and triple-moment simulations were similar; both had realistic precipitation fields, though generally overpredicted in quantity, and...