Michael P. Meyers

New primary ice-nucleation parameterizations in an explicit cloud model

Abstract Two new primary ice-nucleation parameterizations are examined in the Regional Atmospheric Modeling System (RAMS) cloud model via sensitivity tests on a wintertime precipitation event in the Sierra Nevada region. A model combining the effects of deposition and condensation-freezing nucleation is formulated based on data obtained from continuous-flow diffusion chambers. The data indicate an exponential variation of ice-nuclei concentrations with ice supersaturation reasonably independent of temperatures between −7° and −20°C. Predicted ice concentrations from these measurements exceed values predicted by the widely used temperatures dependent Fletcher approximation by as much as one order of magnitude at temperatures warmer than −20°C. A contact-freezing nucleation model is also formulated based on laboratory data gathered by various authors using techniques that isolated this nucleation mode. Predicted contact nuclei concentrations based on the newer measurements are as much as three orders of mag...

New RAMS cloud microphysics parameterization part I: the single-moment scheme

A new cloud microphysical parameterization is described. Features of this new scheme include: the use of generalized gamma distributions as the basis function for all hydrometeor species; the use of a heat budget equation for hydrometeor classes, allowing heat storage and mixed phase hydrometears; partitioning hydrometeors into seven classes (including separate graupel and hail categories) ; the use of stochastic collection rather than continuous accretion approximations and extension of the ice nucleation scheme to include homogeneous nucleation of ice from haze particles and cloud droplets. The versatility and credibility of the new scheme is explored, using sensitivity experiments for a simple two-dimensional convective cloud simulation.

New RAMS cloud microphysics parameterization. Part II: The two-moment scheme

Abstract This paper is the second in a series of articles describing the new microphysics scheme in the Regional Atmospheric Modeling System (RAMS). In this part, a new two-moment microphysical parameterization is described. The proposed scheme predicts the mixing ratio and number concentration of rain, pristine ice crystals, snow, aggregates, graupel and hail. The general gamma distribution is the basis function used for hydrometeor size in each category. Additional features include: use of stochastic collection for number concentration tendency; breakup of rain droplets formulated into the collection efficiency; diagnosis of ice crystal habit dependent on temperature and saturation; evaporation and melting of each species assuming that the smallest particles completely disappear first; and more complex shedding formulations which take into account the amount of water mass on the coalesced hydrometeor. Preliminary sensitivity testing of the new microphysical scheme in an idealized convective simulation shows that the two-moment prediction scheme allows more flexibility of the size distribution enabling the mean diameter to evolve in contrast to the one-moment scheme. Sensitivity to the prescribed input parameters such as cloud droplet concentrations and the shape parameter v is demonstrated in the model results.

Parameterization and Impact of Ice initiation Processes Relevant to Numerical Model Simulations of Cirrus Clouds

Abstract An effort to improve descriptions of ice initiation processes of relevance to cirrus clouds for use in regional-scale numerical cloud models with bulk microphysical schemes is described. This is approached by deriving practical parameterizations of the process of ice initiation by homogeneous freezing of cloud and haze (CCN) particles in the atmosphere. The homogeneous freezing formulations may be used with generalized distributions of cloud water and CCN (pure ammonium sulfate assumed). Numerical cloud model sensitivity experiments were made using a microphysical parcel model and a mososcale cloud model to investigate the impact of the homogeneous freezing process and heterogeneous ice nucleation processes on the formation and makeup of cirrus clouds. These studies point out the critical nature of assumptions made regarding the abundance and character of heterogeneous ice nuclei (IN) present in the upper troposphere. Conclusions regarding the sources of ice crystals in cirrus clouds and the pote...

Parameterization of Ice Crystal Conversion Processes Due to Vapor Deposition for Mesoscale Models Using Double-Moment Basis Functions. Part I: Basic Formulation and Parcel Model Results

Abstract Observational data collected during the FIRE II experiment showing the existence of bimodal ice spectra along with experimental evidence of the size dependence of riming are utilized in the development of a bimodal ice spectrum parameterization for use in the RAMS model. Two ice classes are defined: pristine ice and snow, each described by a separate, complete gamma distribution function. Pristine ice is small ice consisting of particles with mean sizes less than 125 µm, while snow is the large class consisting of particles greater than 125 µm. Analytical equations are formulated for the conversion between the ice classes by vapor depositional growth (sublimation). During ice subsaturated conditions, a number concentration sink is parameterized for all ice species. The performance of the parameterizations in a simple parcel model is discussed and evaluated against an explicit Lagrangian parcel microphysical model.

Evaluation of the Potential for Wintertime Quantitative Precipitation Forecasting over Mountainous Terrain with an Explicit Cloud Model. Part I: Two-Dimensional Sensitivity Experiments

Abstract A prolonged orographic precipitation event occurred over the Sierra Nevada in central California on 12–13 February 1986. This well-documented case was investigated via the nonhydrostatic version of the Colorado State University (CSU) Regional Atmospheric Modeling System (RAMS). The two-dimensional, cross-barrier simulations produced flow fields and microphysical structure, which compared well with observations. The feasibility of producing quantitative precipitation forecasts (QPF) with an explicit cloud model was also demonstrated. The experiments exhibited a profound sensitivity to the input sounding. Initializing with a sounding, which is representative of the upstream environment, was the most critical factor to the success of the simulation. The QPF was also quite sensitive to input graupel density. Decreasing the density of graupel led to increases in the overall precipitation. Sensitivities to other microphysical parameters as well as orography and dynamics were also examined.

Mesoscale Snowfall Prediction and Verification in Mountainous Terrain

Short-term forecasting of precipitation often relies on meteorological radar coverage to provide information on the intensity, extent, and motion of approaching mesoscale features. However, in significant portions of mountainous regions, radar coverage is lacking because of topographic blocking, and the absence of radar signatures in sections of the radar scan produces uncertain or even misleading information to the public and operational forecasters. In addition, echo characteristics within the radar volume scan are often influenced by the vertical extent and type of precipitation. Each of these conditions limits the opportunity for accurate snowfall prediction and studies of precipitation climatology. To improve both short-term forecasting and postevent verification studies, much greater use can be made of specifically sited surface observations, tailored graphical output from mesoscale models, satellite remote sensing, and case study knowledge of local topographic influences. In this paper, methods to support snowfall forecasts and verification in radar-limited mountainous terrain are demonstrated that include matching the output parameters and graphics from high-resolution mesoscale models to surface mesonets and snowfall observations, analysis of continuous and event-based measurements of snow density, application of multispectral satellite data for verification and trend analysis, and characterization of orographic influences in different winter storm scenarios. The advantages of improved wintertime quantitative precipitation forecasting (QPF) in mountain regions include public safety responsibilities that are critical to National Weather Service (NWS) operations, and are relevant to any mountainous region with radar scan limitations or during periods of radar data outages.

A Rocky Mountain Storm. Part II: The Forest Blowdown over the West Slope of the Northern Colorado Mountains—Observations, Analysis, and Modeling

Abstract A devastating winter storm affected the Rocky Mountain states over the 3-day period of 24–26 October 1997. Blizzard conditions persisted over the foothills and adjoining plains from Wyoming to southern New Mexico, with maximum total snowfall amounts near 1.5 m. (Part I of this two-part paper describes the observations and modeling of this blizzard event.) During the morning of 25 October 1997, wind gusts in excess of 50 m s−1 were estimated west of the Continental Divide near Steamboat Springs in northern Colorado. These winds flattened approximately 5300 ha (13 000 acres) of old-growth forest in the Routt National Forest and Mount Zirkel Wilderness. Observations, analysis, and numerical modeling were used to examine the kinematics of this extreme event. A high-resolution, local-area model (the Regional Atmospheric Modeling System) was used to investigate the ability of a local model to capture the timing and strength of the windstorm and the aforementioned blizzard. Results indicated that a syne...

A Rocky Mountain Storm. Part I: The Blizzard—Kinematic Evolution and the Potential for High-Resolution Numerical Forecasting of Snowfall

Abstract Over the 3-day period of 24–26 October 1997, a powerful winter storm was the cause of two exceptional weather phenomena: 1) blizzard conditions from Wyoming to southern New Mexico along the Front Range of the Rocky Mountains and 2) hurricane-force winds at the surface near Steamboat Springs, Colorado, with the destruction of about 5300 ha of old-growth forest. This rare event was caused by a deep, cutoff low pressure system that provided unusually strong, deep easterly flow over the Front Range for an extended period. The event was characterized by highly variable snowfall and some very large snowfall totals; over a horizontal distance of 15 km, in some cases, snowfall varied by as much as 1.0 m, with maximum total snowfall depths near 1.5 m. Because this variability was caused, in part, by terrain effects, this work investigates the capability of a mesoscale model constructed in terrain-following coordinates (the Regional Atmospheric Modeling System: RAMS) to forecast small-scale (meso γ), orogr...