The Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR Scientific Divisions ; copies may be obtained on request from the Publications Office of NCAR. Designation symbols for the series include: Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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A Description of the Advanced Research WRF Version 3

: The development of the Weather Research and Forecasting (WRF) modeling system is a multiagency effort intended to provide a next-generation mesoscale forecast model and data assimilation system that will advance both the understanding and prediction of mesoscale weather and accelerate the transfer of research advances into operations. The model is being developed as a collaborative effort ort among the NCAR Mesoscale and Microscale Meteorology (MMM) Division, the National Oceanic and Atmospheric Administration's (NOAA) National Centers for Environmental Prediction (NCEP) and Forecast System Laboratory (FSL), the Department of Defense's Air Force Weather Agency (AFWA) and Naval Research Laboratory (NRL), the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma, and the Federal Aviation Administration (FAA), along with the participation of a number of university scientists. The WRF model is designed to be a flexible, state-of-the-art, portable code that is an efficient in a massively parallel computing environment. A modular single-source code is maintained that can be configured for both research and operations. It offers numerous physics options, thus tapping into the experience of the broad modeling community. Advanced data assimilation systems are being developed and tested in tandem with the model. WRF is maintained and supported as a community model to facilitate wide use, particularly for research and teaching, in the university community. It is suitable for use in a broad spectrum of applications across scales ranging from meters to thousands of kilometers. Such applications include research and operational numerical weather prediction (NWP), data assimilation and parameterized-physics research, downscaling climate simulations, driving air quality models, atmosphere-ocean coupling, and idealized simulations (e.g boundary-layer eddies, convection, baroclinic waves).

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A Description of the Advanced Research WRF Version 2

This study examines the performance of the Weather Research and Forecasting (WRF)-Single-Moment- Microphysics scheme (WSMMPs) with a revised ice-microphysics of the Hong et al. In addition to the simple (WRF Single-Moment 3-class Microphysics scheme; WSM3) and mixed-phase (WRF Single-Moment 5-class Microphysics scheme; WSM5) schemes of the Hong et al., a more complex scheme with the inclusion of graupel as another predictive variable (WRF Single-Moment 6-class Microphysics scheme; WSM6) was developed. The characteristics of the three categories of WSMMPs were examined for an idealized storm case and a heavy rainfall event over Korea. In an idealized thunderstorm simulation, the overall evolutionary features of the storm are not sensitive to the number of hydrometeors in the WSMMPs; however, the evolution of surface precipitation is significantly influenced by the complexity in microphysics. A simulation experiment for a heavy rainfall event indicated that the evolution of the simulated precipitation with the inclusion of graupel (WSM6) is similar to that from the simple (WSM3) and mixed-phase (WSM5) microphysics in a low-resolution grid; however, in a high-resolution grid, the amount of rainfall increases and the peak intensity becomes stronger as the number of hydrometeors increases.

The WRF Single-Moment 6-Class Microphysics Scheme (WSM6)

A revised approach to cloud microphysical processes in a commonly used bulk microphysics parameterization and the importance of correctly representing properties of cloud ice are discussed. Several modifications are introduced to more realistically simulate some of the ice microphysical processes. In addition to the assumption that ice nuclei number concentration is a function of temperature, a new and separate assumption is developed in which ice crystal number concentration is a function of ice amount. Related changes in ice microphysics are introduced, and the impact of sedimentation of ice crystals is also investigated. In an idealized thunderstorm simulation, the distribution of simulated clouds and precipitation is sensitive to the assumptions in microphysical processes, whereas the impact of the sedimentation of cloud ice is small. Overall, the modifications introduced to microphysical processes play a role in significantly reducing cloud ice and increasing snow at colder temperatures and ...

A Revised Approach to Ice Microphysical Processes for the Bulk Parameterization of Clouds and Precipitation

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 idea...

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

A two-dimensional, time-dependent cloud model has been used to simulate a moderate intensity thunderstorm for the High Plains region. Six forms of water substance (water vapor, cloud water, cloud ice, rain, snow and hail, i.e., graupel) are simulated. The model utilizes the “bulk water” microphysical parameterization technique to represent the precipitation fields which are all assumed to follow exponential size distribution functions. Autoconversion concepts are used to parameterize the collision-coalescence and collision-aggregation processes. Accretion processes involving the various forms of liquid and solid hydrometeors are simulated in this model. The transformation of cloud ice to snow through autoconversion (aggregation) and Bergeron process and subsequent accretional growth or aggregation to form hail are simulated. Hail is also produced by various contact mechanisms and via probabilistic freezing of raindrops. Evaporation (sublimation) is considered for all precipitation particles outsi...

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Bulk Parameterization of the Snow Field in a Cloud Model

A numerical model of a hail-bearing cumulus cloud is presented. The model is one-dimensional and time-dependent, and it employs extensive parameterization of the microphysical processes. The raindrop and hailstone size distributions are assumed to be exponential at all times. Cloud droplets are converted to raindrops according to Berry's parameterization of the autoconversion process and are accreted by the raindrops according to Kessler's formulation. Raindrops are frozen at a rate consistent with Bigg's freezing equation, and the hailstones so formed then accrete raindrops and cloud droplets. Ice crystals are not allowed by the model, and for consistency, then, it is assumed that the cloud droplets do not freeze except when accreted by hailstones at temperatures less than0C. The melting and evaporation processes are modeled, and their impact on the results is explored. The results of five test cases are presented. The sequence of cases is designed to illustrate the effects of the presence of ha...

A Numerical Model of a Hail-Bearing Cloud

The effects of precipitation on a model of cumulus cloud initiation and development over mountains are studied by numerically integrating the equations of motion, equations of conservation of water substance, and the thermodynamic energy equation. The model is two-space dimensional with a vertical wind shear in a stable, incompressible atmosphere. Heating and evaporation at the valley and mountain interact with the initial ambient flow to initiate clouds which produce shadows on the surface and cut down both heating and evaporation. The model is restricted vertically to 3.5 km and horizontally to 7.0 km. Several precipitation parameters are studied in this model. One, the critical water content determines when cloud water converts to rainwater. A second, the autoconversion rate, determines how rapidly the cloud water converts to rainwater. The third parameter determines how quickly the precipitation evaporates beneath the cloud. The rainwater first forms by autoconversion and is then increased by...

Numerical Modeling of Precipitation and Cloud Shadow Effects on Mountain-Induced Cumuli

This paper describes and compares various methods for calculating radar reflectivity factors in numerical cloud models that use bulk methods to characterize the precipitation processes. Equations sensitive to changes in the parameters of the particle size distributions are favored because they allow simulation of phenomena causing such changes. Marshall-Palmer-type functions are established to represent hailstone size distributions because the previously available distributions lead to implausibly large reflectivity factors. Simplified equations are developed for calculating reflectivity factors for both dry and wet hail. Some examples are given of the use of the various equations in numerical cloud models.

Radar Reflectivity Factor Calculations in Numerical Cloud Models Using Bulk Parameterization of Precipitation

A two-dimensional time-dependent cloud model which covers a region 19.2 km × 19.2 km in the x and z directions with 200 m grid intervals, has been used to simulate silver iodide (AgI) seeding effects on strong convective clouds. The model is a set of conservation equations for momentum, energy and mass (air and water contents). One extra conservation equation is applied to trace the seeding agent which advects and diffuses along the flow field and interacts with the supercooled cloud fields. Contact and deposition nucleation are simulated. Only inertial impact and Brownian collection are considered as possible mechanisms for contact nucleation. Most of the AgI particles work as deposition or sorption nuclei in this study. Three different soundings are tested. Most of the effort is used in testing sounding H1, from Miles City, Montana, 29 July 1975. Seeding at a different place (see H1/P1), at a different time (case H1/T1), and with different amounts of AgI (cases H1/M1 and H1/M2) are simulated. T...

Harold D. Orville

Papers

Bulk Parameterization of the Snow Field in a Cloud Model

A Numerical Model of a Hail-Bearing Cloud

Numerical Modeling of Precipitation and Cloud Shadow Effects on Mountain-Induced Cumuli

Radar Reflectivity Factor Calculations in Numerical Cloud Models Using Bulk Parameterization of Precipitation

Numerical Simulation of Ice-Phase Convective Cloud Seeding