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 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...

Numerical Simulation of Ice-Phase Convective Cloud Seeding

A recently developed Storm Electrification Model (SEM) has been used to simulate the July 19, 1981, Cooperative Convective Precipitation Experiment (CCOPE) case study cloud. This part of the investigation examines the comparison between the model results and the observations of the actual cloud with respect to its nonelectrical aspects. A timing equivalence is established between the simulation and observations based on an explosive growth phase which was both observed and modeled. This timing equivalence is used as a basis upon which the comparisons are made. The model appears to do a good job of reproducing (in both space and time) many of the observed characteristics of the cloud. These include: (1) the general cloud appearance; (2) cloud size; (3) cloud top rise rate; (4) rapid growth phase; (5) updraft structure; (6) first graupel appearance; (7) first radar echo; (8) qualitative radar range-height indicator evolution; (9) cloud decay; and (10) the location of hydrometers with respect to the updraft/-downdraft structure. Some features that are not accurately modeled are the cloud base height, the maximum liquid water content, and the time from first formation of precipitation until it reaches the ground. While the simulation is not perfect, the faithfulness of the model results to the observations is sufficient to give us confidence that the microphysical processes active in this storm are adequately represented in the model physics. Areas where model improvement is indicated are also discussed.

A numerical modeling study of a Montana thunderstorm: 2. Model results versus observations involving electrical aspects

The early, prelightning, electrification of a storm resulting from noninductive (NI) charging involving graupel, cloud ice/snow, and supercooled cloud water in a riming environment is studied using a comparative approach in a two-dimensional storm electrification model. The primary schemes examined are NI charge transfers based on the laboratory work of Takahashi [1978] and Saunders et al. [1991]. The NI mechanism, based on Takahashi's work, develops a positive dipole (positive charge above negative) and electric fields approaching 185 kV m−1 as the cloud enters the dissipating stage. Charge transfers, based on the work of Saunders and colleagues, had to be reduced in magnitude to produce electrification that is consistent with the observations. In addition, the Saunders scheme produces an initially inverted dipole (negative charge above positive) which resolves to a positive dipole in the latter part of the simulation and produces electric fields approaching 250 kV m−1. Sensitivity tests show that the NI scheme, based on Takahashi's work, is sensitive to the number concentration of ice crystals, whereas the Saunders-based scheme is much less sensitive to ice crystal numbers. The Saunders parameterization has strong positive charging of graupel at low effective liquid water content and low temperature. This positive charging can result in an unusual cloud-top charge structure when used at full value but is benign when the charging is reduced in magnitude. The charge structure resulting from the Saunders scheme is quite sensitive to the calculation of the effective water content, which determines the level of charge reversal. Both of the NI schemes are capable of producing electrification that approaches thunderstorm levels.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2000JD900532

An examination of thunderstorm‐charging mechanisms using a two‐dimensional storm electrification model

This paper is the first in a three part series describing numerical simulations of hailstorms and hailstone growth using a two-dimensional, time-dependent cloud model. In this model. cloud water, cloud ice and rain are treated via standard parameterization technique The precipitating ice field is discretized into 20 logarith-mically spaced size categories which evolve in, and interact with the time-dependent dynamic framework. Ice particles are generated by the freezing of raindrops and via a parameterization of the Bergeron process. Growth of these ice particles is based on wet and dry growth concepts applied to the continuous accretion process. The model has been used to simulate a severe supercellular hailstorm from the National Hail Research Experiment These simulations include cases assuming various microphysical configurations of the model along with simplified cloud seeding experiments The simulations indicate many areas of agreement between the model results and observation chief among th...

Richard D. Farley

Papers

Bulk Parameterization of the Snow Field in a Cloud Model

Numerical Simulation of Ice-Phase Convective Cloud Seeding

A numerical modeling study of a Montana thunderstorm: 2. Model results versus observations involving electrical aspects

An examination of thunderstorm‐charging mechanisms using a two‐dimensional storm electrification model

Numerical Modeling of Hailstorms and Hailstone Growth. Part I: Preliminary Model Verification and Sensitivity Tests