A completely new nonhydrostatic model system known as the Advanced Regional Prediction System (ARPS) has been developed in recent years at the Center for Analysis and Prediction of Storms (CAPS) at the University of Oklahoma. The ARPS is designed from the beginning to serve as an effective tool for basic and applied research and as a system suitable for explicit prediction of convective storms as well as weather systems at other scales. The ARPS includes its own data ingest, quality control and objective analysis packages, a data assimilation system which includes single-Doppler velocity and thermodynamic retrieval algorithms, the forward prediction component, and a self-contained post-processing, diagnostic and verification package. The forward prediction component of the ARPS is a three-dimensional, nonhydrostatic compressible model formulated in generalized terrain-following coordinates. Minimum approximations are made to the original governing equations. The split-explicit scheme is used to integrate the sound-wave containing equations, which allows the horizontal domain-decomposition strategy to be efficiently implemented for distributed-memory massively parallel computers. The model performs equally well on conventional shared-memory scalar and vector processors. The model employs advanced numerical techniques, including monotonic advection schemes for scalar transport and variance-conserving fourth-order advection for other variables. The model also includes state-of-the-art physics parameterization schemes that are important for explicit prediction of convective storms as well as the prediction of flows at larger scales. Unique to this system are the consistent code styling maintained for the entire model system and thorough internal documentation. Modern software engineering practices are employed to ensure that the system is modular, extensible and easy to use. The system has been undergoing real-time prediction tests at the synoptic through storm scales in the past several years over the continental United States as well as in part of Asia, some of which included retrieved Doppler radar data and hydrometeor types in the initial condition. As the first of a two-part paper series, we describe herein the dynamic and numerical framework of the model, together with the subgrid-scale turbulence and the PBL parameterization. The model dynamic and numerical framework is then verified using idealized and realistic mountain flow cases and an idealized density current. Other physics parameterization schemes will be described in Part II, which is followed by verification against observational data of the coupled soil-vegetation model, surface layer fluxes and the PBL parameterization. Applications of the model to the simulation of an observed supercell storm and to the prediction of a real case are also found in Part II. In the latter case, a long-lasting squall line developed and propagated across the eastern part of the United States following a historical number of tornado outbreak in the state of Arkansas.

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The Advanced Regional Prediction System (ARPS) – A multi-scale nonhydrostatic atmospheric simulation and prediction model. Part I: Model dynamics and verification

An explicit microphysical parametrization including ice physics was developed for use in the NCAR/Penn State Mesoscale Model Version 5 (MM5). This scheme includes three options of increasing complexity to represent the hydrometeor species. The scheme is evaluated by comparing model simulations with two well observed winter storms that occurred during the Winter Icing and Storms Project. The evaluation focused on the prediction of supercooled liquid water (SLW), which is of particular importance to aircraft icing. The intercomparisons showed that:



1
The double-moment microphysical scheme, in which both ice mixing ratios and number concentrations were predicted, performed best, with close agreement to the observed fields.

2
The single-moment schemes, in which the mixing ratio of ice species are predicted and number concentration specified, performed reasonably well if a diagnostic equation for No, s, the Y-intercept of the assumed exponential snow distribution, is allowed to vary with snow mixing ratio.

3
Accurate microphysical simulations of SLW in shallow upslope clouds and cyclonic storms required accurate simulations of the kinematic and thermodynamic structure and evolution of the storms.





Though the two storms were dynamically different, the SLW formed through a balance of the condensational growth of cloud water and the depletion of cloud water by deposition and riming of snow and/or graupel for both storms. The results of this study suggest that accurate prediction of SLW over limited areas of the country may be possible using the current microphysical parametrization and high-resolution grids (δχ <10 km).

Explicit forecasting of supercooled liquid water in winter storms using the MM5 mesoscale model

Precipitation is a key link in the global water cycle and a proxy for changing climate; therefore, proper assessment of the urban envi- ronment's impact on precipitation (land use, aerosols, thermal properties) will be increasingly important in ongoing climate diagnostics and prediction, Glob- al Water and Energy Cycle (GWEC) analysis and modeling, weather forecast- ing, freshwater resource management, urban planning-design, and land- atmosphere-ocean interface processes. These facts are particularly critical if current projections for global urban growth are accurate. The goal of this paper is to provide a concise review of recent (1990-present) studies related to how the urban environment affects precipitation. In addition to providing a synopsis of current work, recent findings are placed in context with historical investigations such as Metropolitan Meteorological Experiment (METROMEX) studies. Both observational and modeling studies of urban- induced rainfall are discussed. Additionally, a discussion of the relative roles of urban dynamic and microphysical (e.g., aerosol) processes is presented. The paper closes with a set of recommendations for what observations and capa- bilities are needed in the future to advance our understanding of the processes.

/pdf/a-review-of-current-investigations-of-urban-induced-rainfall-2wrneu2hp1.pdf

A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future

Approaches to study Urban Heat Island – Abilities and limitations

A high-resolution (3-km horizontal grid spacing) near-cloud-resolving numerical simulation of the formation of Hurricane Diana (1984) is used to examine the contribution of deep convective processes to tropical cyclone formation. This study is focused on the 3-km horizontal grid spacing simulation because this simulation was previously found to furnish an accurate forecast of the later stages of the observed storm life cycle. The numerical simulation reveals the presence of vortical hot towers, or cores of deep cumulonimbus convection possessing strong vertical vorticity, that arise from buoyancy-induced stretching of local absolute vertical vorticity in a vorticity-rich prehurricane environment. At near-cloud-resolving scales, these vortical hot towers are the preferred mode of convection. They are demonstrated to be the most important influence to the formation of the tropical storm via a two-stage evolutionary process: (i) preconditioning of the local environment via diabatic production of mul...

https://opensky.ucar.edu:/islandora/object/articles%3A17604/datastream/PDF/view

The Role of “Vortical” Hot Towers in the Formation of Tropical Cyclone Diana (1984)

In anticipation of computers that will be able to run weather forecasting models on very fine grids fast enough for real-time purposes, an algorithm for representing water phase change and precipitation processes was developed. The design criteria guiding this development are sufficiency (i.e., providing the required services), computational efficiency, and compatibility within four-dimensional data assimilation systems. The implication of the last criterion is that the model's moisture variables need to be consistent with observable or inferable cloud properties. The algorithm is compared with a well-documented research microphysics algorithm in terms of computing efficiency and agreement with observations. The weather forecasting model runs much faster using the new package instead of the research algorithm. The agreement between the new algorithm and the research algorithm is much better than the agreement between the observations and the results from either algorithm, which suggests that erro...

An explicit cloud physics parameterization for operational numerical weather prediction

Seven familiar stability indices were computed from sounding data for each of 83 days of a convection forecasting experiment conducted during the summer of 1985 in northeast Colorado. Observations of convectively driven weather events were collected; the values of the indices were compared against this dataset to examine their performance as predictors of severe weather (large hail, tornadoes, high wind) and significant weather (nonsevere but important from an economic or public safety standpoint). The results of the analysis are Benchmark values of the indices that give their typical magnitudes on active days versus quiescent days. These values, compared with those computed in other regions, illustrate the potential fallacy of interpreting the indices in the absence of analogous region-specific reference statistics. Rankings that determine which indices worked best in this experiment. The highest ranked indices were the SWEAT index for severe weather and buoyancy for significant weather. Interes...

Relationships of Several Stability Indices to Convective Weather Events in Northeast Colorado

An automated procedure is developed for detecting and forecasting atmospheric conditions conductive to aircraft icing over the continental United States. The procedure uses gridded output from the Nested-Grid Model, and is based on the manual techniques currently in use at the National Aviation Weather Advisory Unit in Kansas City, Missouri. Verification of the procedure suggests forecasting performance on par with the human forecasters. Unfortunately, efforts at more-rigorous performance analysis are hindered by the inadequacies of the verification database, which consists of pilots’ subjective reports of airframe ice buildup. In general, no-ice conditions are not reported. The physics of aircraft icing are reviewed, and the current manual techniques are discussed. The automated procedure provides an infrastructure for implementing incremental improvements in the algorithm as observations and numerical models improve.

Toward the Improvement of Aircraft-Icing Forecasts for the Continental United States

A set of microphysics equations is scaled based on the convective length and velocity scales. Comparisons are made among the dynamical transport and various microphysical processes. From the scaling analysis, it becomes apparent which parameterized microphysical processes present off-scaled influences in the integration of the set of microphysics equations. The variabilities of the parameterized microphysical processes are also studied using the approach of a controlled parameter space. Given macroscopic dynamic and thermodynamic conditions in different regions of convective storms, it is possible to analyze and compare vertical profiles of these processes. Bulk diabatic heating profiles for a cumulus convective updraft and downdraft are also derived from this analysis. From the two different angles, the scale analysis and the controlled-parameter space approach can both provide an insight into and an understanding of microphysics parameterizations.

Scaling the microphysics equations and analyzing the variability of hydrometeor production rates in a controlled parameter space

Diabatic initialization of cloud-resolving forecast models such as MM5, RAMS, ARPS, and WRF allows these models to prognose the future of precipitating cloud systems such as snowstorms and thunderstorms that are present at the initial time. This is a solution to one of the most long-standing problems in NWP: the 1to 3-h spin-up of cloud systems caused by the use of traditional dry initialization.

Paul Schultz

Papers

An explicit cloud physics parameterization for operational numerical weather prediction

Relationships of Several Stability Indices to Convective Weather Events in Northeast Colorado

Toward the Improvement of Aircraft-Icing Forecasts for the Continental United States

Scaling the microphysics equations and analyzing the variability of hydrometeor production rates in a controlled parameter space

The use of three-dimensional analyses of cloud attributes for diabatic initialization of mesoscale models