Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

This study evaluates the sensitivity of winter precipitation to numerous aspects of a bulk, mixed-phase microphysical parameterization found in three widely used mesoscale models [the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5), the Rapid Update Cycle (RUC), and the Weather Research and Forecast (WRF) model]. Sensitivities of the microphysics to primary ice initiation, autoconversion, cloud condensation nuclei (CCN) spectra, treatment of graupel, and parameters controlling the snow and rain size distributions are tested. The sensitivity tests are performed by simulating various cloud depths (with different cloud-top temperatures) using flow over an idealized two-dimensional mountain. The height and width of the two-dimensional barrier are designed to reproduce an updraft pattern with extent and magnitude consistent with documented freezing-drizzle cases. By increasing the moisture profile to saturation at low temperatures, a deep, ...

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Explicit Forecasts of Winter Precipitation Using an Improved Bulk Microphysics Scheme. Part I: Description and Sensitivity Analysis

The Rapid Refresh (RAP), an hourly updated assimilation and model forecast system, replaced the Rapid Update Cycle (RUC) as an operational regional analysis and forecast system among the suite of models at the NOAA/National Centers for Environmental Prediction (NCEP) in 2012. The need for an effective hourly updated assimilation and modeling system for the United States for situational awareness and related decision-making has continued to increase for various applications including aviation (and transportation in general), severe weather, and energy. The RAP is distinct from the previous RUC in three primary aspects: a larger geographical domain (covering North America), use of the community-based Advanced Research version of the Weather Research and Forecasting (WRF) Model (ARW) replacing the RUC forecast model, and use of the Gridpoint Statistical Interpolation analysis system (GSI) instead of the RUC three-dimensional variational data assimilation (3DVar). As part of the RAP development, modif...

A North American Hourly Assimilation and Model Forecast Cycle: The Rapid Refresh

After six years of scientific, technical developments and meteorological validation, the Application of Research to Operations at Mesoscale (AROME-France) convective-scale model became operational at Meteo-France at the end of 2008. This paper presents the main characteristics of this new numerical weather prediction system: the nonhydrostatic dynamical model core, detailed moist physics, and the as- sociated three-dimensional variational data assimilation (3D-Var) scheme. Dynamics options settings and variables are explained. The physical parameterizations are depicted as well as their mutual interactions. The scale-specific features of the 3D-Var scheme are shown. The performance of the forecast model is evaluated using objective scores and case studies that highlight its benefits and weaknesses.

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The AROME-France Convective-Scale Operational Model

A sample of 413 soundings in close proximity to tornadic and nontornadic supercells is examined. The soundings were obtained from hourly analyses generated by the 40-km Rapid Update Cycle-2 (RUC-2) analysis and forecast system. A comparison of 149 observed soundings and collocated RUC-2 soundings in regional supercell environments reveals that the RUC-2 model analyses were reasonably accurate through much of the troposphere. The largest error tendencies were in temperatures and mixing ratios near the surface, primarily in 1-h forecast soundings immediately prior to the standard rawinsonde launches around 1200 and 0000 UTC. Overall, the RUC-2 analysis soundings appear to be a reasonable proxy for observed soundings in supercell environments. Thermodynamic and vertical wind shear parameters derived from RUC-2 proximity soundings are evaluated for the following supercell and storm subsets: significantly tornadic supercells (54 soundings), weakly tornadic supercells (144 soundings), nontornadic supercells (215 soundings), and discrete nonsupercell storms (75 soundings). Findings presented herein are then compared to results from previous and ongoing proximity soundings studies. Most significantly, proximity soundings presented here reinforce the findings of previous studies in that vertical shear and moisture within 1 km of the ground can discriminate between nontornadic supercells and supercells producing tornadoes with F2 or greater damage. Parameters that combine measures of buoyancy, vertical shear, and low-level moisture show the strongest ability to discriminate between supercell classes.

/pdf/close-proximity-soundings-within-supercell-environments-1bx6enprf4.pdf

Close Proximity Soundings within Supercell Environments Obtained from the Rapid Update Cycle

The Rapid Update Cycle (RUC), an operational regional analysis–forecast system among the suite of models at the National Centers for Environmental Prediction (NCEP), is distinctive in two primary aspects: its hourly assimilation cycle and its use of a hybrid isentropic–sigma vertical coordinate. The use of a quasi-isentropic coordinate for the analysis increment allows the influence of observations to be adaptively shaped by the potential temperature structure around the observation, while the hourly update cycle allows for a very current analysis and short-range forecast. Herein, the RUC analysis framework in the hybrid coordinate is described, and some considerations for high-frequency cycling are discussed. A 20-km 50-level hourly version of the RUC was implemented into operations at NCEP in April 2002. This followed an initial implementation with 60-km horizontal grid spacing and a 3-h cycle in 1994 and a major upgrade including 40-km horizontal grid spacing in 1998. Verification of forecasts...

An Hourly Assimilation–Forecast Cycle: The RUC

RUC20 : the 20-km version of the Rapid Update Cycle

The NOAA Rapid Update Cycle (RUC) is a mesoscale atmospheric data analysis and prediction system configured with a hybrid isentropic-sigma vertical coordinate and run operationally at the National Centers for Environmental Prediction (NCEP). The RUC model is the only quasi-isentropic forecast model running operationally in the world. Primary users include the aviation, severe weather, and general forecast communities, including National Weather Service Forecast Offices. The RUC is distinguished from other hybrid isentropic forecast systems by its application at a fairly high horizontal resolution (10-20 km), utilization of a high-frequency (hourly) analysis update cycle, and use of a continuous vertical coordinate formulation that allows purely isentropic model levels to extend into the lower troposphere. The 2003 operational version of the RUC model and data assimilation system is described herein, complete with a discussion of the analysis formulation and model numerics and physical parameterizations. Within the 3DVAR analysis, use of the quasi-isentropic coordinate system for the analysis increments allows the influence of observations to be adaptively shaped by the potential temperature structure around the observation. Within the model, use of the hybrid θ−σ coordinate reduces the cross-coordinate vertical transport compared to a pure σ coordinate system. Examination of a 36-h forecast East Coast cyclogenesis case illustrates the detailed yet coherent nature of the potential vorticity, moisture, and vertical velocity structures produced by the quasi-isentropic RUC model.

Mesoscale Weather Prediction with the RUC Hybrid Isentropic-Sigma Coordinate Model and Data Assimilation System

¶A three-dimensional variational (3dVAR) analysis set in a generalized vertical coordinate is described. This analysis technique has been applied to the Rapid Update Cycle (RUC), a mesoscale analysis/model system in the United States providing high-frequency, short-range forecasts. The RUC 3dVAR analysis is, in fact, set in a hybrid isentropic-sigma coordinate, but without loss of generality or applicability to other coordinate systems. The use of this coordinate provides an adaptive analysis space, with sloping of background error covariances in the proximity of baroclinic systems, and a stability-dependence for vertical error covariances. The basic characteristics of the RUC are described briefly, with special attention to its vertical coordinate. A detailed description of observation operators is provided. The 3dVAR algorithm, including stream function and velocity potential as control variables for the multivariate aspect, is described in detail. A few examples of analysis results are provided. The RUC 3dVAR in hybrid-isentropic-sigma coordinates is being implemented at the National Centers for Environmental Prediction (NCEP) in 2001.

A variational assimilation technique in a hybrid isentropic-sigma coordinate

Sounder and imager data from the GOES platform offer an opportunity to enhance the quality of the initial conditions for numerical weather prediction, as is done in the Rapid Update Cycle (RUC, Benjamin et al., 2001). The most important strength of sounder data over imager data is that their multichannels are designed for retrieving vertical distribution of temperature and moisture. The relative advantages of GOES imager data over sounder data includes better spatial coverage in the RUC domain, higher ingest frequency (15 min vs 1 hour), and higher resolution (4 km vs 10 km). The higher ingest frequency helps in reducing temporal sampling error, and higher spatial resolution refines the spatial variability of clouds. Therefore, imager data are used to enhance the subgrid variation of clouds, namely, multilevel fractional clouds. We formulate the fractional cloud coverage derived by imager data as a weak contraint in one dimensional variational formulation to generalize current cloud analysis employed in the 20-km RUC.

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Dezso Devenyi

Papers

An Hourly Assimilation–Forecast Cycle: The RUC

RUC20 : the 20-km version of the Rapid Update Cycle

Mesoscale Weather Prediction with the RUC Hybrid Isentropic-Sigma Coordinate Model and Data Assimilation System

A variational assimilation technique in a hybrid isentropic-sigma coordinate

One dimensional variational assimilation experiments combining goes sounder and imager radiance data