The RUC40 forecast model is an updated version of the generalized vertical coordinate model described by Bleck and Benjamin (1993). Modifications to improve the RUC40 included use of the code structure of the NCAR/Penn State Mesoscale Model version 5 (MM5, Grell et al. 1994). This allowed relatively easy transfer of MM5 parameterizations (cloud microphysics, radiation) into the RUC40 model.

The RUC40 model contains 42 model fields produced by the Mesoscale Analysis and Prediction System (MAPS) coupled modeling system at the NOAA Forecast Systems Laboratory (FSL).

The MAPS MORDS data set used here was obtained from NCAR's GCIP Model Output Archive Summary (http://rda.ucar.edu/datasets/ds609.1/). The files were untarred and collected together into monthly directories, but there are known gaps in the times in the archive from NCAR. These gaps are documented more below in the File Naming Convention section.

The numerical characteristics of the RUC40 mode include:

• Arakawa-C staggered horizontal grid (Arakawa and Lamb, 1977); u and v horizontal wind points are offset from mass points to improve numerical accuracy.
• No vertical staggering.
• Time step is 60 seconds at 40-km resolution.
• Positive definite advection schemes are used for the continuity equation (advection of pressure thickness between levels) and for horizontal advection (Smolarkiewicz 1983) of virtual potential temperature, and all vapor and hydrometer moisture variables.

RUC40 data are stored in individual ASCII data files, with one file per hour. Within each hourly file, 42 data variables are stored in row-major order, starting at the lower-left coordinate. Because the analysis runs at a 00Z initial time do not contain the full set of the 42 fields (described in the table below), the 00Z forecast run at time of 01Z was selected as the nearest time value to the 00Z analysis output.

There are several places in the time span of the data in which gaps are found, and these gaps are documented in two files: (1) in an Excel spreadsheet file calledruc40-list.xls, and (2) a text file called RUC-all.out. These two files provide a list by month of all the files that are contained in the untarred/unzipped monthly directories.

RUC40 data are stored in individual ASCII data files, with one file per hour. Within each hourly file, 42 data variables are stored in row-major order, starting at the lower-left coordinate. For easier access, the hourly ASCII files have been tarred/gzipped by month (e.g., 200210.tar.gz for October 2002 data). After the files are gunzipped and untarred by month, RUC40 ASCII data files have file names in the following form: <year><month><day>.<time>. ruc40-mords.asc

example: 2002100204.ruc40-mords.asc, where

year is the four-digit year the data were acquired, e.g., "2002"
month is the two-digit month of year the data were acquired, e.g., "10" is October
day is the two-digit day of the month the data were acquired, e.g., “02” for the 2nd day of October
hour is the two-digit UTC hour of the data, e.g., hour is 04Z in the example.

There are several places in the time span of the data in which gaps are found, and these gaps are documented in two files: (1) in an Excel spreadsheet file called ruc40-list.xls, and (2) a text file called RUC-all.out. These two files provide a list by month of all the files that are contained in the untarred/unzipped monthly directories.

The RUC40 model covers the 40 km (approximate) Lambertian latitude/longitude grid over the Large-Regional Study Area (LRSA) in Colorado and Wyoming, USA.

Southern Latitude: 38.3940 N 
Northern Latitude: 42.5680 N 
Western Longitude: 108.6150 W 
Eastern Longitude: 103.9710 W

Spatial Coverage Map

The following map provides an overview of the observation site:

LRSA and MAPS MORDS (RUC40) Grid Description

The following figure shows the RUC40 domain, which is placed on a Lambert conformal projection and matches what is used for the AWIPS 212 National Weather Service (NWS) distribution grid. The mesh is rectangular on this projection, and its size is 151 by 113 grid points. The grid length is 40.635 km at 35°N. Due to the varying map-scale factor from the projection, the actual grid length in RUC40 varies from about 40.6 km at 35°N to 33 km at the north boundary.

A fortran program ("read-asc40.F90") is provided with this data set that reads the latitude/longitude descriptive ASCII file, 40kmlatlon.asc.txt. These files are provided so that users can see the original domain of the RUC40.

The lower left corner point is (1,1), and the upper right corner point is (151,113), as shown in the following table.

In the vertical dimension, there are four subsurface levels in the ground and one surface level, each corresponding to a depth of:

Layer 1: Ground surface level
Layer 2: 5 cm
Layer 3: 20 cm
Layer 4: 40 cm
Layer 5: 160 cm

RUC 40 data, originally in GRIB format and covering a central North American domain, were converted to ASCII format and subsetted to the LRSA domain. Outer bounds of this MAPS-LRSA domain are:

Lower Left : 38.3940°N, 108.6150°W
Lower Right : 38.3940°N, 103.9710°W
Upper Left : 42.5680°N, 108.6150°W
Upper Right : 42.5680°N, 103.9710°W

Parameters presented in this data set are relative humidity, sfc temperature, dew point, sea-level pressure, precipitation, snow accumulation, snow depth, categorical precipitation types, freezing levels, 3-h pressure change, CAPE/CIN, lifted index, helicity, precipitable water, soil moisture, tropopause pressure, vertical velocity, PBL depth, gust wind speed, cloud base height, cloud top height, cloud fraction, visibility, pressure of maximum equivalent potential temperature in column, convective cloud top height, and equilibrium level height.

The atmospheric prognostic variables of the RUC40 forecast model are:

• pressure thickness between levels
• virtual potential temperature
• horizontal wind components
• water vapor mixing ratio
• cloud water mixing ratio
• rain water mixing ratio
• ice mixing ratio
• snow mixing ratio
• graupel (rimed snow) mixing ratio
• number concentration for ice particles
• turbulence kinetic energy
• turbulent variance of potential temperature
• turbulent variance of water vapor mixing ratio
• turbulent covariance of potential temperature perturbations with water vapor mixing ratio perturbations

The soil prognostic variables (at six model levels) of the RUC40 forecast model are:

• soil temperature
• soil volumetric moisture content
• Other surface-related prognostic variables are snow water equivalent moisture and snow temperature.