RUC-2 - The Rapid Update Cycle Version 2 Technical Procedures Bulletin - draft

Stanley G. Benjamin, John M. Brown, Kevin J. Brundage, Barry E. Schwartz, Tatiana G. Smirnova, and Tracy L. Smith

NOAA/ERL Forecast Systems Laboratory, Boulder, CO

Lauren L. Morone

Environmental Modeling Center, National Centers for Environmental Prediction, Camp Springs, MD

Revised 31 Mar 98, a few small updates. Change log link added 16 June 1998. Use of tropical storm reconnaissance data added 31 Aug 98.

ABSTRACT - Summary of RUC-2 vs. RUC-1 differences
Horizontal and vertical domain
Data assimilated
Assimilation frequency
Model physics
Surface analyses/forecasts
Variables available
Output formats available
Verification stats for 40km MAPS vs. 60km MAPS and 48km Eta

Change log for operational RUC-2 running in real-time at NCEP

To RUC/MAPS homepage, including real-time images


A number of significant weather forecasting problems exist in the 0-12 hour range, including severe weather in all seasons (tornadoes, severe thunderstorms, crippling snow and ice storms) and hazards to aviation (clear air turbulence, icing, downbursts). Accurate short-term forecasts are clearly indispensable for the protection of life and property, but they also have tremendous economic value even under non- threatening conditions, for example, for agriculture and the recreation and power-generation industries. The Rapid Update Cycle (RUC) was designed to provide accurate numerical forecast guidance for weather-sensitive users for the next 12 hour period. The RUC runs at the highest frequency of any forecast model at the National Centers for Environmental Prediction (NCEP), assimilating recent observations aloft and at the surface to provide very high frequency updates of current conditions and short-range forecasts using a sophisticated mesoscale model.

This bulletin describes a new version of the RUC, called RUC-2, implemented at NCEP in April 1998. The RUC-2 produces new 3-d analyses and short-range forecasts every hour, compared to the 3-h updating in RUC-1. The original Rapid Update Cycle (RUC-1, Benjamin et al. 1994a (TPB) ,1994b ) was implemented in September 1994 at NCEP. Some number of smaller changes were made to RUC-1 over the 1995-1996 period, but the RUC-2 is a significant advance over RUC-1, not just in assimilation frequency, but also in resolution, types of data assimilated, and model physics. These changes (summarized in the TPB Abstract) allow the RUC-2 to more accurately represent significant weather systems across the United States in all seasons.

Summary of characteristics in RUC-2 compared to RUC-1. Also see the TPB Abstract.

Uses of the RUC

  • Explicit use of short-range forecasts - The RUC forecasts are unique in that they are initialized with very recent data. Thus, the majority of the time, the most recent RUC forecast has been initialized with more recent data than the other forecast model runs available. Even at 0000 and 1200 UTC, when other model runs are available, the RUC forecasts are useful for comparison over the next 12-h since they have some unique aspects regarding the isentropic coordinate, hourly data assimilation, and model physics.
  • Monitoring current conditions with hourly analyses - Hourly analyses are particularly useful when overlaid with hourly satellite and radar images, or hourly observations such as from surface stations or profilers.
  • Evaluating trends of longer-range models - RUC-2 analyses and forecasts are useful to confirm (or call into question) the short-term predictions of the Eta, NGM, and AVN models. This is often helpful in establishing which of the 48-72-h models is verifying most accurately in the first 12-h period.

Some key users of the RUC


2.a. Domain

The RUC-2 domain ( Fig.1a) is on a Lambert conformal projection matching that used for the AWIPS 212 NWS distribution grid. The mesh is rectangular on this projection, and its size is 151 by 113 grid points (compared to 81x62 for RUC-1 (Fig.1b) ). The grid length is 40.635 km at 35 deg N. Due to the varying map-scale factor from the projection, the actual grid length in RUC-2 varies from about 40.6 km at 35 deg N to 33 km at the north boundary. The grid length is about 38 km at 43 deg N.

The RUC-2 domain was designed to:

  • provide higher horizontal resolution than RUC-1
  • move the lateral boundaries slightly farther off the east and west coasts than in RUC-1 to improve coastal forecasts (a weakness of RUC-1)
  • match the AWIPS 212 distribution grid to avoid interpolation and give field users the highest resolution possible.

The 40-km RUC-2 domain covers about 50% more area than the 60-km RUC-1 domain. It extends farther than the RUC-1 domain in all directions, but especially in the southeast, owing to use of the Lambert conformal projection and the need to cover slightly east of the state of Maine. It covers considerably more oceanic areas than the RUC-1 domain.

The RUC-2 latitude/longitude at each point in an ASCII file can be downloaded from The lower left corner point is (1,1), and the upper right corner point is (151,113), as shown in the table below.

RUC-2 point AWIPS-212 point Latitude Longitude
(1,1) (23,7) 16.2810 N 126.1378 W
(1,113) (23,119) 54.1731 N 139.8563 W
(151,1) (173,7) 17.3400 N 69.0371 W
(151,113) (173,119) 55.4818 N 57.3794 W
RUC-2 domain parameters

2.b. Horizontal resolution

Horizontal resolution in RUC-2 is 40 km compared to 60 km for the RUC-1. The higher resolution allows considerable improvement in resolution of topography and also in shapes of coasts and lakes. These improvement improve the ability of the RUC-2 to resolve local circulations and orographic precipitation patterns. Because the RUC-2 model has less internal smoothing than the Eta or NCAR/Penn State MM5 models, these features tend to be fairly well depicted considering its 40-km resolution.

2.c. Vertical resolution

The RUC-2 has 40 vertical levels compared to 25 levels in RUC-1. The RUC-2 continues to use a generalized vertical coordinate configured as a hybrid isentropic-sigma coordinate in both the analysis and model. This coordinate has proven to be very advantageous in RUC-1 in providing sharper resolution near fronts and the tropopause (e.g., Benjamin 1989, Johnson et al. 1993, Zapotocny et al. 1994). Some of the other advantages include:

  • All of the adiabatic component of the vertical motion on the isentropic surfaces is captured in flow along the 2-d surfaces. Vertical advection, which usually has somewhat more truncation error than horizontal advection, does much less "work" in isentropic/sigma hybrid models than in quasi-horizontal coordinate models. This characteristic results in improved moisture transport and very little precipitation spin-up problem in the first few hours of the forecast.
  • Improved conservation of potential vorticity. The potential vorticity and tropopause level (based on the 2.0 PV unit surface) show very good spatial and temporal coherence in RUC-2 grids.
  • Observation influence in the RUC-2 analysis extends along isentropic surfaces, leading to improved air-mass integrity and frontal structure.

A sample cross section of RUC-2 native levels is displayed in Fig. 2. The cross-section is across the United States, passing south of San Francisco, through Boulder (where a downslope windstorm occurred that morning) and through southern Virginia on the East Coast. The cross section is for a 12-h forecast valid at 1200 UTC 30 November 1995.

The typical RUC-2 resolution near fronts is apparent in this figure, as well as the tendency for more terrain-following levels to "pile up" in warmer regions (the eastern part of the cross section, in this case). The hybrid isentropic-sigma coordinate is defined by a 20-line section of code in both the analysis and forecast model. The rest of the code treats the analysis/model processes as a generalized vertical coordinate. The 20-line section of code can be changed to define a pure sigma terrain-following coordinate and has been tested in this mode.

In the RUC-2 (as well as in RUC-1), analysis/model levels which are isentropic in part of the domain can become terrain-following in other parts, as shown in Fig. 2. A reference potential temperature is assigned to each of the 40 levels (Table 1).

Table 1. RUC-2 reference potential temperatures
224. 232. 240. 245. 250. 255. 260. 265.
270. 274. 278. 282. 286. 290. 294. 297.
300. 302. 304. 306. 308. 310. 312. 314.
316. 318. 320. 322. 325. 328. 331. 334.
337. 341. 347. 355. 364. 375. 400. 450.

The prespecified pressure spacing in RUC-2, starting from the ground is 2, 5, 8, and 10 mb, followed by as many 15-mb layers as are needed. (Near-surface pressure spacing in RUC-1 was 20 mb.) This terrain-following spacing compacts somewhat as the terrain elevation increases. Excellent resolution of the boundary layer is provided in all locations, including over higher terrain. The lowest atmospheric level in RUC-2 is set at 5 m above the model terrain height. The effects of this choice are discussed in the analysis and model sections, but since the RUC-2 has an explicit level actually at the surface, no extrapolation from higher levels is necessary to diagnose values at the surface. The minimum potential temperature spacing occurs through much of the troposphere and is 2 K instead of 4 K as in RUC-1. The top level in RUC-2 is at 450 K as opposed to 410 K in RUC-1. Overall, the vertical resolution is somewhat higher both in the boundary layer and free atmosphere, and the domain extends farther into the stratosphere.

2.d. Terrain

The most obvious difference, of course, between terrain in RUC-2 ( Fig. 3a) and that in RUC-1 (Fig. 3b) is that finer-scale topographical features are distinct in the RUC-2 terrain. RUC-2 analyses and forecasts can depict many significant topographically induced features, including mountain/valley circulations, mountain waves, sea breezes, and orographic precipitation patterns. The surface elevation of the RUC-2 is defined by a "slope envelope" topography instead of the previous full envelope topography used in RUC-1. The envelope topography is defined by adding the sub-grid-scale terrain standard deviation (calculated from a 10-km terrain field) to the mean value over the grid box. In the slope envelope topography, the terrain standard deviation is calculated with respect to a plane fit to the high-resolution topography within each grid box. This gives more accurate terrain values, especially in sloping areas at the edge of high-terrain regions. It also avoids a tendency of the standard envelope topography to project the edge of plateaus too far laterally onto low terrain regions. Using the slope envelope topography gives lower terrain elevation at locations such as Denver and Salt Lake City which are located close to mountain ranges. The RUC-2 topography at each point in an ASCII file can be downloaded from


3.a. Data assimilated
The new data sets assimilated in the 40-km RUC-2 include:

These new data sets already assimilated in the experimental 40-km RUC/MAPS at FSL will also be ingested into the RUC-2 as soon as available at NCEP:
  • boundary-layer (915 MHz) profiler winds
  • RASS (Radio Acoustic Sounding System) temperatures
Satellite-based precipitable water retrievals and cloud-drift winds are currently used only over water points. Satellite observations over land will be ingested in the near future. Wind profiler, rawinsonde, aircraft, and surface (land and buoy) observations continue to be utilized in the RUC-2, as they were for RUC-1, except that the wind profiler and rawinsonde data are used with higher vertical resolution due to the 40 levels in RUC-2. Here is a summary of the actual measurements used from other data sets:
  • Rawinsonde/dropwindsonde - temperature, height, moisture, wind
  • Aircraft - wind, temperature
  • Surface - wind, temperature, dewpoint, altimeter setting
More information on the use of wind data in RUC-2 is available in Smith and Benjamin (1998).

3.b. Optimum interpolation analysis

The optimal interpolation multivariate analysis used in RUC-1 has been substantially modified for the RUC-2, providing, among other things, closer fit to observations, better use of aircraft ascent/descent winds and temperatures, and greater efficiency. A discussion of optimal interpolation analysis in isentropic coordinates is provided in Benjamin (1989).

Sequence in RUC-2 analysis

  • Read in observations
  • Subject to gross quality control (range limits, wind shear, lapse rate)
  • Read in background (previous 1-h forecast, if available). RUC-2 will "cold start" with Eta forecast background if RUC-2 has not been running within last 12 hours.

    This background field is defined at the (x,y,p) points of the hybrid coordinate surfaces for the background field. The quality control and analysis steps below are carried out at these (x,y,p) points. This will result in changes to virtual potential temperature at these points. For the RUC-2, the next-to-last step (bullet) is in effect a repositioning of the coordinate surfaces to correspond to the results of the analysis steps that preceed it.

  • Perform precipitable water analysis and modify background moisture values according to precipitable water observations (currently -- GOES and SSM/I, future - GPS). In this precipitable water "pre-analysis", the shape of the water vapor mixing ratio in the background grid field is left intact, but is either moistened or dried out according to the observations. (See Benjamin et al. 1998 - GPS precipitable water paper, NWP conference.)
  • Perform buddy-check quality control. Flag suspicious observations. (See quality control section below.)
  • Calculate super-observations. This procedure combines observations that are near to each other in space. It prevents against the possibility of ill-conditioned matrices in the optimum interpolation analysis.
  • Multivariate z/u/v analysis at all levels. A level-dependent partial geostrophic constraint is applied, weakest at the surface and in the boundary layer. The wind analysis is anisotropic and oriented along the flow, according to the geostrophically derived horizontal covariances of forecast error (Benjamin 1989).
  • Height analysis increment (z') calculated in last step is vertically differentiated to obtain a temperature increment. This temperature increment is added to the temperature field. Now the temperature (virtual potential temperature) background is an updated field which has taken into account the height observations and wind observations through the partial geostrophic constraint.
  • Calculate surface pressure increment from multivariate z' increment at surface. This provides an updated background field for the univariate surface pressure analysis a few steps down. The height analysis is essentially ignored from this step on, since a hydrostatic integration will occur at the end of the analysis to calculate heights.
  • Perform univariate temperature (theta-v) analysis at all levels using temperature observations. Now the direct temperature observations (e.g., surface, aircraft, rawinsonde, RASS) have also been incorporated.
  • Perform univariate wind analysis at lowest 5 levels. This analysis uses the result of the previous multivariate analysis as its background. This step forces close matching to surface wind observations. No geostrophic constraint is applied at this step.
  • Perform univariate analysis for pressure at surface. This step forces close fitting to surface pressure observations (calculated through the altimeter setting).
  • Perform univariate moisture (condensation pressure) analysis at all levels. The moisture variable stored in RUC-2 is water vapor mixing ratio, but inside the RUC-2 analysis, values are converted to condensation pressure, since this variable varies with fewer orders of magnitude over the depth of the troposphere than water vapor mixing ratio.
  • All calculations up to this point have been done to change values at the (x,y,p) points of the background field. The exact same procedure could have been applied to a background from a sigma or eta coordinate model. In the case of the RUC-2, we adjust (vertically interpolate) these values to the hybrid isentropic-sigma coordinates.
  • Hydrostatic integration to recalculate z (height) at all levels. Thus, the RUC-2 mass field changes are all made through the virtual potential temperature field at all levels and the surface pressure field. The height observations influence these fields, as described above.
  • Diagnose other variables from analysis - e.g., special levels such as freezing level, maximum wind level, tropopause level...

The RUC-2 analysis provides de facto analyses of cloud variables and soil variables by using the previous 1-h forecast of these variables as initial conditions for the next run. Although use of observations will later provide improved fields for these variables (e.g., Kim and Nychka 1998), this "cycling" provides substantial improvement over zero initial clouds and climatology for soil variables.

3.c. Incorporation of the surface analysis within the 3-d analysis

With the 1-h assimilation cycle, the RUC-2 integrates into one system the RUC-1 and RSAS (RUC Surface Analysis System) from the 60-km era. The RUC-2 surface analyses are improved over those from RUC-1 due to the use of a forecast background combined with new design features to ensure that the 40km surface analyses not only draw more closely to the data, but also have better consistency and reliability. Specific advantages of RUC-2 surface analyses over those from RUC-1 are:

The following new features are added to ensure that the 40km surface analyses draw very closely to surface data:

Comparison of 60km RUC-1 and 40km RUC-2 surface temperature analyses for 1200 UTC 19 February 1997.

3.d. Quality control

As in RUC-1, quality control in RUC-2 involves a buddy check. The buddy check is of observation residuals, the differences betwen the observation and the background field interpolated to the observation point, and not of the observations alone. This is an important distinction, since it means that any known anomaly in the previous forecast has already been subtracted out, improving the sensitivity of the QC procedure to actual errors.

At each observation point, the parameter in question is estimated via optimum interpolation of values from surrounding observation points. If the estimated and measured values differ by more than a prescribed amount, further checks determine whether the central observation or one of its neighbors is erroneous.

Bird contamination for radar/profiler winds

Checks are made for bird contamination for both VAD and profiler winds in RUC-2. A careful check for bird (and other) contamination in profiler winds is made at the Profiler Hub in Boulder, CO. This check includes use of second-moment data to examine for likelihood of bird contamination. If the quality control flag produced by this check indicates suspicious data, the profiler data at that level is not used by RUC-2. For VAD winds, no second-moment data is available, so a cruder and more conservative check is made. A solar angle is calculated, and if the sun is down and the temperature is warmer than -2 deg C, VAD winds are not used if they have a northerly component between 15 August and 15 November or a southerly component between 15 February and 15 June.

3.e. Future improvements

A new 3-d variational analysis (Devenyi and Benjamin 1998) is nearing completion for the RUC-2 and will follow the rest of the RUC-2 into operations with a lag time of several months.


See also information on 1-h cycle and data used for more differences.

1-h assimilation cycle. The background for each analysis is the previous 1-h forecast. The 1-h cycle allows much more complete use of profiler, surface, and VAD data, which are all available at least hourly. The time window for aircraft data is now -1h to 0h instead of -2h to +1h, meaning that aircraft data are now applied closer to the time that they are actually reported.

Grids from RUC-2 will be available almost 1 hour earlier than those from RUC-1. The data cut-off time from the 40km system is 20 min after the analysis valid time. A catch-up cycle at 0000 and 1200 UTC runs at +55 min to catch late-arriving rawinsonde data. Twelve-hour forecasts from these times are run from the catch-up cycle analysis, rather than the "early look" analysis at 20 min after.


The RUC-2 forecast model is an updated version of the generalized vertical coordinate model described by Bleck and Benjamin (1993). Modifications to a 20-line section of code in the model are sufficient to modify it from the hybrid isentropic-sigma coordinate described in section 2.c to either a pure sigma or pure isentropic model.

The RUC-2 model is considerably different from the RUC-1 model in its parameterizations of physical processes such as cloud microphysics (stable precipitation), turbulent mixing, radiation, and convective precipitation. To some extent, this was made possible by changing the RUC-2 model to use 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 RUC-2 model, and will continue to do so in the future as new MM5 parameterizations are developed.

5.a. Basic dynamics/numerics Here are some of the basic numerical characteristics of the RUC-2 model:

  • Arakawa-C staggered horizontal grid (Arakawa and Lamb 1977); u and v horizontal wind points offset from mass points to improve numerical accuracy.
  • No vertical staggering.
  • Time step is 60 seconds at 40-km resolution.
  • Positive definite advection schemes used for continuity equation (advection of pressure thickness between levels) and for horizontal advection (Smolarkiewicz 1983) of virtual potential temperature and all vapor and hydrometeor moisture variables.
The atmospheric prognostic variables of the RUC-2 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 levels) of the RUC-2 forecast model are:
  • soil temperature
  • soil volumetric moisture content
Other surface-related prognostic variables are snow water equivalent moisture and snow temperature.

5.b. Physical parameterizations

Explicit cloud/moisture processes. The explicit microphysics from the NCAR/Penn State mesoscale model MM5 (level 4, Reisner et al. 1997) is used, with five hydrometeor species -- cloud water, rain water, snow, ice, graupel (mixing ratios for each) and also with an explicit prediction of ice particle number concentration. This improvement was made to provide improved forecasts of clouds, icing, and precipitation from RUC-2. In the 60km RUC-1, stable precipitation was defined simply by supersaturation removal, with no knowledge of cloud or ice processes. All of the cloud variables are cycled in the 40-km MAPS, meaning that there are initial cloud fields for each run. In the RUC-2 model, all six cloud variables are advected using the positive definite scheme of Smolarkiewicz (1983) on the isentropic-sigma levels with adaptive vertical resolution. The incorporation of this scheme into RUC-2 is described in detail by Brown et al. (1998).

Improved surface physics. The RUC-2 includes a 6-layer soil/vegetation/snow model (schematic) to improve forecasts of low-level conditions. Surface (shelter/anemometer level) forecasts are often critically dependent on accurate estimates of surface fluxes, and in turn, on reasonably accurate soil moisture and temperature estimates. The RUC-2 soil model contains heat and moisture transfer equations solved at 6 levels at each grid point together with the energy and moisture budget equations for the ground surface (Smirnova et al. 1997a,b). The heat and moisture budgets are applied to a thin layer spanning the ground surface and including both the soil and the atmosphere with corresponding heat capacities and densities. A treatment of the evapotranspiration process, developed by Pan and Mahrt (1987), is implemented in the MAPS/RUC soil/vegetation scheme.

In the presence of snow cover, snow is considered to be an additional upper layer of soil that interacts with the atmosphere, significantly affecting its characteristics (Smirnova et al 1998).

The snow model contains a heat-transfer equation within the snow layer together with the energy and moisture budget equations on the surface of the snow pack. This budget is applied to the entire snow layer if the snow depth is less than a threshold value, currently set equal to 7.5 cm, or to the top 7.5 cm layer of snow if the snow pack is thicker. Snow evaporates at a potential rate unless the snow layer would all evaporate before the end of the time step. In this case the evaporation rate is reduced to that which would just evaporate all the existing snow during the current time step. A heat budget is also calculated at the boundary between the snow pack and the soil, allowing melting from the bottom of the snow layer. Melting at the top or bottom of the snow layer occurs if energy budgets produce temperatures higher than the freezing temperature (0 deg C). In this case the snow temperature is set equal to the freezing point, and the residual from the energy budget is spent on melting snow. Water from melting snow infiltrates into the soil, and if the infiltration rate exceeds the maximum possible value for the given soil type, then the excess water becomes surface runoff.

The accumulation of snow on the ground surface is provided by the microphysics algorithm of the MAPS/RUC forecast scheme (Reisner et al. 1997, Brown et al. 1998). It predicts the total amount of precipitation and also the distribution of precipitation between the solid and liquid phase. The subgrid-scale ("convective") parameterization scheme also contributes to the liquid precipitation. With or without snow cover, the liquid phase is infiltrated into the soil at a rate not exceeding maximum infiltration rate, and the excess goes into surface runoff. The solid phase in the form of snow or graupel is accumulated on the ground/snow surface and is unavailable for the soil until melting begins. The RUC-2 surface package provides surface temperature and dewpoint forecasts that are clearly superior to those of the RUC-1 due to improved surface heat and moisture fluxes. The soil temperature and moisture has been evolving since 29 April 1996, leading to fairly accurate estimates of these fields, certainly much better than climatology (Smirnova et al. 1997b). Real-time estimates of soil moisture in the top 2 cm are available on the MAPS/RUC home page,

Atmospheric radiation. The MM5 atmospheric radiation package (Dudhia 1989, Grell et al. 1994) is used in the RUC-2, with additions for attenuation and scattering by all hydrometeor types. This scheme is a broadband scheme with separate components for longwave and shortwave radiation. In the RUC-1, there was no atmospheric radiation at all, only a surface radiation budget with clouds diagnosed from relative humidity. The solar flux at the top of the atmosphere is now variable, taking into account the elliptical orbit of the earth around the sun.

Turbulent mixing. In RUC-2, turbulent mixing at all levels, including the boundary layer, is prescribed the explicit turbulence scheme of Burk and Thompson (1989). This scheme is a level-3.0 scheme, with explicit forecast of turbulent kinetic energy and three other turbulence variables, replacing the Mellor-Yamada level-2.0 scheme in RUC-1. The surface layer mixing continues to be prescribed by Monin-Obukhov similarity theory, specifically the three-layer scheme described in Pan et al. (1994).

With the Burk-Thompson scheme, the RUC-2 forecasts TKE amounts of 5-20 J/kg in the boundary layer, and also forecasts TKE maxima aloft, typically localized in frontal zones, corresponding to estimated areas of clear-air turbulence potential.

Convective parameterization. A version of the Grell (1993) convective parameterization is used, updated from that used in the RUC-1, including fixes to downdraft detrainment, calculation of cloud top, minimum cloud depth, and capping criteria. This version gives somewhat larger amounts of precipitation and more coherent patterns in convective areas than the RUC-1 version.

The inclusion of downdrafts in the Grell scheme results in smaller-scale details in RUC-2 warm season precipitation patterns than may be evident in that from the Eta model, which currently uses the Betts-Miller-Janjic convective parameterization. This same difference in character of precipitation forecasts is also evident in NCEP/NSSL experiments comparing the Kain-Fritsch (which also includes downdrafts) and Betts-Miller-Janjic schemes both within the MesoEta model (Kain et al. 1998).

5.c. Lateral boundary conditions Lateral boundary conditions for the RUC-2 model are provided by the early Eta run output at 3-h intervals. The Eta model forecasts are interpolated to the 40-km RUC-2 domain on its hybrid coordinate levels. Values of pressure thickness, virtual potential temperature, and horizontal winds at the edge of the RUC-2 domain (up to 5 grid points from the boundary) are nudged (Davies 1976) toward the Eta values at each time step in a model run.

The accuracy of RUC-2 forecasts is driven to some extent by the time availability of Eta forecasts. RUC-2 forecasts initialized at 0000 or 1200 UTC are forced to use boundary conditions from Eta runs already 12 h old, since the RUC-2 runs before the Early Eta. This means that the 12-h RUC-2 forecasts valid at 0000 or 1200 UTC are nudging toward 24-h Eta forecasts at these times. Typically, the skill of RUC-2 forecasts jumps near the western boundary by the 0300 or 1500 UTC runs, respectively, since the newer Early Eta runs are available by those times.

5.d. Fields for surface boundary conditions

  • Daily 50-km resolution sea-surface temperatures- NCEP. The same SST field used for the Eta model is also used for the RUC-2. An up-to-date display of the field used in RUC-2 and Eta is available here .
  • Daily 14-km resolution lake-surface temperatures for the Great Lakes - NOAA/Great Lakes Environmental Research Laboratory
  • Weekly ice cover - NESDIS/NCEP
  • Monthly vegetation fraction data at a resolution of 0.14 degrees latitude - NESDIS/NCEP
  • Seasonal (4 seasons) albedo at 1 deg resolution.
  • Land use (14 classes) at 1 deg resolution.
  • Soil texture at 1 deg resolution
  • The snow fields cycled by RUC-2 seem to be more accurate than the daily U.S. Air Force snow cover analysis. A better snow cover analysis from NESDIS is expected early in 1998, and modifications will be made to combine the RUC-2 cycled fields with these data when they become available. Improved surface fields (land use, soil texture) will also added as they become available for the RUC-2 domain.


    Verification statistics for the RUC-1, RUC-2, and the 48-km Eta models are available at this link.


    Variables available

    In RUC-2, water vapor mixing ratio replaces condensation pressure (output in RUC-1) as the water vapor moisture variable in the 3-d grids. Height also replaces Montgomery stream function. The use of height and water-vapor mixing ratio instead of the variables they replace facilitates calculation of derived quantities involving these variables. Height also stores more efficiently in GRIB.

    40km RUC/MAPS output formats

    From the 40km RUC at NCEP, five different formats will be available: Click here for more information on 40km RUC-2 variables.

    RUC-2 GRIB table - parameters for all RUC-2 variables

    • isobaric main (25-mb) grids of primary six 3-d variables plus about 77 2-d fields (including precipitation, fluxes, CAPE/CIN, tropopause fields, surface fields, fields from special levels - mean layers near surface, freezing level, max wind, etc.)
      (~6 MB in GRIB format per output time)
    • native (hybrid coordinate) grids of 3-d variables plus 2-d fields
      (~10 MB in GRIB format per output time)
    • surface grids (25 2-d fields)
      (0.35 MB per output time)
    • model output (BUFR) soundings at ~486 sites (standard sounding variables plus surface variables).
      Naming convention
      isobaric main:
           XX = cycle time (01,02,03..)
         - zz = forecast hour (00,01,02...)
      BUFR sounding:

      (~2.5 MB for each hour for a given run, soundings for all sites)

    Use of GRIB gridded input and output. The MAPS database routines used in RUC-1 will no longer be used for grid input and output.


    Explanation of diagnosed RUC-2 variables , including surface fields, stability indices, precipitation products, special level fields (tropopause, freezing level).


    • 3-d variational analysis
    • 3-d cloud analysis using satellite, radar, and surface observations combined with explicit RUC-2 multi-hydrometeor cloud forecast.
    • Assimilation of new data types - radial winds from radar, satellite radiances, GPS precipitable water, local mesonets.
    • Improved physical parameterizations, including cloud microphysics, surface physics (frozen soil, high-resolution soil and surface data sets), and turbulence physics.
    • 20-km horizontal resolution - planned for NCEP's Class 8 computer about 1999.
    • Non-hydrostatic version of RUC forecast model - Development underway in collaboration with University of Miami.


  • Arakawa, A., and V.R. Lamb, 1977: Computational design of the basic dynamical processes of the UCLA general circulation model. Methods in Computational Physics, Vol. 17, Academic Press, 174-265, 337 pp.

  • Benjamin, S.G., J.M. Brown, K.J. Brundage, B.E. Schwartz, T.G. Smirnova, and T.L. Smith, 1998: The operational RUC-2. Preprints, 16th Conference on Weather Analysis and Forecasting, AMS, Phoenix, 249-252.

  • Benjamin, S.G., T.L. Smith, B.E. Schwartz, S.I. Gutman, and D. Kim, 1998: Precipitation forecast sensitivity to GPS precipitable water observations combined with GOES using RUC-2. 12th Conf. on Num. Wea. Pred., AMS, Phoenix, 73-76.

  • Benjamin, S.G., J.M. Brown, K.J. Brundage, D. Devenyi, D. Kim, B.E. Schwartz, T.G. Smirnova, T.L. Smith, and A. Marroquin, 1997: Improvements in aviation forecasts from the 40-km RUC. Preprints, 7th Conference on Aviation, Range, and Aerospace Meteorology, Long Beach, February, 411-416.

  • Benjamin, S. G., K. J. Brundage, and L. L. Morone, 1994a: The Rapid Update Cycle. Part I: Analysis/model description. Technical Procedures Bulletin No.~416, NOAA/NWS, 16 pp. [National Weather Service, Office of Meteorology, 1325 East-West Highway, Silver Spring, MD 20910]. This is the TPB for the original 60-km RUC-1.

  • Benjamin, K.J. Brundage, P.A. Miller, T.L. Smith, G.A. Grell, D. Kim, J.M. Brown, and T.W. Schlatter, 1994b. The Rapid Update Cycle at NMC. Preprints, Tenth Conference on Numerical Weather Prediction, Portland, OR, July 18-22, 1994. American Meteorological Society, Boston, 566-568.

  • Benjamin, S. G., K. A. Brewster, R. L. Brummer, B. F. Jewett, T. W. Schlatter, T. L. Smith, and P. A. Stamus, 1991: An isentropic three-hourly data assimilation system using ACARS aircraft observations. Mon. Wea. Rev., 119, 888-906. The original MAPS description -- an early pure isentropic version.

  • Benjamin, S. G., 1989: An isentropic meso-alpha scale analysis system and its sensitivity to aircraft and surface observations. Mon. Wea. Rev., 117, 1586-1603.

  • Bleck, R., and S.G. Benjamin, 1993. Regional weather prediction with a model combining terrain-following and isentropic coordinates. Part I: model description. Mon. Wea. Rev., 121: 1770-1785. Primary journal article on the dynamic framework for the MAPS/RUC hybrid coordinate model.

  • Brown, J.M., T.G. Smirnova, and S.G. Benjamin, 1998: Introduction of MM5 level 4 microphysics into the RUC-2. Preprints 12th Conf. on Num. Wea. Pred., AMS, Phoenix.

  • Burk, S.D., and W.T. Thompson, 1989: A vertically nested regional numerical prediction model with second-order closure physics. Mon. Wea. Rev., 117, 2305-2324.

  • Davies, H.C., 1976: A lateral boundary formulation for multi-level prediction models. Tellus, 102, 405-418.

  • Devenyi, D. and S.G. Benjamin, 1998: Application of a 3DVAR analysis in RUC-2. 12th Conf. on Num. Wea. Pred., AMS, Phoenix, 37-40.

  • Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46, 3077-3107.

  • Grell, G.A., 1993: Prognostic evaluation of assumptions used by cumulus parameterizations. Mon. Wea. Rev., 121, 764-787.

  • Grell, G.A., J. Dudhia, and D.R. Stauffer, 1994: A description of the fifth-generation Penn State/NCAR Mesoscale Model (MM5). NCAR Technical Note, NCAR/TN-398 + STR, 138 pp.

  • Johnson, D.R., T.H. Zapotocny,F.M. Reames, B.J. Wolf, and R.B. Pierce, 1993: A comparison of simulated precipitation by hybrid isentropic-sigma and sigma models. Mon. Wea. Rev., 121, 2088-2114.

  • Kain, J.S., D.J. Stensrud, M.E. Baldwin, and G.S. Manikin, 1998: A comparison of two convective parameterizations schemes in NCEP's MesoEta model and the implications for quantative precipitation forecasting.

  • Kim. D., and D. Nychka, 1998: Comparisons of density smoothers to combine satellite imager and sounder data. 14th Conf. on Prob. and Stat. in the Atmos. Sci., AMS, Phoenix

  • Marroquin, A., T.G. Smirnova, J.M. Brown, and S.G. Benjamin, 1998: Forecast performance of a prognostic turbulence formulation implemented in the MAPS/RUC model. 12th Conf. on Num. Wea. Pred., AMS, Phoenix.

  • Pan, H.-L. and L. Mahrt, 1987: Interaction between soil hydrology and boundary-layer development. Bound.-Layer Meteorol., 38, 185-202.

  • Pan, Z., S.G. Benjamin, J.M. Brown, and T. Smirnova. Comparative experiments with MAPS on different parameterization schemes for surface moisture flux andb oundary- layer processes. Monthly Weather Review 122:449-470 (1994)

  • Reisner, J., R.M. Rasmussen, and R.T. Bruintjes, 1997: Explicit forecasting of supercooled liquid water in winter storms using a mesoscale model. Quart. J. Roy. Meteor. Soc.

  • Schwartz, B.E. and S.G. Benjamin, 1998: Verification of RUC-2 and Eta model precipitation forecasts. 16th Conf. on Wea. Analysis and Forecasting, AMS, Phoenix, J19-J22.

  • Smirnova, T.G., J.M. Brown, and S.G. Benjamin, 1998: Impact of a snow physics parameterization on short-range forecasts of skim temperature in MAPS/RUC. 12th Conf. on Num. Wea. Pred., AMS, Phoenix.

  • Smirnova, T. G., J. M. Brown, and S. G. Benjamin, 1997a: Performance of different soil model configurations in simulating ground surface temperature and surface fluxes. Mon. Wea. Rev., 125, 1870-1884.

  • Smirnova, T. G., J. M. Brown, and S. G. Benjamin, 1997b: Evolution of soil moisture and temperature in the MAPS/RUC assimilation cycle. Preprints, 13th Conference on Hydrology, Long Beach, AMS, 172-175.

  • Smith, T.L., and S.G. Benjamin, 1998: The combined use of GOES cloud-drift, ACARS, VAD, and profiler winds in the RUC-2. 12th Conf. on Num. Wea. Pred., AMS, Phoenix.

  • Smolarkiewicz, P.K., 1983: A simple positive-definite advection transport algorithm. Mon. Wea. Rev., 111, 479-486.

  • Zapotocny, T.H., D.R. Johnson, and F.M. Reames, 1994: Development and initial test of the University of Wisconsin global isentropic-sigma model. Mon. Wea. Rev., 122, 2160-2178.
  • Please credit the NOAA/Earth System Research Laboratory, RUC development group, if you wish to use any pictures from this web site.

    This page prepared by Stan Benjamin

    Last updated: 2 Feb 98