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:
- use of a forecast background rather than persistence
- multivariate/univariate two-pass analysis for winds/pressure
instead of a single-pass univariate analysis
- consistency in data-void regions with terrain-induced dynamics and
surface physics in the 40-km version, allowing features of
the background (forecast) fields such as mountain/valley
circulations, drainage winds, effects
of variations in soil moisture, vegetation type, land use, roughness length,
cover, land/water contrast, and explicit clouds to be present
in the analysis.
- improved quality control due to the forecast background. This is
a fairly significant item, as the 60km QC led to frequent bullseyes that could
only be eliminated by black-listing problematic stations
- lack of spurious temperature, moisture, and wind
gradients at ocean or data-void boundaries.
The following new features are added to ensure that the 40km surface
draw very closely to surface data:
- All station pressure (altimeter) and surface wind observations are used
regardless of the difference between station and model elevation. The
pressure is reduced to the model elevation using the local lapse rate
over the bottom 5 levels in the background field.
- Temperature and dewpoint observations are reduced, via the local lapse
from model terrain height to actual station elevation, provided,
that the reduction does not exceed 70 mb. With this change and
the higher-resolution 40km terrain, a far higher percentage (95%) of
surface temperature and dewpoint observations in the western U.S.
are used in the 40km
3-d analysis than in the 60km RUC-1 3-d analysis.
for a list of surface stations used in the RUC-2 at a particular
time and the pressure separation between station pressure and model
pressure for each.
- The surface wind analysis is performed in two passes, as noted earlier.
The first pass is a multivariate wind/height analysis with weak
geostrophic coupling since some correlation between the
actual and geostrophic winds is expected at the surface,
especially over water. The second pass uses the first pass as its
background and is univariate, so that local details, particularly
in the wind observations, are drawn for.
- Expected surface observation errors for the 40km RUC-2 (a parameter in
the analysis) have been reduced from values in
the 60km RUC to force closer fit to observations.
- Through use of a minimum topography field, surface temperature and
dewpoint are diagnosed at close to the station elevation in both the
and RUC-2. The minimum topography field is determined
from a high-resolution 10km topography field, with the value for the
grid box being the minimum 10km elevation, which is
of valley elevations in rough terrain. The rationale is that
surface stations in
mountainous areas are usually located in valleys or open parks at
- The reduction from the model topography to the minimum topography is done
using the model lapse rate limited to be between the dry adiabatic and
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.
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.
4. ONE-HOUR ASSIMILATION CYCLE FOR RUC-2
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,
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.
5. RUC-2 FORECAST MODEL
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
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
5.a. Basic dynamics/numerics
Here are some of the basic numerical characteristics of the RUC-2 model:
The atmospheric prognostic variables of the RUC-2 forecast model are:
- 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
The soil prognostic variables (at six levels) 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
Other surface-related prognostic variables are snow water equivalent moisture
and snow temperature.
- soil temperature
- soil volumetric moisture content
5.b. Physical parameterizations