Evaluation of RAMS Turbulence Predictions
over the Chesapeake Bay
Overview
Mesoscale model simulations have been compared against
observed winds, temperature and moisture for various atmospheric
conditions including sea breeze flows, around fronts, and
in complex terrain. For this study, the utility of the ARL
version of the Regional Atmospheric Modeling System 3a
(RAMS) for computing air pollutant deposition velocity
(Vd) onto water surfaces was evaluated.The RAMS, developed
at Colorado State University , was used to simulate mesoscale
atmospheric circulations on two IBM/6000 workstations at
ARL(McQueen, et al., 1995). Special ARL software allows
the user to setup and initialize RAMS anywhere in the world
using gridded meteorological fields and global land and
water surface data sets. Pollutant deposition onto water
is dependent on the heat and moisture fluxes from the surface
and by several turbulence variables, therefore these parameters
were evaluated along with the atmospheric state variables.
Valigura (1995) estimated heat fluxes over the Chesapeake
Bay to compute deposition velocity of nitric acid (HNO3)
by using measurements at several levels from specially
designed buoys. This database was used to evaluate various
RAMS flux and turbulence variables, over the Chesapeake
Bay Observing System (CBOS) buoy. These results helped
determine the RAMS settings needed to predict parameters
that control coastal dispersion and deposition over the
water accurately. An objective trajectory cluster analysis
formed the basis of the criteria used to select cases for
study in this investigation. The trajectories beginning
at each altitude were clustered separately following Stunder
(1996).
Click HERE for a gif movie
of a 2 km RAMS Chesapeake Bay simulation.
Research Results
This study examined the ability of a mesoscale model
to compute surface turbulence and flux variables over water
with the accuracy needed for air pollution studies. Sensible
heat fluxes and deposition velocities (Fig. 1) compared
well with observations when the model horizontal resolution
was reduced to 5 km or less and the first model level were
12 m. Other turbulent variables compared poorly especially
under stable stratifications.
Figure 1. Sensible heat flux (left) and deposition
velocity (right) time-series for various horizontal resolution
experiments.
Overall, latent heat fluxes were significantly underpredicted
even with finer resolutions. Results degraded when the
effects of clouds on short- and long-wave radiation were
incorporated. Latent fluxes were also insensitive to increasing
the initial sea surface temperature (SST) over the observed
daytime range (1 C), and to using an improved roughness
length parameterization over water. Errors were much larger
during stably stratified conditions, therefore, substantial
underprediction of pollutants to the bay would be expected
by RAMS during these conditions. However, RAMS would be
a reliable predictor of fluxes and deposition velocity
during unstable conditions.
Further experiments were performed to help explain the
poor predictions during the daytime for stable conditions.
Latent heat fluxes over water were strongly sensitive to
the soil moisture content of the surrounding land masses
for stable atmospheric conditions and improved when geostrophic
forcing terms were added to the momentum equations (Fig.
2).
Figure 2. Latent heat flux time-series averaged
for all stably stratified case.
References
McQueen, J.T., R.A. Valigura and B.J.B. Stunder, 1997:
Evaluation of the RAMS Model for estimating deposition
velocity onto the Chesapeake Bay. Atmos. Envir., (In Press).
McQueen, J.T., R.A. Valigura and B.J.B. Stunder, 1997:
Evaluation of surface flux and turbulence predictions over
the Chesapeake Bay from a mesoscale model,13th Conference
on Hydrology. 77th Meeting of the Amer. Meteor. Soc., Long
Beach, CA, 62-65.
McQueen, J.T., R.R. Draxler and G.D. Rolph, 1995: Influence
of grid size and terrain resolution on wind field predictions
from an operational mesoscale model. J. Appl. Meteor. ,34,
2166-2181.
Stunder, B.J.B., 1996: An assessment of the quality of
forecast trajectories. J. Appl. Meteor., 35, 1319-1331.
Valigura, R.A., 1995: Iterative bulk exchange model for
estimating air-water transfer of HNO3. J. Geophys. Res.,
100, 26045-26050.
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