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Meteorology
CEMPD has been developing physics parameterization schemes in meteorology models and applying these models at various scales ranging from urban to intercontinental. To support air quality modeling applications, the group has a variety of capabilities in meteorology research and applications, such as:
- Develop land surface and PBL models, e.g. the Pleim-Xiu land surface
model in MM5, a PBL scheme based on Turbulence Velocity Scale
for use in MM5 and in Air Quality Models
- Surface Data Assimilation Scheme in MM5, e.g., the Flux-Adjusting Surface
Data Assimilation System (FASDAS) to develop improved meteorological
fields
- Remotely sensed data assimilation methods into MM5, e.g., Soil Moisture
Assimilation using Satellite-derived Skin Temperature Tendencies,
to improve meteorological fields
- Alternate Stomatal Resistance estimation methodologies for use in MM5
and in Air Quality Models, to improve PBL and Precipitation
simulations
- Develop an integrated modeling system with online coupled meteorology
and chemistry which enable us to investigate the direct effect
of aerosols on radiation
- Apply MM5 to intercontinental domains (Fig.
1 for trans-Pacific and Fig.
2 for trans-Atlantic) for annual simulations to investigate
intercontinental transports of air pollutants
- Investigate the role of emissions from the Indian subcontinent on regional
climate trends using the integrated modeling system (Fig.
3)
- Develop new data analysis and quality-assurance techniques. A program
was developed to calculate statistical parameters in order
to create plots to compare the model and observational values
of key meteorological variables (Fig.
4). Scripts have been developed to use PAVE to create many
data analysis graphics. For example, time series plots of key
variables comparing model and observational values at observation
stations (Fig.
5). Plots overlaying the observational value on top of
the model data have also been created using PAVE (Fig.
6). A program was also developed to display vertical soundings
from RAOB data alongside model data (Fig.
7). This was also done with virtual temperature and winds
from radar profiler data (Fig.
8).
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Figure
1. Trans-Pacific domain for MM5 simulations |
Figure
2. Trans-Atlantic domain for MM5 simulations |
Figure
3.
Simulation domain for the Indian subcontinent |
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Figure
4. Statistical plot of model and obs. Temperature |
Figure
5. Time series plot of mixing ratio at an observation station |
Figure
6. Model temperature with obs. Temperature overlaid |
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Figure
7. RAOB sounding
data compared to model data |
Figure
8. Vertical wind sounding plot from Charlotte radar profiler
compared to model data |
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Relevant Projects
Collaborative Research: Evaluation of a Coupled Meteorology-Chemistry Model against Long-term Measurements of Elemental Carbon and Sulfate for Regional Climate Applications
