IMPACT OF THE WRF METEOROLOGICAL MODELING COUPLING WITH MICROSCALE CFD MODELING ON THE WIND FIELD STUDY INSIDE A URBAN CANOPY
Name: Felipe Simões Maciel
Type: MSc dissertation
Publication date: 19/02/2020
Advisor:
Name | Role |
---|---|
Neyval Costa Reis Jr. | Advisor * |
Examining board:
Name | Role |
---|---|
Elisa Valentim Goulart | Co advisor * |
Jane Meri Santos | Internal Examiner * |
Murilo Pereira de Almeida | External Examiner * |
Neyval Costa Reis Jr. | Advisor * |
Summary: The present work investigates the impact of the use of mesoscale meteorological model data
coupled as boundary conditions for microscale CFD (Computational Fluid Dynamics) models
for a real urban area. Numerical simulations were performed using CFD considering transient
input data from the WRF model and from the fixed weather station. The geometry studied is
based on a real urban area of Metropolitan Region of Vitória, in Brazil. The microscale CFD
modeling consists of solving the mass and momentum conservation equations for transient
flow, on a discretized domain formed by 3D hexahedral mesh. The standard k-ε model was
used for the treatment of turbulence. The coupling of wind speed and direction data from the
mesoscale model (considering the macroscopic dynamics of the atmosphere) is carried out by
using a User Defined Function (UDF), which basically reads output data from the WRF
simulations and creates boundary conditions for the microscale CFD simulations. The same
UDF was used to couple data from Vitória Airport weather station as input data for CFD
domain. In order to evaluate the accuracy of the simulations, a 16 days field campaign was
also conducted to measure wind speed and direction at three points within the neighborhood.
The considerable gain was observed comparing WRF results with CFD-WRF coupling results
at the monitoring points. The velocity and direction values from the simulations follow a
trend similar to the data measured in the field and are in accordance with commonly used
acceptance criteria. For the case with airport station data as an entry condition, there is a
significantly greater agreement between the data. This is due to the better quality of input data
provided by the airport meteorological station. The result of microscale modeling using
mesoscale data is shown to be sensitive to the quality of the input data, since the better
agreement between the results is observed in periods of better WRF data quality. Also, good
results were obtained from the use of measured data as input for the CFD model. Using data
from mesoscale models such as WRF is a viable option for studying wind field modeling and
pollutant dispersion in areas WHERE meteorological measurement stations are not available.