dc.contributor | Silva, Cláudio Moisés Santos e | |
dc.contributor | | |
dc.contributor | | |
dc.contributor | Santos, Alexandre Torres Silva dos | |
dc.contributor | | |
dc.contributor | Gonçalves, Weber Andrade | |
dc.contributor | | |
dc.creator | Ferreira, Moniki Dara de Melo | |
dc.date.accessioned | 2020-09-09T18:40:04Z | |
dc.date.accessioned | 2022-10-06T13:15:56Z | |
dc.date.available | 2020-09-09T18:40:04Z | |
dc.date.available | 2022-10-06T13:15:56Z | |
dc.date.created | 2020-09-09T18:40:04Z | |
dc.date.issued | 2020-05-15 | |
dc.identifier | FERREIRA, Moniki Dara de Melo. Estudo da velocidade do vento através de downscaling dinâmico em alta resolução sobre terreno complexo no Nordeste do Brasil. 2020. 76f. Dissertação (Mestrado em Ciências Climáticas) - Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, 2020. | |
dc.identifier | https://repositorio.ufrn.br/jspui/handle/123456789/29999 | |
dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3966216 | |
dc.description.abstract | Using advanced tools in wind flow modeling based on Numerical Weather Prediction (NWP)
is essential for wind projects, since these techniques help to get a depth knowledge about the
wind pattern within any geographical area. Dynamical downscaling is widely used in mesoscale
models: a grid nesting method used to perform atmospheric simulations in high resolution at a
low computational cost. In this work, we run numerical simulation using the mesoscale model
Weather Research and Forecasting (WRF) for a nesting process of three grids in order to
produce a high-resolution simulation in terrain area complex. For a performance test, we use a
set of observed wind speed and air temperature data through August 2005 and it was obtained
from an anemometric tower (50 meters) located in Belo Jardim/PE. In the validation
methodology, statistical metrics such as the root mean square error, the standard deviation and
Pearson's correlation were calculated between the observed and simulated datasets. Results
show that using different grid nesting configurations significantly interferes the performance of
the mesoscale model in representing the phenomena in the study region. Observational mean
hourly data and the grid 01 showed an RMSE between 1.2 to 1.4 mps and a standard deviation
around 0.97 to 1.9 mps. Grid 02 had a RMSE between 0.85 to 1.9 mps and a standard deviation
ranging 0.85 to 1.3 mps. Grid 03 got a RMSE approximately 0.9 to 1.6 mps and a standard
deviation of 0.75 to 1.1 mps. The lowest RMSE for all spacing grids was found at 4 pm local
time. Overall, the wind speed diurnal cycle of grid 01 performed better during the first hours of
the day and at night. This domain dimension can influence the results performance, since it
inserts more information about the adjacent regions, predominating over the simulation of local
winds. In the central hours of the day, the simulated wind speed was overestimated due to a
higher estimate of the turbulence from the model, and during the night, it was underestimated.
It is likely that the vertical temperature profiles may be more difficult to represent by the model
due to its more stratified nature and, therefore, the turbulent flows estimated at this time of day. | |
dc.publisher | Universidade Federal do Rio Grande do Norte | |
dc.publisher | Brasil | |
dc.publisher | UFRN | |
dc.publisher | PROGRAMA DE PÓS-GRADUAÇÃO EM CIÊNCIAS CLIMÁTICAS | |
dc.rights | Acesso Aberto | |
dc.subject | Velocidade do vento | |
dc.subject | Modelagem de mesoescala | |
dc.subject | Regionalização dinâmica | |
dc.subject | Energia eólica | |
dc.title | Estudo da velocidade do vento através de downscaling dinâmico em alta resolução sobre terreno complexo no Nordeste do Brasil | |
dc.type | masterThesis | |