Noéle Bissoli Perini Souza, E. G. S. Nascimento, D. Moreira
{"title":"Performance evaluation of the WRF model in a tropical region: wind speed analysis at different sites","authors":"Noéle Bissoli Perini Souza, E. G. S. Nascimento, D. Moreira","doi":"10.20937/atm.52968","DOIUrl":null,"url":null,"abstract":"In this study, the performance of the mesoscale Weather Research and Forecasting (WRF) model is evaluated using combinations of three Planetary Boundary Layer (PBL) and three Land Surface Model (LSM) schemes, in order to identify the optimal parameters for the determination of wind speed in a tropical region. The state of Bahia in Brazil is selected as the location for the case study and simulations are performed over a period of eight months between 2015 and 2016. This is done to ensure that the dry and rainy seasons at the three different experimental sites—Esplanada, Mucuri, and Mucugê—are well separated from each other. The results of the simulations are compared with the observational data obtained from three towers equipped with anemometers at heights of 80, 100, 120 and 150 m, strategically placed at each site. Overestimation of wind speed is observed in the simulations, despite similarities between the simulated and observed wind directions. In addition, the accuracies of simulations corresponding to sites that are closer to the ocean are observed to be lower—the most accurate wind speed estimates are obtained corresponding to Mucugê, which is located farthest from the ocean. Finally, analysis of the results obtained from each tower accounting for periods with higher and lower precipitation reveals that the combination of the PBL-YSU scheme with the LSM-RUC scheme yields the best results.","PeriodicalId":55576,"journal":{"name":"Atmosfera","volume":" ","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2021-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmosfera","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.20937/atm.52968","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 3
Abstract
In this study, the performance of the mesoscale Weather Research and Forecasting (WRF) model is evaluated using combinations of three Planetary Boundary Layer (PBL) and three Land Surface Model (LSM) schemes, in order to identify the optimal parameters for the determination of wind speed in a tropical region. The state of Bahia in Brazil is selected as the location for the case study and simulations are performed over a period of eight months between 2015 and 2016. This is done to ensure that the dry and rainy seasons at the three different experimental sites—Esplanada, Mucuri, and Mucugê—are well separated from each other. The results of the simulations are compared with the observational data obtained from three towers equipped with anemometers at heights of 80, 100, 120 and 150 m, strategically placed at each site. Overestimation of wind speed is observed in the simulations, despite similarities between the simulated and observed wind directions. In addition, the accuracies of simulations corresponding to sites that are closer to the ocean are observed to be lower—the most accurate wind speed estimates are obtained corresponding to Mucugê, which is located farthest from the ocean. Finally, analysis of the results obtained from each tower accounting for periods with higher and lower precipitation reveals that the combination of the PBL-YSU scheme with the LSM-RUC scheme yields the best results.
期刊介绍:
ATMÓSFERA seeks contributions on theoretical, basic, empirical and applied research in all the areas of atmospheric sciences, with emphasis on meteorology, climatology, aeronomy, physics, chemistry, and aerobiology. Interdisciplinary contributions are also accepted; especially those related with oceanography, hydrology, climate variability and change, ecology, forestry, glaciology, agriculture, environmental pollution, and other topics related to economy and society as they are affected by atmospheric hazards.