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dc.contributor.advisorChen, Yongsheng
dc.contributor.advisorHuang, Gordon
dc.contributor.advisorLiu, John
dc.creatorYu, Zhongqi
dc.date.accessioned2016-09-13T13:15:44Z
dc.date.available2016-09-13T13:15:44Z
dc.date.copyright2013-08
dc.identifier.urihttp://hdl.handle.net/10315/32034
dc.description.abstractGlobal climate models (GCMs) are widely used to study climate change. Due to their coarse resolutions, GCMs cannot resolve some microscale and mesoscale processes such as topographical effects. Dynamic downscaling simulations using Regional Climate Models (RCMs) are often required to provide higher spatial- and temporal-resolution climate variabilities in specific regions. Uncertainties in dynamic downscaling simulations due to errors in the atmospheric state and models need to be understood first in the present climate simulations. Then the reliability for future projections can be inferred. This research contains three parts. The first part gives an assessment of temperature and precipitation over Ontario based on the North American Regional Climate Change Assessment Program (NARCCAP) RCM simulation data. In part two, five 8-year downscaling simulations using the Weather Research and Forecasting (WRF) model driven by five NARCCAP model data over Ontario are studied. Each of these simulation results and their mean are analyzed to address the dynamic downscaling effect on temperature and precipitation and their variabilities. Lastly in the third part, a 14-member perturbed ensemble simulation using the WRF model was conducted. The ensemble means of temperature and precipitation are evaluated and the uncertainties in regional climate modeling are discussed. The temperature and precipitation in seven NARCCAP RCM simulations from 1979 to 2004 are compared to the observations over Ontario. The observed annual area mean temperature has a remarkable rising trend in the late 1990s after decades of fluctuation. It is mainly due to a significant rise of winter area mean temperature during that period. This rising trend has been revealed in all seven models. For the annual area mean precipitation, the observed values fluctuate during this period, and the NARCCAP RCM model simulations show larger discrepancies. One focus of this thesis is to assess the impact of increased model resolution on regional climate simulations. Five NARCCAP RCM (MM5I, RCM3, HRM3, CRCM and WRFG) simulation data with 50-km horizontal resolution are downscaled to 10-km horizontal grid over Ontario to provide initial and boundary conditions for the WRF downscaling simulations in the period from 1991 to 1998. The model results show that the high resolution has great impact on regional climate simulations. Three sets of ensembles, the seven-member NARCCAP RCM simulations, the five-member WRF downscaling simulations, and a 14-member perturbed ensemble simulations using WRF model with the stochastic kinetic energy backscatter scheme are analyzed to assess the performance of the ensemble approach in regional climate simulations. The ensemble mean temperature and precipitation are compared to reanalysis data and the observations. The root mean square errors (RMSE) and the correlations are calculated. The results show that the ensemble method improves the accuracy of simulations, for both temperature and precipitation.
dc.rightsAuthor owns copyright, except where explicitly noted. Please contact the author directly with licensing requests.
dc.titleRegional climate modeling over Ontario using the WRF model
dc.typeElectronic Thesis or Dissertation
dc.degree.disciplineEarth & Space Science
dc.degree.nameMSc - Master of Science
dc.degree.levelMaster's
dc.subject.keywordsRegional climate models
dc.subject.keywordsRCMs
dc.subject.keywordsWeather research and forecasting
dc.subject.keywordsWRF
dc.subject.keywordsNorth American Regional Climate Change Assessment Program
dc.subject.keywordsNARCCAP
dc.subject.keywordsOntario


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