Climate change studies are crucial to assist decision-makers in understanding future risks and planning adequate adaptation measures. In general, Global/Regional Climate Models (GCMs/RCMs) achieve coarse resolutions, and are thus unable to provide sufficient information to conduct local climate assessments. Downscaling, defined as a method that derives local to regional-scale (10 to 100 km) information from larger-scale models or data analyses, is used to address this deficiency. In this thesis, a particular downscaling technique, known as the Quantile-Quantile transformation, was used to adjust the statistical distribution of RCM variables to match the statistical distribution of the observed variables generated by two RCMs: the Canadian R...
© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.Natur...
The future climate impact studies rely on future projections obtained from downscaling of Coupled Mo...
AbstractIn this work we perform a statistical downscaling by applying a CDF transformation function ...
Climate change studies are crucial to assist decision-makers in understanding future risks and plann...
Large-scale general circulation models give us an idea of how the climate may possibly develop over ...
This study aims to provide a deeper understanding of the level of uncertainty associated with the de...
Development of local climate is important for climate hazard assessment. Cameron Highlands was chose...
AbstractThis study aims to provide a deeper understanding of the level of uncertainty associated wit...
This study evaluates statistical downscaling techniques using different metrics and compares climate...
In this work we perform a statistical downscaling by applying a CDF transformation function to local...
Study region: An analysis of hydrological response to a dynamically downscaled multi-member multi-mo...
Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potenti...
The primary tools to assess climate change are the Atmosphere–Ocean General Circulation Model (AOGCM...
This study examined the impact of model biases on climate change signals for daily precipitation and...
Recent global warming has caused significant changes to the regional climate over Eastern Canada and...
© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.Natur...
The future climate impact studies rely on future projections obtained from downscaling of Coupled Mo...
AbstractIn this work we perform a statistical downscaling by applying a CDF transformation function ...
Climate change studies are crucial to assist decision-makers in understanding future risks and plann...
Large-scale general circulation models give us an idea of how the climate may possibly develop over ...
This study aims to provide a deeper understanding of the level of uncertainty associated with the de...
Development of local climate is important for climate hazard assessment. Cameron Highlands was chose...
AbstractThis study aims to provide a deeper understanding of the level of uncertainty associated wit...
This study evaluates statistical downscaling techniques using different metrics and compares climate...
In this work we perform a statistical downscaling by applying a CDF transformation function to local...
Study region: An analysis of hydrological response to a dynamically downscaled multi-member multi-mo...
Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potenti...
The primary tools to assess climate change are the Atmosphere–Ocean General Circulation Model (AOGCM...
This study examined the impact of model biases on climate change signals for daily precipitation and...
Recent global warming has caused significant changes to the regional climate over Eastern Canada and...
© Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License.Natur...
The future climate impact studies rely on future projections obtained from downscaling of Coupled Mo...
AbstractIn this work we perform a statistical downscaling by applying a CDF transformation function ...