https://hdl.handle.net/10388/14867

Hwang, Yunsung (2023) The features of MCSs in Canada and the United States using convection-permitting climate models forced by ERA5 and CMIP6, USASK Harvest - Theses and Dissertations, https://hdl.handle.net/10388/14867

Global climate models (GCMs) are tools that help us understand how the climate works and how it might change in the future. They are based on mathematical equations that describe the physical processes of the atmosphere, ocean, land and ice. The Coupled Model Intercomparison Project (CMIP) is a project that compares different GCMs and their results. Regional Climate Models (RCMs) are similar to GCMs, but they focus on a smaller area and have more details. However, RCMs rely on parameterization schemes to represent subgrid-scale processes that cannot be resolved by the model grid. Parameterization schemes introduce uncertainties and errors in the model results, especially for complex and nonlinear processes like convection and cloud formation. Convection-permitting climate models (CPCMs) are a type of RCMs that can capture small-scale weather features like thunderstorms and clouds without using parameterization schemes. By using a finer grid resolution, CPCMs can explicitly resolve these processes and reduce the uncertainties and biases from parameterization schemes. This makes CPCMs more accurate and reliable for simulating the climate and its changes. Mesoscale Convective Systems (MCSs) are large groups of thunderstorms that can produce heavy rain, hail and strong winds. They are important for the water cycle and the climate of the Rocky Mountains in Canada and the United States. The main goals of this study are to use CPCMs to 1) analyze how well they represent the long-term features of MCSs before they occur in the current climate and 2) project how these features may vary in the future under different greenhouse gas emission scenarios. This study aimed to improve our knowledge of the features of MCSs in current and future climates using CPCMs. However, the study was limited by the data availability of both the input forcing datasets and observational datasets. The study had three main objectives: 1) to understand the climatological characteristics of MCSs in the central United States (2004 - 2018), 2) to examine the regional features of MCSs over the Canadian Prairies (2009 - 2018), and 3) to project the future climate in the central United States (2076 - 2100) for summer seasons. Due to the computational resources required to run the CPCMs, the domain size and analysis period were restricted to 24 degrees in longitude and 20 degrees in latitude, respectively, as well as the summer season. This constraint prevented the study from covering longer periods or larger domains for each objective. The study analyzed meteorological parameters that represented both dynamical and thermodynamic conditions. However, it did not consider physical factors, even though the higher resolution CPCMs showed agreement with previous studies. One of the benefits of the study was that it provided detailed information about the conditions preceding convection when identifying daytime and nighttime MCSs. The findings of the study also yielded important insights into the regional features of MCSs but were extremely restricted to statistical results, lacking a comprehensive analysis of the physical aspects. However, it is essential to interpret these findings with caution, as they may not fully capture the entire range of variability and uncertainty of MCSs in different climates and regions. Furthermore, the absence of explicitly simulated convection initiation limits their physical meaning.

https://harvest.usask.ca/bitstreams/8a5ea904-9e6b-42f7-9433-168fca956a75/download