Over the last two decades, the Laurentian Great Lakes have experienced both extreme low and unprecedented high water levels. These events have renewed interest among regional stakeholders in revised water level design guidance to support resilient infrastructure investment, as well as water level scenario development to explore future system vulnerabilities. In response to this need, the Great Lakes Restoration Initiative (GLRI) convened a multidisciplinary team of Great Lakes scientists and engineers to develop a novel water level simulation framework under climate change uncertainty that provides design guidance for alternative climate scenarios, as well as a large ensemble of climate and hydrologic scenarios for exploratory modeling and impacts assessment. The framework is composed of an ensemble of long-term (1000-year) net basin supply (NBS) series, developed by coupling a stochastic weather generator with runoff and evaporation models for each of the Great Lakes, which are then coupled with lake hydrodynamic models that capture fine scale coastal processes. This report focuses on one module of this model workflow - the stochastic weather generator – and how it is used within the broader modeling framework. The weather generator is organized around the identification and simulation of synoptic weather regimes (WRs), or large-scale patterns of atmospheric circulation, that account for the seasonal and interannual persistence of regional weather. The weather generator uses WR simulations as the basis to simulate a suite of daily meteorological variables, including precipitation, air and dew point temperatures, wind speeds, and cloud cover across the Great Lakes, their contributing watersheds, and other regions within the St. Lawrence River basin. Output from the model is then systematically perturbed to capture warming, changes in the mean and seasonality of precipitation, and extreme precipitation-temperature scaling relationships consistent with recent projections from the Coupled Model Intercomparison Project 6 (CMIP6). This report documents the calibration and validation of the weather generator model and summarizes an ensemble of future climate scenarios created with the model. Ultimately, climate scenarios from the stochastic weather generator are passed through runoff, evaporation, and routing and regulation models of the Great Lakes to simulate lake level response. Water level simulations will be combined with future scenarios of seiche and storm surge to quantify the likelihood of total water level extremes under climate variability and change. The resulting database will provide new guidance for resilient infrastructure design along the Great Lakes shoreline under different scenarios of climate change, as well as the likelihood of those scenarios at different planning horizons.