Abstract : The objective of this work is to provide the best estimation of physical state of the Great Lakes using the two-way coupled Great Lakes-Atmosphere Regional Model (GLARM) integrated with Data Assimilation (DA) methodology. The aim of the first part is to understand the lake internal process that determines the relationship between lake surface temperature (LST) and lake thermal variations. A 3-D hydrodynamic model was used to examine the nonlinear processes of water mixing and ice formation that caused changes in lake heat content and further variation of LST. The results show that heat content trends do not necessarily follow (and can even be opposed to) trends in LST. In addition, the lake total lake heat content, thermal properties, length of stratification periods, and lake stability intensity were analyzed using validated GLARM 3-D results from 1983-2016. Furthermore, the lake thermal variations were analyzed using physical stability indices. The results reveal that climate change would not only affect the air-lake energy exchange but can also alter lake internal dynamics. In the second part, a Great Lakes forecast system with both long-term and short-term predictions is presented. A downscaled, robust, and sophisticated two-way coupled GLARM model was used to project the climate change over the Great Lakes region over the periods of 2030 - 2050 and 2080 - 2100. Two Representative Concentration Pathway (RCP) emissions scenarios (RCP4.5, RCP8.5) were included. As a result, the stress in air temperature and precipitation during the period of 2080 - 2100 under the high emission scenario (RCP8.5) will be exacerbated with larger spatial variability compared with the medium emission scenario (RCP4.5). For lake conditions, annual mean LST of Lake Erie shows the largest changes among the five lakes. The decrease in the mean lake ice coverage is projected over all the five lakes, while the largest decrease occurs along the coast. Furthermore, the application of DA using Lake Erie as a case study was evaluated. The results show that DA can effectively improve the model performance with limited observational data. The data assimilative model also improves forecasting accuracy and restrains the forecasting uncertainty to an acceptable level on a timescale of 1-7 days after unleashed from DA.

Abstract : The Great Lakes of North America are the largest surface freshwater system in the world and many ecosystems, industries, and coastal processes are sensitive to the changes in their water levels. The recent changes in the Great Lakes climate and water levels have particularly highlighted the importance of water level prediction. The water levels of the Great Lakes are primarily governed by the net basin supplies (NBS) of each lake which are the sum of over-lake precipitation and basin runoff minus lake evaporation. Recent studies have utilized Regional Climate Models (RCMs) with a fully coupled one-dimensional (1D) lake model to predict the future NBS, and the Coordinated Great Lakes Regulating and Routing Model (CGLRRM) has been used to predict the future water levels. However, multiple studies have emphasized the need for a three-dimensional (3D) lake model to accurately simulate the Great Lakes water budget. Therefore, in this study, we used the Great Lakes-Atmosphere Regional Model (GLARM) along with the Large Basin Runoff Model (LBRM) and CGLRRM to predict the changes in NBS and water levels by the mid- and late twenty-first century. GLARM is a 3D regional climate modeling system for the Great Lakes region that is fully coupled to a 3D hydrodynamic lake and ice model. This is the first study to use such an advanced model for water level prediction in the Great Lakes. We found that both annual over-lake precipitation and basin runoff are most likely to increase into the future. We also found that annual lake evaporation is most likely to decrease in Lake Superior but increase in all the other lakes. We posit that the decreases in evaporation are due to decreased wind speed over the lakes and decreased difference between saturated and actual specific humidity over the lakes. Our predicted changes in the three components of NBS would lead to mostly increased NBS and water levels in the future. The ensemble average of our predicted water level changes for Lake Superior, Michigan-Huron, and Erie are +0.14 m, +0.37 m, and +0.23 m by the mid-twenty-first century, respectively, and +0.47 m, +1.29 m, and +0.80 m by the late twenty-first century, respectively. However, due to the multiple sources of uncertainties associated with climate modeling and predictions, the water level predictions from this study should not be viewed as exact predictions. These predictions are unique to our model configuration and methodology. Other studies can easily predict different water level changes through the use of different models and methodologies. Therefore, more predictions from advanced modeling systems like GLARM are needed to generate a consensus on future water level changes in the Great Lakes.

The Laurentian Great Lakes are a tremendous freshwater resource, holding approximately 20% of the world's unfrozen freshwater. With a combined surface area of 244,000 km2, the Great Lakes are constantly interacting with the overlying atmosphere through fluxes of heat, moisture, and momentum. In the current study, we explore interactions between the Great Lakes and overlying atmosphere using a combination of observational and modeling tools. Results based on historical observations indicate that over-lake precipitation from the Lake Superior watershed is associated with transient Rossby waves during each month of the year. Further analysis indicates the origin and path of these waves change with the background flow. During summer and early fall, the Pacific jet is relatively sharp and acts as a waveguide, such that Rossby wave trains traversing the Great Lakes region do not follow a great-circle path. While the atmosphere primarily dictates hydrology in the Great Lakes basin, each of the Great Lakes feeds back on the overlying atmosphere, ultimately influencing the local and regional climate. Historical observational and modeling studies support this claim; however, a consistent, long-term analysis of the impacts of the Great Lakes on climate has yet to be executed. In the current analysis, the influence of the Great Lakes on climate is assessed by comparing two decade-long regional climate simulations, with the lakes present or replaced by woodland. Model results indicate the Great Lakes dampen seasonal and daily surface air temperature ranges, alter the strength and track of synoptic systems, and modify atmospheric stability. Additional analysis based on output from the regional climate model indicates that seasonal fluctuations in atmospheric stability over Lake Superior influence the ratio of over-lake to over-land precipitation. Since the current operational technique used to estimate over-lake precipitation does not account for variations in atmospheric stability, these estimates are likely too high during stable, warm-season months, and too low during less-stable or unstable, cold-season months. Collectively, results from this analysis demonstrate the significance of atmospheric forcing and lake feedbacks on hydrology and climate throughout the Great Lakes basin.

This report provides a state-of-the-art review of the climate change effects on lake hydrodynamics and water quality. Most of the engineering cases in this book deal with the ability of existing infrastructure to cope with extreme weather conditions. The case studies are intended to illustrate the advancement in modeling research on lake hydrodynamics, thermal stratification, pollutant transport, and water quality by highlighting the climate change aspects in the application of these techniques. Topics include climate and lake responses, lake thermodynamics, large-scale circulation, wind-waves on large lakes, great lakes ice cover, and water quality.

The Great Lakes exert a considerable influence on the weather of the surrounding area, causing fog, clouds, breezes, snowfall, and other lake effects. This work explains the atmospheric processes underlying the characteristic weather patterns of the region.

Daily maximum and minimum air temperatures at 25 locations on the perimeter of the Great Lakes for the period 1897 to 1977 were used to generate long term daily air temperatures and freezing and thawing degree-days (FDD's and TDD's). In addition daily, weekly, and monthly FDD's and daily TDD's were calculated for the 81 summer and 80 winter seasons between 1897 and 1877. this report describes the computational procedure and presents graphs and tables resulting from this analysis. The complete analysis is too voluminous to present in hard copy, but is available on microfilm through World Data Center A, Institure of Arcic and Alpine research, University of Colorado at Boulder, Boulder Colorado 80309.