The Role of Ice Cover in Heavy Lake-Effect Snowstorms over the Great Lakes Basin as Simulated by RegCM4

Abstract

A 20-km regional climate model, the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 4 (ICTP RegCM4), is employed to investigate heavy lake-effect snowfall (HLES) over the Great Lakes Basin and the role of ice cover in regulating these events. When coupled to a lake model and driven with atmospheric reanalysis data between 1976 and 2002, RegCM4 reproduces the major characteristics of HLES. The influence of lake ice cover on HLES is investigated through 10 case studies (2 per Great Lake), in which a simulated heavy lake-effect event is compared with a companion simulation having 100% ice cover imposed on one or all of the Great Lakes. These experiments quantify the impact of ice cover on downstream snowfall and demonstrate that Lake Superior has the strongest, most widespread influence on heavy snowfall and Lake Ontario the least. Ice cover strongly affects a wide range of atmospheric variables above and downstream of lakes during HLES, including snowfall, surface energy fluxes, wind speed, temperature, moisture, clouds, and air pressure. Averaged among the 10 events, complete ice coverage causes major reductions in lake-effect snowfall (>80%) and turbulent heat fluxes over the lakes (>90%), less low cloudiness, lower temperatures, and higher air pressure. Another important consequence is a consistent weakening (30%–40%) of lower-tropospheric winds over the lakes when completely frozen. This momentum reduction further decreases over-lake evaporation and weakens downstream wind convergence, thus mitigating lake-effect snowfall. This finding suggests a secondary, dynamical mechanism by which ice cover affects downstream snowfall during HLES events, in addition to the more widely recognized thermodynamic influence.

Improving Climate Sensitivity of Deep Lakes within a Regional Climate Model and Its Impact on Simulated Climate

“…Although many multiyear regional climate model simulations now include interactive lake models (Lofgren 2002;Holman et al 2012;Vavrus et al 2013), there has been little effort to evaluate deep lake model performance within coupled regional climate models beyond a 10-day simulation (Hostetler et al 1993), particularly the lake's physical structure and ability to capture observed variability. When a study is explicitly focused on variability and/or trends, the lake model must capture year-to-year variability in temperature and ice cover to accurately simulate local climate features impacted by lake conditions (i.e., lake-effect snow).…”

“…When a study is explicitly focused on variability and/or trends, the lake model must capture year-to-year variability in temperature and ice cover to accurately simulate local climate features impacted by lake conditions (i.e., lake-effect snow). The Hostetler model is used in both offline and coupled lake simulations (Notaro et al 2013a,b;Vavrus et al 2013;Bates et al 1995;Bonan 1995;Hostetler and Bartlein 1990;Hostetler et al 1994;Stepanenko et al 2010), as well as in global climate models as part of the land surface component. The Hostetler model is used in both offline and coupled lake simulations (Notaro et al 2013a,b;Vavrus et al 2013;Bates et al 1995;Bonan 1995;Hostetler and Bartlein 1990;Hostetler et al 1994;Stepanenko et al 2010), as well as in global climate models as part of the land surface component.…”

The role of meteorological processes in the description of uncertainty for climate change decision-making

“…In the western USA, RCM simulations have not shown large improvement over the BCSD method (Wood et al 2004), but in the Great Lakes region, the dynamic interaction of the lakes with local and regional climate requires higherresolution modeling of the system (Gula and Peltier 2012;Notaro et al 2013b;Wright et al 2012). Recent modeling studies where lake models have been coupled to RCMs are advancing our understanding of complex precipitation processes in the Great Lakes region (Notaro et al 2013a;Notaro et al 2013b;Vavrus et al 2013). Better representation of processes in the models allows projected climate changes to be physically explained, and practitioners can use that information to systematically think about climate impacts (Rood and Team 2014).…”

Modeling the Impacts of a Man-Made Lake on the Meteorological Conditions of the Surrounding Areas

“…These studies point to the importance of the ratio of wind speed U to maximum fetch distance L in determining the morphology of lake-effect circulation for both circular (Laird et al 2003a) and elliptical (Laird et al 2003b) lakes. These observational (Laird et al 2009(Laird et al , 2010Alcott et al 2012;Workoff et al 2012) and modeling Vavrus et al 2013;Wright et al 2013) studies focus on the frequency and environmental conditions favorable for the occurrence of lake-effect precipitation events. 2) Case studies of observed lake-effect precipitation events.…”

“…Additionally, modeling studies discussed above addressed either idealized (Laird et al 2003a,b;Crosman and Horel 2012) or substantially larger real lakes (Harris and Kotamarthi 2005;Sills et al 2011;Vavrus et al 2013;Wright et al 2013), whereas we look at a small, real lake. While previous studies were focused on specific seasonal mesoscale phenomena (either wintertime lake-effect precipitation event or summertime lake-breeze event), here we consider both cold and warm seasons.…”