Northern Great Plains Blizzards In Past And Future Climates

Areas that reside in the high-latitudes such as the northern United States can experience hazardous conditions during the winter months due to snowstorms. When strong winds exist with falling or freshly fallen snow, blizzard conditions are able create significant personal, societal, and economic impacts for the Northern Great Plains. While the climatology for these extreme snowstorms is known, the frequency and intensity of how these events may change in a warming climate is not certain. In order to determine how extreme snowstorms may change in the future climate, climate models can be used but the horizontal and vertical grid spacing makes identifying blizzard events difficult. Moreover, climate models do not include blowing snow, which means that blizzards that don’t have any falling snow are not considered. Therefore, another method must be used in order to identify these extreme snowstorm events. The presented work will use a competitive neural network known as the Self-Organizing Map (SOM) to identify meteorological patterns associated with blizzard events over the Northern Great Plains from 1979-2015. Once these large-scale patterns are identified from observations, they will be identified in the Community Earth System Model (CESM) 4.0 20th Century forcing climate simulations run in support for the Coupled Model Intercomparison Project Phase 5 (CMIP-5). In specific, the methodology will rely on the ‘Mother of All Runs’ (MOAR) ensemble member, which allows for specific meteorological patterns to be identified. Blizzard events will be identified during historical time periods to determine biases, and then under future emissions scenarios

A Climatology of Atmospheric Patterns Associated with Red River Valley Blizzards

Stretching along the border of North Dakota and Minnesota, The Red River Valley (RRV) of the North has the highest frequency of reported blizzards within the contiguous United States. Despite the numerous impacts these events have, few systematic studies exist that discuss the meteorological properties of blizzards. As a result, forecasting these events and lesser blowing snow events is an ongoing challenge. This study presents a climatology of atmospheric patterns associated with RRV blizzards for the winter seasons of 1979-1980 and 2017-2018. Patterns were identified using subjective and objective techniques using meteorological fields from the North American Regional Re-analysis (NARR). The RRV experiences, on average, 2.6 events per year. Blizzard frequency is bimodal, with peaks occurring in December and March. The events can largely be typed into four meteorological categories dependent on the forcing that drives the blizzard: Alberta Clippers, Arctic Fronts, Colorado Lows, and Hybrids. The objective classification of these blizzards using a competitive neural network known as the Self-Organizing Map (SOM) demonstrates that gross segregation of the events can be achieved with a small (eight-class) map. This implies that objective analysis techniques can be used to identify these events in weather and climate model output that may aid future forecasting and risk assessment projects

A Climatology of Atmospheric Patterns Associated with Red River Valley Blizzards

Stretching along the border of North Dakota and Minnesota, The Red River Valley (RRV) of the North has the highest frequency of reported blizzards within the contiguous United States. Despite the numerous impacts these events have, few systematic studies exist that discuss the meteorological properties of blizzards. As a result, forecasting these events and lesser blowing snow events is an ongoing challenge. This study presents a climatology of atmospheric patterns associated with RRV blizzards for the winter seasons of 1979−1980 and 2017−2018. Patterns were identified using subjective and objective techniques using meteorological fields from the North American Regional Re-analysis (NARR). The RRV experiences, on average, 2.6 events per year. Blizzard frequency is bimodal, with peaks occurring in December and March. The events can largely be typed into four meteorological categories dependent on the forcing that drives the blizzard: Alberta Clippers, Arctic Fronts, Colorado Lows, and Hybrids. The objective classification of these blizzards using a competitive neural network known as the Self-Organizing Map (SOM) demonstrates that gross segregation of the events can be achieved with a small (eight-class) map. This implies that objective analysis techniques can be used to identify these events in weather and climate model output that may aid future forecasting and risk assessment projects