Forecasters, climatologists, social scientists, and stakeholders are collaborating to develop new methods of weather prediction tailored to the needs of people living and working in the North.
Our goal is to enable safer and more cost-effective planning, operations, and response—to improve life in this dynamic environment. Better prediction products can reduce risk from extreme weather and environmental hazards. They can also increase economic opportunity through more accurate prediction of environmental processes.
Alaska Blocking Index— enables inferences about upcoming Alaska weather patterns. Learn more about the Alaska Blocking Index
Analog Forecasting—useful in sea ice work, seasonal fire outlooks, marine shipping, tourism, and the oil and gas industry. Learn more about analog forecasting
Wildfire Build-Up Index—used to assess fire danger and create seasonal fire outlooks. Learn more about the Wildfire Build-Up Index
Improve existing forecasting and prediction products by conducting needs assessments to determine how users find, consume, and make decisions based on weather prediction products.
Act as liaison between managers, planners, industry, and the science community to ensure that prediction products meet the unique needs of stakeholders.
Nathan Kettle, Research Assistant Professor, UAF International Arctic Research Center
The Alaska Blocking Index (ABI) assigns one value, based on pressure in the middle atmosphere, that can be used to predict weather-related events likely to impact Alaska in the coming weeks or months. This tool is currently under development.
How the ABI connects to weather: Similar to the phases of the El Niño Southern Oscillation, the ABI enables forecasters to make inferences about regional weather patterns likely to occur in the coming weeks to months.
When the ABI is positive, high pressure is overhead. Storms are “blocked” from the region; clear skies and calm weather persist. When the index is negative, low pressure is overhead, driving cloudy conditions and storms.
We are working to link specific ABI values to weather-related events that people care about, such as temperature extremes, rain or snow, location of the sea ice edge, open water duration, break-up and freeze-up, and conditions linked to wildfire.
Where is the science now? The ABI is currently defined on a monthly scale, 1948 to present. This historical record offers a way to compare ABI values to known weather, and to explore trends as well as seasonal and year-to-year variability. Future work will devine the index at a daily scale, potentially back to the mid-1800s. Important questions to consider are:
What is the range and accuracy of predictions based on the ABI?
What is the link between ABI values and specific weather, and between regional to hemispheric weather patterns?
Can the Alaska Blocking index help you? In the future, we will work with stakeholders to tailor ABI applications to the unique challenges and hazards that threaten Northern infrastructure, and impact communities and operations. These could include Bering Sea crabbers interested in predicting the location of the ice edge, or communities looking to better time contracts for snow removal.
Tom Ballinger, Research Assistant Professor, UAF International Arctic Research Center
Analog forecasts compare the evolution of current atmospheric conditions to past years where users may have personal experience to draw from.
On-the-ground experience is an excellent starting point for decisive action. We have developed a new forecasting technique at the nexus of science and experience-based decision-making. The analog forecasting technique examines forecasts that are days, months, or a year into the future and looks for a time in the past when the weather scenario looked very similar (an analog).
Analog forecasting has many applications. From wildfire management to storm readiness, analog forecasting is useful anytime people can benefit from knowing when today’s conditions are similar to a time in the past.
The United States Navy taps into past experience. Our team provides daily analog forecasts to the U.S. Navy during their biannual ice exercises, known as ICEX, in the Arctic Ocean. The forecasts aim to provide advance notice of potential ice and weather hazards that could impact under-ice submarine activity or the temporary ice camp housing support staff.
To supply the forecasts, sea ice and atmospheric conditions that led to past hazards are analyzed. For example, a crack in the ice damaged a runway that had been used in a previous exercise. The forecast team analyzed the air pressure driving the winds that moved and cracked the ice. Forecasters search for developing atmospheric conditions that are similar. When matches arise, Navy personnel apply their experience responding to past hazards to make faster, safer decisions about the future.
A tool to streamline analog forecasting. To streamline analog forecasting, EAPI and the Scenarios Network for Alaska + Arctic Planning produced a web tool to identify best analogs back to 1949 for six atmospheric variables, including precipitation and sea level pressure. The tool then provides a forecast based on how the weather patterns evolved in those analog years.
Users specify the areas from which the analogs are determined, such as the tropics, where ocean temperatures and pressures can correlate with future weather in Alaska. The tool is designed for forecasting professionals and others with experience using climate data for planning.
The Wildfire Build-up Index is used in Alaska and Canada to assess fuel moisture level and wildfire danger.
We work with Alaska wildfire managers to predict the index for the coming fire season. This seasonal outlook for the build-up index is used to prepare resources and personnel. The higher the Wildfire Build-Up Index, the hotter and drier the fuels. As the season progresses, the value “builds” until rain reduces it.
The index helps increase preparedness. In the past, fire managers used the index to predict fire activity a few days out. Our team is now helping to provide an outlook of the build-up index months before the season starts. To do so, seasonal weather forecast models explore how the index varies under past known weather and climate conditions. Where model predictions are consistently too wet, or too hot, the model is corrected to account for the difference. Even with these adjustments, predicting the index three months into the future remains difficult.
Model accuracy can be improved by understanding how slowly varying parts of the climate system—such as sea surface temperatures and sea ice—contribute to Alaska fire weather.
Uma Bhatt, Professor, Department of Atmospheric Sciences, UAF Geophysical Institute
Are you interested in collaborating on approaches to forecasting that use the best science? Do you have expertise in decision-making under uncertainty? Please get in touch.