Research

SD-RET Research Project Example 4:

Climate Change in the Northern Great Plains

Research mentor:Dr. Bill Capehart, Atmospheric and Environmental Sciences, Department of Civil & Environmental Engineering.

Lab Overview: With climate change, temperature, precipitation and other weather patterns have changed over the US with notable changes in extreme event frequency in some regions. For example, Maryland has experienced two “1000-year return” flooding events in as many (i.e., two) years. Many of the observable changes to our climate are subtler, with long-term extreme events drifting to shorter return periods, e.g., a 20-year-repeat storm event drifting to a 15-year return period. These subtler or “nuisance” events occur more often than the 100- 500- or 1000- year events have been statistically shown to create overall economic impacts on parity with the headline-grabbing major events.

This presents scientists and engineers with the challenge of not only recalibrating our expectations of how changing climate impacts the extreme events that “break” systems, but also our ability to articulate these changes and related statistics to end-users, policy makers and the general public.

We currently project future climate using model ensembles, multiple simulations of the same general scenario with each simulation member slightly different the others. This ensemble of model runs produces a spectrum of possible future outcomes. The resulting output can then be used to generate a probabilistic spread of means and extremes that can give insight on how our “normal” expectations and extreme events will drift over the coming decades.

SD-RET research project: The SD-RET RAs for this project will work with pre-compiled climate model output used in the recent Fourth National Climate Assessment (NCA4) downscaled over the Northern Great Plains to assess the potential impacts of climate change on our region’s natural and human systems. Their tools will include the R statistical package and visualization packages that can also be taken back to the classroom.

The SD-RET RAs will:

learn how climate model ensembles are designed, executed and processed;
learn (or refine) their skills with statistical software;
learn how to calculate extreme events from statistical distributions;
link extreme and nuisance events to design limits and capacities of human and natural systems;
learn how to present, visualize and articulate climate projection information as well as extreme event probability.

Examples of alignment to the Next Generation Science/Common Core State Standards ^3,22:

MS-ESS3-5: Ask questions to clarify evidence of the factors that have caused the rise in global temperatures over the past century.
MS-ESS3-2: Analyze and interpret data on natural hazards to forecast future catastrophic events and inform the development of technologies to mitigate their effects
HS-ESS3-1: Construct an explanation based on evidence for how the availability of natural resources, occurrence of natural hazards, and changes in climate have influenced human activity.
HS-ESS3-5: Analyze geoscience data and the results from global climate models to make an evidence-based forecast of the current rate of global or regional climate change and associated future impacts to Earth’s systems
3-ESS2-1: Represent data in tables and graphical displays to describe typical weather conditions expected during a particular season.
S.ID.3: Interpret differences in shape, center, and spread in the context of the data sets, accounting for possible effects of extreme data points (outliers).