The effects of climate change will likely cause smaller but stronger storms in the United States, according to a new framework for modeling storm behavior developed at the University of Chicago. Though storm intensity is expected to increase the predicted reduction in storm size may alleviate some fears of widespread severe flooding in the future. A new approach, published today in Journal of Climate, uses new statistical methods to identify and track storm features in both observational weather data and new high-resolution climate modeling simulations.
"Climate models all predict that storms will grow significantly more intense in the future, but that total precipitation will increase more mildly over what we see today. By developing new statistical methods that study the properties of individual rainstorms, we were able to detect changes in storm frequency, size, and duration that explain this mismatch." said Elisabeth Moyer associate professor of geophysical sciences at the University of Chicago.
Most climate models agree that high levels of atmospheric carbon will increase precipitation intensity, by an average of approximately 6 percent per degree temperature rise. These models also predict an increase in total precipitation; however, this growth is smaller, only 1 to 2 percent per degree temperature rise. Understanding changes in storm behavior that might explain this gap have remained difficult to find. In the past, climate simulations were too coarse in resolution (100s of kilometers) to accurately capture individual rainstorms. More recently, high-resolution simulations have begun to approach weather-scale, but analytic approaches had not yet evolved to make use of that information and evaluated only aggregate shifts in precipitation patterns instead of individual storms. To address this discrepancy, postdoctoral scholar Won Chang and Michael Stein, Jiali Wang, V. Rao Kotamarthi, and Moyer developed new methods to analyze rainstorms in observational data or high-resolution model projections. First, they adapted morphological approaches from computational image analysis to develop new statistical algorithms for detecting and analyzing individual rainstorms over space and time. They then analyzed results of new ultra-high-resolution (12 km) simulations of U.S. climate performed with the Weather Research and Forecasting Model (WRF). Analyzing simulations of precipitation in the present and future, the researchers detected changes in storm features that explained why the stronger storms predicted didn't increase overall rainfall as much as expected. Individual storms become smaller in terms of the land area covered, especially in the summer. In winter, storms become smaller as well, but also less frequent and shorter. The team also found several important differences between model output and present-day weather. The model tended to predict storms that were both weaker and larger than those actually observed, and in winter, model-forecast storms were also fewer and longer than observations. New precipitation forecasts that include these changes in storm characteristics will add important details that help assess future flood risk under climate change. These results suggest that concerns about higher-intensity storms causing severe floods may be tempered by reductions in storm size, and that the tools developed at UChicago and Argonne can help further clarify future risk.
"Changes in spatio-temporal precipitation patterns in changing climate conditions. Climate change will drive stronger, smaller storms in U.S., new modeling approach forecasts." ScienceDaily
https://www.sciencedaily.com/releases/2016/12/161201172318.htm
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