Collaborative Research: Fingerprinting Energy and Water Cycle Extremes through a Scale-Interaction Lens

点击翻译按钮获取中文摘要

Extreme weather events such as heat waves, cold air outbreaks (CAOs), droughts, and heavy precipitation commonly cause disruptions over regions the size of the northern midwest or the southern great plains. These extremes are generally embedded in large-scale meterological patterns (LMPs). For instance a drought might occur within a high-pressure center which is part of a pattern of highs and lows originating over the North Pacific and extending across the continental US. The LMPs may in turn be generated or influenced by planetary-scale climate modes (PCMs) such as El Nino/Southern Oscillation (ENSO) events and the Arctc Oscillation (AO). Thus efforts to understand and predict extreme weather events, or to anticipate changes in their frequency and intensity due to climate change, must consider the events from a multi-scale perspective that recognizes the interplay of regional, continental, and planetary scales that contribute to them.Work performed here seeks to develop a comprehensive suite of multi-scale metrics, or "fingerprints", for characterizing the atmospheric processes responsible for regional extreme weather events. Once the fingerprints are developed they are used to determine the dynamical mechanisms through which larger-scale processes lead to, or strongly influence, the regional extremes. The research also uses the fingerprints and subsequent dynamical analysis to assess the realism of climate model simulations of regional extremes and their associations with LMPs and PCMs. One analysis technique uses the the tendency equation for geopotential height in a two-layer quasi-geostrophic model to identify "optimal modes", meaning wave patterns which are optimally shaped to extract energy from the mean flow to achieve rapid growth over a few days. Prior work by the Principle Investigators (PIs) and their collaborators used this approach to show that planetary-scale circulation anomalies can alter the mean state in a way that promotes the growth of an optimal mode that promotes CAOs. Additional prior work links the long-term reduction in the summertime equator-to-pole temperature contrast to a reduction in frontal weather systems over North America, which in turn promotes dryer and warmer summers in the US.The work is of societal as well as scientific interest given the disruptions caused by extreme weather. The project supports a graduate student and a postdoctoral research fellow, thereby developing the future workforce in this research area. The PI at Georgia Tech works with the Center for Education Integrating Science, Mathematics and Computing (CEISMC), which conducts K-12 outreach in Atlanta-area schools and organizes summer workshops focused on underrepresented students. The PI at Florida State University works with undergraduate students to produce long-range forecasts of continental-scale CAOs, which have been used by stakeholders from the agriculture, energy, and water sectors.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.