Atmospheric sciences colloquia

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Seminar coordinator for AY 2022-2023 is Professor Zhuo Wang,

Seminar: Sophie Orendorf/Songning Wang

Event Type
Dr. Zhuo Wang
2079 NHB
Mar 29, 2022   3:30 pm  

Sophie Orendorf: A Convective Windstorm in a Warmer Climate

Severe straight-line winds in convective windstorms can cause casualties and significant damage to houses, crops, and infrastructure over a large-scale region. The 10 August 2020 Midwest derecho resulted in four deaths, hundreds of injuries, and was the costliest thunderstorm event in U.S. history.  It is not currently known how the mechanisms producing convective windstorms in such quasi-linear convective systems might differ in a future, warmer climate. A method known as pseudo global warming (PGW) is utilized to evaluate potential differences in this specific storm if it instead had occurred in a warmer climate, and to understand why it might differ.  The method includes first simulating the 10 Aug 2020 event in the observed environment, and then simulating the same event in environments altered according to the predictions from five different climate models from the CMIP5 data set. The simulation of the historical event suggests that its strong surface winds were mainly produced by the lowering of a strong rear inflow jet (RIJ) within the quasi-linear convective system, rather than from mesovortices or downbursts that can be associated with such systems.  In the future warmer climate, for all but one of the PGW simulations, the area of extreme surface winds increases, as it appears does their intensity. The RIJ in these PGW convective storms is stronger than in the historical case and appears to be the dominant mechanism behind the more severe surface winds in those simulations as well. Downbursts and mesovortices also appear to be more frequent in the PGW simulations, but their transience suggests they are of lesser importance.

Songning Wang: Change in the frequency of tornado activity in China with climate change

Global climate change affects weather systems across all scales, but the uncertainty of this effect increases with decreasing scale. Tornadoes are examples of small-scale systems that can cause extreme damage, thus emphasizing the importance of estimating possible trends in their future occurrences. One way of doing so is to use output from global climate model (GCM) simulations to calculate environmental parameters, including the significant tornado parameter (STP), which can then serve as tornado-occurrence proxies. This is a form of statistical downscaling. Using seven models contributed to the Coupled Model Intercomparison Project phase 6 (CMIP6), we computed STP and other environmental parameters over the region of China for the historical time period 1970-1999 and for the future time period 2070-2099 under the Shared Socioeconomic Pathway (SSP) 585. Across most models, STP is higher in the future over the east, south, and northeast of China. An average increase of 3-9 days per year of tornado-favorable conditions is projected for these regions in the future. We also find more inter-annual variability, or volatility, in tornado-favorable days in the future. This research will provide hazard assessments to inform future decision making.

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