Understanding the Nonstationarity in the Seasonality of Extreme Precipitation: A Case Study of the Eastern United States
Abstract
Global warming is likely to impact extreme storms in the eastern United States (eUS), ultimately affecting the empirical probability distribution of extreme daily precipitation timing. In this work, probabilistic properties of dates of annual maximum precipitation (AMP) were studied using circular statistics at 583 sites in the eUS (1950-2019). The circular median, standard deviation, and tests of uniformity are used in two blocks of equal length records of long-term samples of dates of maxima to explore the spatiotemporal changes in AMP seasonality. Furthermore, a kernel circular density method is applied to identify the shift in the distributional modes of timing of AMP. The results reveal a distinct spatial variability in the temporal changes in seasonality across the eUS. Majority of stations observe a shift in the median date of occurrence and circular standard deviation of extreme precipitation, and around 70% of them are concentrated within the Central, South, and Southeast regions. The results of shifts in distribution modality indicate that the nonstationarity of significant season(s) of AMP is pronounced in several stations over the four seasons, especially in summer and fall as 80% of locations observe modality shift. On the other hand, changes in strength of seasonality are rarely found in winter and summer, while spring and fall observe significant increase in the number of locations with shift in the strength of seasonality across the study area. Results of changes in extreme precipitation seasonality have a critical role in the flood risk management and preparedness.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFM.H35B..06A