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Advances in Statistical Climatology, Meteorology and Oceanography An international open-access journal on applied statistics
Adv. Stat. Clim. Meteorol. Oceanogr., 1, 45-57, 2015
https://doi.org/10.5194/ascmo-1-45-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
17 Nov 2015
Characterization of extreme precipitation within atmospheric river events over California
S. Jeon1, Prabhat2, S. Byna2, J. Gu2, W. D. Collins3,1, and M. F. Wehner2 1Earth Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
2Computational Research Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
3University of California, Berkeley, Berkeley, California, USA
Abstract. Atmospheric rivers (ARs) are large, spatially coherent weather systems with high concentrations of elevated water vapor. These systems often cause severe downpours and flooding over the western coastal United States – and with the availability of more atmospheric moisture in the future under global warming we expect ARs to play an important role as potential causes of extreme precipitation changes. Therefore, we aim to investigate changes in extreme precipitation properties correlated with AR events in a warmer climate, which are large-scale meteorological patterns affecting the weather and climate of California.

We have recently developed the TECA (Toolkit for Extreme Climate Analysis) software for automatically identifying and tracking features in climate data sets. Specifically, we can now identify ARs that make landfall on the western coast of North America. Based on this detection procedure, we can investigate the impact of ARs by exploring the spatial extent of AR precipitation using climate model (CMIP5) simulations and characterize spatial patterns of dependence for future projections between AR precipitation extremes under climate change within the statistical framework. Our results show that AR events in the future RCP (Representative Concentration Pathway)8.5 scenario (2076–2100) tend to produce heavier rainfall with higher frequency and longer days than events from the historical run (1981–2005). We also find that the dependence between extreme precipitation events has a shorter spatial range, within localized areas in California, under the high future emissions scenario than under the historical run.


Citation: Jeon, S., Prabhat, Byna, S., Gu, J., Collins, W. D., and Wehner, M. F.: Characterization of extreme precipitation within atmospheric river events over California, Adv. Stat. Clim. Meteorol. Oceanogr., 1, 45-57, https://doi.org/10.5194/ascmo-1-45-2015, 2015.
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This paper investigates the influence of atmospheric rivers on spatial coherence of extreme precipitation under a changing climate. We use our TECA software developed for detecting atmospheric river events and apply statistical techniques based on extreme value theory to characterize the spatial dependence structure between precipitation extremes within the events. The results show that extreme rainfall caused by atmospheric river events is less spatially correlated under the warming scenario.
This paper investigates the influence of atmospheric rivers on spatial coherence of extreme...
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