Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, United States
Current affiliation: Department of Geophysical Sciences and the Data Science Institute, University of Chicago, 5801 S. Ellis Ave, Chicago, IL 60637, United States
Paul A. O'Gorman
Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Ave, Cambridge, MA 02139, United States
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Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 1,603 (including HTML, PDF, and XML)
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1,574
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29
1,603
0
0
HTML: 1,574
PDF: 0
XML: 29
Total: 1,603
BibTeX: 0
EndNote: 0
Views and downloads (calculated since 03 Nov 2025)
Cumulative views and downloads
(calculated since 03 Nov 2025)
Total article views: 1,603 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,574
0
29
1,603
0
0
HTML: 1,574
PDF: 0
XML: 29
Total: 1,603
BibTeX: 0
EndNote: 0
Views and downloads (calculated since 03 Nov 2025)
Cumulative views and downloads
(calculated since 03 Nov 2025)
Viewed (geographical distribution)
Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.
Total article views: 1,603 (including HTML, PDF, and XML)
Thereof 1,578 with geography defined
and 25 with unknown origin.
Total article views: 1,603 (including HTML, PDF, and XML)
Thereof 1,578 with geography defined
and 25 with unknown origin.
Estimating small probabilities of high-impact extreme weather events is a persistent computational challenge, motivating techniques such as rare event sampling and ensemble boosting: lightly perturbing simulated moderate events into more extreme ones. We formulate a new, flexible sampling strategy and characterizes a critical parameter – the advance split time, dictating when to perturb – in a simple atmospheric turbulence model, with generalizable entropy-based criteria.
Estimating small probabilities of high-impact extreme weather events is a persistent...