Flash droughts present a new challenge for subseasonal-to-seasonal prediction
AuthorPendergrass, Angeline G.
Meehl, Gerald A.
Bonfils, Céline J. W.
Gallant, Ailie J. E.
Neale, Richard B.
Overpeck, Jonathan T.
Wheeler, Matthew C.
Wood, Andrew W.
Woodhouse, Connie A.
AffiliationUniv Arizona, Sch Geog & Dev
MetadataShow full item record
PublisherNATURE PUBLISHING GROUP
CitationPendergrass, A.G., Meehl, G.A., Pulwarty, R. et al. Flash droughts present a new challenge for subseasonal-to-seasonal prediction. Nat. Clim. Chang. 10, 191–199 (2020). https://doi.org/10.1038/s41558-020-0709-0
JournalNATURE CLIMATE CHANGE
RightsThis is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2020.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractFlash droughts, which develop over the course of weeks, are difficult to forecast given the current state of subseasonal-to-seasonal prediction. This Perspective offers operational and research definitions, places them in the broader context of climate and suggests avenues for future research. Flash droughts are a recently recognized type of extreme event distinguished by sudden onset and rapid intensification of drought conditions with severe impacts. They unfold on subseasonal-to-seasonal timescales (weeks to months), presenting a new challenge for the surge of interest in improving subseasonal-to-seasonal prediction. Here we discuss existing prediction capability for flash droughts and what is needed to establish their predictability. We place them in the context of synoptic to centennial phenomena, consider how they could be incorporated into early warning systems and risk management, and propose two definitions. The growing awareness that flash droughts involve particular processes and severe impacts, and probably a climate change dimension, makes them a compelling frontier for research, monitoring and prediction.
NotePublic domain article
VersionFinal published version