Advances in the subseasonal prediction of extreme events: relevant case studies across the globe
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hdl:2117/371614
Tipus de documentArticle
Data publicació2022-06
EditorAmerican Meteorological Society
Condicions d'accésAccés obert
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Abstract
Extreme weather events have devastating impacts on human health, economic activities, ecosystems, and infrastructure. It is therefore crucial to anticipate extremes and their impacts to allow for preparedness and emergency measures. There is indeed potential for probabilistic subseasonal prediction on time scales of several weeks for many extreme events. Here we provide an overview of subseasonal predictability for case studies of some of the most prominent extreme events across the globe using the ECMWF S2S prediction system: heatwaves, cold spells, heavy precipitation events, and tropical and extratropical cyclones. The considered heatwaves exhibit predictability on time scales of 3–4 weeks, while this time scale is 2–3 weeks for cold spells. Precipitation extremes are the least predictable among the considered case studies. Tropical cyclones, on the other hand, can exhibit probabilistic predictability on time scales of up to 3 weeks, which in the presented cases was aided by remote precursors such as the Madden–Julian oscillation. For extratropical cyclones, lead times are found to be shorter. These case studies clearly illustrate the potential for event-dependent advance warnings for a wide range of extreme events. The subseasonal predictability of extreme events demonstrated here allows for an extension of warning horizons, provides advance information to impact modelers, and informs communities and stakeholders affected by the impacts of extreme weather events.
DatasetData availability statement. ERA5 data were obtained from the Copernicus Climate Change Service Climate Data Store (CDS), https://cds.climate.copernicus.eu/cdsapp#!/home. The ECMWF S2S model data were obtained through the MARS archive (https://apps.ecmwf.int/datasets/data/s2s/). CPC Global Unified Precipitation data were provided by the NOAA/OAR/ESRL/PSL, Boulder, Colorado, from their website at www.psl.noaa.gov/thredds/catalog/Datasets/cpc_global_precip/catalog.html. Australian precipitation data from the Australian Water Availability Project (AWAP) are available on request from the Bureau of Meteorology at www.bom.gov.au/climate/austmaps/metadata-daily-rainfall.shtml. The satellite image for Tropical Cyclone Claudia was captured by NOAA-20 satellite’s IITS instrument (www.nesdis.noaa.gov/content/tropical-cyclone-claudia-loses-strength-it-moves-away-australia). The satellite image for Cyclone Belna was obtained from https://en.wikipedia.org/wiki/Cyclone_Belna (NASA: https://worldview.earthdata.nasa.gov/). The satellite image for Typhoon Chan-hom was obtained from https://en.wikipedia.org/wiki/Typhoon_Chan-hom_%282015%29 (SSEC/CIMSS, University of Wisconsin–Madison). The satellite image for Medicane Zorbas is a MODIS image captured by NASA’s Terra satellite (EOSDIS Worldview) from https://commons.wikimedia.org/wiki/File:Zorbas_2018-09-29_0912Z.jpg. The ECMWF CAPE data for studying Medicane Zorbas were obtained from the IRI/LDEO Climate Data Library (https://iridl.ldeo.columbia.edu/SOURCES/.ECMWF/.S2S). Observed tropical cyclone data are obtained from the International Best Track Archive for Climate Stewardship (IBTrACS) (Knapp et al. 2010) at https://climatedataguide.ucar.edu/climate-data/ibtracs-tropical-cyclone-best-track-data.
CitacióDomeisen, D.I.V. [et al.]. Advances in the subseasonal prediction of extreme events: relevant case studies across the globe. "Bulletin of the American Meteorological Society", Juny 2022, vol. 103, núm. 6, p. E1473-E1501.
ISSN1520-0477
Col·leccions
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[15200477 - Bul ... s across the Globe (1).pdf | 46,88Mb | Visualitza/Obre |
Fitxers | Descripció | Mida | Format | Visualitza |
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[15200477 - Bul ... s across the Globe (1).pdf | 46,88Mb | Visualitza/Obre |