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What is the most useful approach for forecasting hydrological extremes during El Niño?

Emerton, Rebecca E. (författare)
Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England.;European Ctr Medium Range Weather Forecasts, Reading, Berks, England.
Stephens, Elisabeth M. (författare)
Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England.
Cloke, Hannah L. (författare)
Uppsala universitet,Luft-, vatten- och landskapslära,Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England.;Univ Reading, Dept Meteorol, Reading, Berks, England.
Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England;European Ctr Medium Range Weather Forecasts, Reading, Berks, England. Univ Reading, Dept Geog & Environm Sci, Reading, Berks, England. (creator_code:org_t)
2019-04-03
2019
Engelska.
Ingår i: Environmental Research Communications (ERC). - : IOP PUBLISHING LTD. - 2515-7620. ; 1:3
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • In the past, efforts to prepare for the impacts of El Nino-driven flood and drought hazards have often relied on seasonal precipitation forecasts as a proxy for hydrological extremes, due to a lack of hydrologically relevant information. However, precipitation forecasts are not the best indicator of hydrological extremes. Now, two different global scale hydro-meteorological approaches for predicting river flow extremes are available to support flood and drought preparedness. These approaches are statistical forecasts based on large-scale climate variability and teleconnections, and resource-intensive dynamical forecasts using coupled ocean-atmosphere general circulation models. Both have the potential to provide early warning information, and both are used to prepare for El Nino impacts, but which approach provides the most useful forecasts? This study uses river flow observations to assess and compare the ability of two recently-developed forecasts to predict high and low river flow during El Nino: statistical historical probabilities of ENSO-driven hydrological extremes, and the dynamical seasonal river flow outlook of the Global Flood Awareness System (GloFAS-seasonal). Our findings highlight regions of the globe where each forecast is (or is not) skilful compared to a forecast of climatology, and the advantages and disadvantages of each forecasting approach. We conclude that in regions where extreme river flow is predominantly driven by El Nino, or in regions where GloFAS-seasonal currently lacks skill, the historical probabilities generally provide a more useful forecast. In areas where other teleconnections also impact river flow, with the effect of strengthening, mitigating or even reversing the influence of El Nino, GloFAS-seasonal forecasts are typically more useful.

Ämnesord

NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Klimatforskning (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Climate Research (hsv//eng)
NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Meteorologi och atmosfärforskning (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Meteorology and Atmospheric Sciences (hsv//eng)

Nyckelord

hydrological extremes
El Nino
seasonal forecasting
climate variability

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