The benefits of ensemble prediction for forecasting an extreme event: the Queensland floods of February 2019

Hawcroft, Matt and Lavender, Sally ORCID: https://orcid.org/0000-0003-4785-1569 and Copsey, Dan and Milton, Sean and Rodriguez, Jose and Tennant, Warren and Webster, Stuart and Cowan, Tim (2021) The benefits of ensemble prediction for forecasting an extreme event: the Queensland floods of February 2019. Monthly Weather Review, 149. pp. 2391-2408. ISSN 0027-0644


Abstract

From late January to early February 2019, a quasi-stationary monsoon depression situated over northeast Australia caused devastating floods. During the first week of February, when the event had its greatest impact in northwest Queensland, record-breaking precipitation accumulations were observed in several locations, accompanied by strong winds, substantial cold maximum temperature anomalies and related wind chill. In spite of the extreme nature of the event, the monthly rainfall outlook for February issued by Australia’s Bureau of Meteorology on 31st January provided no indication of the event. In this study, we evaluate the dynamics of the event and assess how predictable it was across a suite of ensemble model forecasts using the UK Met Office numerical weather prediction (NWP) system, focussing on a one week lead time. In doing so, we demonstrate the skill of the NWP system in predicting the possibility of such an extreme event occurring. We further evaluate the benefits derived from running the ensemble prediction system at higher resolution than used operationally at the Met Office and with a fully coupled dynamical ocean. We show that the primary forecast errors are generated locally, with key sources of these errors including atmosphere-ocean coupling and a known bias associated with the behaviour of the convection scheme around the coast. We note that a relatively low resolution ensemble approach requires limited computing resource, yet has the capacity in this event to provide useful information to decision makers with over aweek’s notice, beyond the duration of many operational deterministic forecasts.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version, in accordance with the copyright policy of the publisher. © 2021 American Meteorological Society.
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Date Deposited: 26 May 2021 03:57
Last Modified: 12 Oct 2021 23:08
Uncontrolled Keywords: Toowoomba floods; Toowoomba; flooding; prediction; forecasting; Australia; ensembles; forecasting techniques; numerical weather prediction/forecasting
Fields of Research (2008): 04 Earth Sciences > 0401 Atmospheric Sciences > 040107 Meteorology
04 Earth Sciences > 0401 Atmospheric Sciences > 040102 Atmospheric Dynamics
Fields of Research (2020): 37 EARTH SCIENCES > 3701 Atmospheric sciences > 370108 Meteorology
37 EARTH SCIENCES > 3701 Atmospheric sciences > 370105 Atmospheric dynamics
Identification Number or DOI: https://doi.org/10.1175/MWR-D-20-0330.1
URI: http://eprints.usq.edu.au/id/eprint/42029

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