A forecast-model-based extreme weather event attribution system developed for Aotearoa New Zealand

被引:4
|
作者
Tradowsky, Jordis S. [1 ,2 ]
Bodeker, Greg E. [1 ]
Noble, Christopher J. [3 ]
Stone, Daithi A. [4 ]
Rye, Graham D. [3 ]
Bird, Leroy J. [1 ]
Herewini, William, I [1 ,5 ]
Rana, Sapna [3 ,6 ]
Rausch, Johannes [3 ,7 ]
Soltanzadeh, Iman [3 ,8 ]
机构
[1] Bodeker Sci, Alexandra, New Zealand
[2] Norwegian Meteorol Inst, Oslo, Norway
[3] Meteorol Serv New Zealand Ltd, Wellington, New Zealand
[4] Natl Inst Water & Atmospher Res, Wellington, New Zealand
[5] Meridian Energy, Christchurch, New Zealand
[6] He Pou Rangi Climate Change Commiss, Wellington, New Zealand
[7] Meteomatics AG, St Gallen, Switzerland
[8] E ON Digital Technol, Bonn, Germany
来源
ENVIRONMENTAL RESEARCH-CLIMATE | 2023年 / 2卷 / 04期
关键词
extreme weather events; extreme event attribution; precipitation simulation; attribution system;
D O I
10.1088/2752-5295/acf4b4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A largely automated extreme weather event (EWE) attribution system has been developed that uses the Weather Research and Forecast numerical weather prediction model to simulate EWEs under current and pre-industrial climate conditions. The system has been applied to two extreme precipitation events in Aotearoa New Zealand with the goal of quantifying the effect of anthropogenic climate change on the severity of these events. The forecast simulation of the target event under current climate conditions constitutes the first scenario (ALL). We then apply a climate change signal in the form of delta fields in sea-surface temperature, atmospheric temperature and specific humidity, creating a second 'naturalised' scenario (NAT) which is designed to represent the weather system in the absence of human interference with the climate system. A third scenario, designed to test for coherence, is generated by applying deltas of opposite sign compared to the naturalised scenario (ALL+). Each scenario comprises a 22-member ensemble which includes one simulation that was not subject to stochastic perturbation. Comparison of the three ensembles shows that: (1) the NAT ensemble develops an extreme event which resembles the observed event, (2) the severity, i.e. maximum intensity and/or the size of area affected by heavy precipitation, changes when naturalising the boundary conditions, (3) the change in severity is consistently represented within the three scenarios and the signal is robust across the different ensemble members, i.e. it is typically shown in most of the 22 ensemble members. Thus, the attribution system presented here can be used to provide information about the influence of anthropogenic climate change on the severity of specific extreme events.
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页数:18
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