2022
DOI: 10.1175/bams-d-21-0236.1
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Toward Near-Real-Time Attribution of Extreme Weather Events in Aotearoa New Zealand

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Cited by 12 publications
(6 citation statements)
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“…For the characterization and detection of the 2018 drought we used two widely accepted indicators, the Standardized Precipitation Index (SPI; Mckee et al, 1993) and the Standardized Precipitation Evapotranspiration Index (SPEI; Vicente-Serrano et al, 2014), and one alternative method based on climate networks (Tsonis et al, 2006;Donges et al, 2009). Two aggregation periods, three and six months, were selected, so that two types of droughts, could be considered, meteorological (SPEI3) and agricultural (SPEI6) (Heim, 2002;Zampieri et al, 2017).…”
Section: Drought Indicatorsmentioning
confidence: 99%
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“…For the characterization and detection of the 2018 drought we used two widely accepted indicators, the Standardized Precipitation Index (SPI; Mckee et al, 1993) and the Standardized Precipitation Evapotranspiration Index (SPEI; Vicente-Serrano et al, 2014), and one alternative method based on climate networks (Tsonis et al, 2006;Donges et al, 2009). Two aggregation periods, three and six months, were selected, so that two types of droughts, could be considered, meteorological (SPEI3) and agricultural (SPEI6) (Heim, 2002;Zampieri et al, 2017).…”
Section: Drought Indicatorsmentioning
confidence: 99%
“…Further, a climate network approach was used (Tsonis et al, 2006;Donges et al, 2009) to detect drought conditions in Germany. In a climate network, high spatial coherence of weather conditions is characterized by high values of the node degree measure that accounts for pairwise statistical similarity (e.g.…”
Section: Drought Indicatorsmentioning
confidence: 99%
“…It can also provide risk information on climate change and thus inform policy-making for climate change adaptation [11]. Europe [12], the USA [13], New Zealand [14] and South Africa [15] have been developing their own practical real-time attribution services. This study will benefit the establishment of real-time attribution services in China.…”
Section: Introductionmentioning
confidence: 99%
“…This change in both the severity and frequency of EWEs has been observed recently (Philip et al ., 2021) and it impacts people and the economy in various ways, hence it is necessary to understand and estimate the impact of anthropogenic warming on such extremes (Douris and Kim, 2021). Within New Zealand extreme event attribution and the economic risks associated with EWEs is an active area of research (Frame et al ., 2020; Stone et al ., 2021; Tradowsky et al ., 2022).…”
Section: Introductionmentioning
confidence: 99%