2022
DOI: 10.1038/s41598-022-09666-z
|View full text |Cite
|
Sign up to set email alerts
|

Multi-week prediction of livestock chill conditions associated with the northwest Queensland floods of February 2019

Abstract: The compound extreme weather event that impacted northern Queensland in February 2019 featured record-breaking rainfall, persistent high wind gusts and relatively cold day-time temperatures. This caused livestock losses numbering around 500,000 in the northwest Queensland Gulf region. In this study, we examine the livestock chill conditions associated with this week-long compound weather event and its potential for prediction from eleven world-leading sub-seasonal to seasonal (S2S) forecast systems. The livest… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

2
11
0

Year Published

2022
2022
2024
2024

Publication Types

Select...
6

Relationship

2
4

Authors

Journals

citations
Cited by 7 publications
(13 citation statements)
references
References 33 publications
2
11
0
Order By: Relevance
“…For percentiles estimation, it is based on a 15‐day moving window centered on calendar‐day corresponding to the reference time period (1981–2010). We calculate it by applying the bootstrap procedure, which could provide the temporally consistent results in reasonable sample sizes (Cowan et al., 2022; Perkins‐Kirkpatrick & Gibson, 2017). This procedure divides the 30 years into “base” and “out‐of‐base” periods and eventually ensures that their estimates are comparable, reducing discontinuity to a great extent (Zhang et al., 2005).…”
Section: Methodsmentioning
confidence: 99%
“…For percentiles estimation, it is based on a 15‐day moving window centered on calendar‐day corresponding to the reference time period (1981–2010). We calculate it by applying the bootstrap procedure, which could provide the temporally consistent results in reasonable sample sizes (Cowan et al., 2022; Perkins‐Kirkpatrick & Gibson, 2017). This procedure divides the 30 years into “base” and “out‐of‐base” periods and eventually ensures that their estimates are comparable, reducing discontinuity to a great extent (Zhang et al., 2005).…”
Section: Methodsmentioning
confidence: 99%
“…The dynamics and nature of the event in the observational and historical climate context were documented by NACP scientists at the BoM with analysis of the ability of several international Sub-Seasonal to Seasonal (S2S) prediction systems to forecast the flood event . The study concluded that the S2S systems underestimated the magnitude of the extreme rainfall event in their lead week 1 forecasts, although around ten S2S systems predicted twice the climatological probability of extreme chill conditions (Cowan et al 2022a). This motivated a more detailed UM study to understand the benefits of multi-week ensemble forecasting for extreme, and damaging, events of this nature (Hawcroft et al, 2021).…”
Section: Researchmentioning
confidence: 96%
“…In February 2019, extreme flooding across northeast Australia and the associated cold temperatures and wind chill conditions significantly impacted the cattle industry across the Gulf of Carpentaria Coast drainage basin (Cowan et al 2022a). The dynamics and nature of the event in the observational and historical climate context were documented by NACP scientists at the BoM with analysis of the ability of several international Sub-Seasonal to Seasonal (S2S) prediction systems to forecast the flood event .…”
Section: Researchmentioning
confidence: 99%
“…This event is of particular interest to the forecasting community since it was poorly predicted, particularly at lead times of around 1 week. Some studies have evaluated the skill with which the event was forecast with numerical weather prediction Hawcroft et al (2021) and subseasonal Cowan et al ( , 2022; Tsai et al (2021) models. On the numerical weather prediction time-scale, Hawcroft et al (2021) find that forecast errors mostly originate from atmosphere-ocean coupling and the convection scheme, particularly near the west Cape York Peninsula coast.…”
Section: Introductionmentioning
confidence: 99%