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Cyclone Narelle Is Now Larger and 'More Severe' as It Crosses the Western Australian Coast
Cyclone Narelle caused destructive winds with gusts up to 260 km/h, flooding, and forced evacuations across WA's northwest coast, including damage to a 100,000-hectare cattle station.
- On Friday, Category 4 Cyclone Narelle struck near Exmouth, Western Australia, bringing destructive winds to the Pilbara and northern Gascoyne coasts as it made landfall 55km south of Coral Bay.
- The cyclone intensified rapidly to Category 4 on Thursday night, then battered the 250,000-acre Bullara Station near Coral Bay, where owner Edwina Shallcross reported the homestead roof was ripped off.
- Residents in Exmouth faced "absolutely screaming winds," Exmouth Shire president Matthew Niikkula said, while more than 1,500 properties lost power, leaving locals in darkness awaiting safe conditions.
- Premier Roger Cook called the damage a "very confronting situation," while Prime Minister Anthony Albanese pledged federal support; emergency services fielded 42 calls in the Pilbara and 16 in the Mid West.
- Narelle is expected to weaken on Saturday as it moves southeast toward the Central West, though the Bureau of Meteorology warned of lingering flash flooding and dangerous storm tides.
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Cyclone Narelle is now larger and 'more severe' as it crosses the Western Australian coast
Severe Tropical Cyclone Narelle continues to amaze us with its long journey across northern Australia. This cyclone began life near the Solomon Islands on March 16, when moist air rose rapidly and created a low-pressure zone.
·United Kingdom
Read Full ArticleNightmare Narelle cuts down coast as Perth cops drenching
Cyclone Narelle’s wrecking spree through three States and Territories is set to leave its final mark on WA on Saturday as towns and communities start to deal with the damage left in its ferocious wake.
·City of Perth, Australia
Read Full ArticleCoverage Details
Total News Sources13
Leaning Left3Leaning Right2Center3Last UpdatedBias Distribution38% Left, 37% Center
Bias Distribution
- 38% of the sources lean Left, 37% of the sources are Center
38% Left
L 38%
C 37%
R 25%
Factuality
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