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Current Global Heatwave — Due to Climate Change?

The World Meteorological Organization announced that June was the hottest on record globally with records being set (Xinjiang in China — 52.2C & Rome in Italy — 41.8C.)

Is this due to climate change?……not necessarily.

  • The simultaneous heatwaves and flooding are being caused by a specific Jet Stream pattern that’s creating ‘Heat Domes’.

  • The Jet Stream pattern has been locked for weeks, characterised by 5 ‘U-Bends’.

  • South of these U-Bends, hot air is getting trapped and is warming as its ‘squashed’ downwards.

Tricky To Untangle: Whilst the science is clear that extreme weather events will become more frequent as climate change accelerates, its less clear how intwined global warming is with jet stream patterns.

How Long Will It Last?: The current jet stream pattern is expected to last until August, although it could shift unexpectedly, altering the locations affected by the heat dome and rainfall.

The areas between heat domes such as parts of the US & S.Korea are susceptible to experiencing sudden rainfall and flash flooding.

Longer Term Outlook & Places To Watch:

  • Canada: Outlook looks grim with higher than normal fire activity expected across the country throughout the 2023 Wildfire Season (May — October)

  • North America: No parts of the country are expected to see cooler than average temperatures July — September. A new heat dome has developed on the West Coast with Central California expecting excessive warming. Higher wildfire risk.

  • Europe: Conditions are currently condusive to wildfire (drought & high-temps) — areas most at risk currently are Spain, Mediterranean Islands & Sardinia. However we expect conditions to ease tomorrow onwards.

WEATHER ANALYTIX™: How do we account for this?

The Heat Domes caused by waves in the Jet Stream are sporadic and cannot be reliably predicted or tied to wider global warming patterns — how do we cater for this variability in our climate/extreme weather modelling?

We run global historical weather observations through thousands of simulations and apply fitted models to the tails of the distributions to allow for more extreme events to occur in the future (extreme event analysis).

This effectively increases the potential variability of extreme events and ensures we apply a non-zero probability to events that we have not observed in the past. Additionally, as new extreme historical observations are recorded, these fits and simulations are repeated to adapt to a higher benchmark of severe weather events. More extreme events are becoming the norm, and our models will reflect this using the approach we have adopted.

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