The map shows the spatial pattern of median conditions for the selected month, while the lower panel tracks how the season may evolve at your chosen location.

You can:
• Jump between different ski resorts (like Myrkdalen in the screenshot)
• Switch to major Nordic cities
• Or just click anywhere on the map to get a local forecast time series for that spot

The tool uses ECMWF’s 51-member seasonal ensemble and summarises the range of possible conditions each month.

In the time series you see the 5th, 25th, 50th, 75th and 95th percentiles, so you get a sense of the spread.

Sarcasm aside, it's perhaps worth pointing out that the evidence suggests that weather disasters reduce economic growth for decades - the idea that there's rapid bounceback, or even extra growth stimulated by recovery, has proved wrong

www.newscientist.com/article/mg23...

The real headline is there in the article:

“The wealthiest are increasing their wealth faster than any other group.”

That’s the story. Not the meaningless number.

So when we say the richest 1% hold $52 trillion, we just check out. It sounds like monopoly money.
We’re not wired to understand exponential scales — and that’s exactly how the story slips past us.

Who has a sense of what $52 trillion means?
It’s too big, too abstract. Even billion vs. million is a scale most people can’t intuitively grasp — a billion seconds is 31 years; a million seconds is 12 days.

Thanks to the fantastic team at NERSC, Jakob Dörr, and Philipp Griewank.
If you’re working on climate dynamics, prediction, or sea ice processes, I’d love to hear your thoughts on how sea ice age could play a role in your work.

#Arctic #SeaIce #ClimatePrediction #ClimateModels #ESA #SAGE

This work also launches us into our new ESA project, SAGE, where we’ll dig deeper into how sea ice age can reshape the way we evaluate and improve climate models. Stay tuned. 🌍❄️

Most exciting: sea ice age reveals low-frequency variability in the Arctic (see Fig. 5 in our paper). This opens a new window into decadal-scale fluctuations — crucial for improving #ClimatePrediction systems.

For the first time, we applied the same ice-tracking algorithm to both model output & satellite observations. This fair, like-for-like comparison reduces long-standing biases and shows that sea ice age captures dynamics thickness & volume alone cannot.

Sea ice age is more than just a number — it integrates the dynamic + thermodynamic processes shaping Arctic sea ice. Unlike area or thickness, it can’t easily be tuned in models. Age emerges from the cumulative history of growth, melt & drift. A tough benchmark for climate models.

I'll be talking this afternoon about challenges in interpreting and making fair comparisons of sea ice age between climate models and observations, and demonstrating one way to resolve this using a common definition of sea ice age (paper out soon).