Stephan Hoyer
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stephanhoyer.com
Stephan Hoyer
@stephanhoyer.com
Building AI climate models at Google. I also contribute to the scientific Python ecosystem, including Xarray, NumPy and JAX.

Opinions are my own, not my employer's.
The "ungamable impact" of OSS really resonates with me:
www.thonking.ai/i/158277004/...

Sadly it does not necessarily align with what makes for a sucessful career in Big Tech. But it's worth trying anyways! :)
Why PyTorch is an amazing place to work... and Why I'm Joining Thinking Machines
In which I convince to you to join either PyTorch or Thinking Machines!
www.thonking.ai
March 4, 2025 at 11:22 PM
Reposted by Stephan Hoyer
Is there a link between #ClimateChange & increasing risk/severity of #wildfire in California--including the still-unfolding disaster? Yes. Is climate change the only factor at play? No, of course not. So what's really going on? [Thread] #CAfire #CAwx #LAfires iopscience.iop.org/a...
January 9, 2025 at 10:05 PM
This is a huge milestone for cloud-native big scientific data!
zarr.dev Zarr @zarr.dev · Jan 9
🎉 Zarr-Python 3 is here! 🎉

- Full support for Zarr v3 spec
- Chunk-sharding for more efficient data storage
- Major performance boosts with async I/O & parallel compression

💻 pip install --upgrade zarr
💻 conda install --channel conda-forge zarr

Blog post: https://buff.ly/3C3OwYw
January 9, 2025 at 11:55 PM
Reposted by Stephan Hoyer
Hi, thanks for the mention. Here's a 7-day paywall-free link to the main feature: www.bloomberg.com/graphics/202...
The Risky Business of Predicting Where Climate Disaster Will Hit
Climate tech companies can calculate the chances that a flood or wildfire will ravage your home. But what if their odds are all different?
www.bloomberg.com
December 30, 2024 at 5:27 PM
Reposted by Stephan Hoyer
Some thoughts on the use of AI/ML in climate modeling...

@realclimate.org

¡AI Caramba! www.realclimate.org/index.php/ar...
¡AI Caramba!
Rapid progress in the use of machine learning for weather and climate models is evident almost everywhere, but can we distinguish between real advances and vaporware? First off, let's define some...
www.realclimate.org
December 28, 2024 at 7:36 PM
Can incorporating AI improve precipitation in global weather and climate models?

Yes! In the latest NeuralGCM paper, we show that training on satellite-based precipitation results in significant improvements over traditional atmospheric models:
arxiv.org/abs/2412.11973
Neural general circulation models optimized to predict satellite-based precipitation observations
Climate models struggle to accurately simulate precipitation, particularly extremes and the diurnal cycle. Here, we present a hybrid model that is trained directly on satellite-based precipitation obs...
arxiv.org
December 19, 2024 at 8:34 PM
Interested in AI weather/climate modeling at #AGU24?

I'll be giving an overview talk on NeuralGCM at 11:30am Wed at the Google booth, and an talk on modeling precipitation with NeuralGCM at 4:25pm Wed in the session A34A.
December 9, 2024 at 5:42 PM
There's nothing like the feeling of starting a codebase from scratch.
December 1, 2024 at 1:32 AM
Reposted by Stephan Hoyer
One of my favourite data discoveries this year: Google's mind-blowing ARCO-ERA5 dataset: hourly data for ~300 climate variables, available globally from 1940! 🤯

Loadable with a single line of Python code from a single cloud-friendly Zarr file! Below: a month of wind waves + swell: 🌊
November 27, 2024 at 4:02 AM
Fast JAX simulations of all the PDEs--whee!
I'm excited to share our APEBench paper arxiv.org/abs/2411.00180 and code github.com/tum-pbs/apeb..., to be presented at #NeurIPS. Congratulations Felix and Simon 😀 👍 At its core, APEBench features a lightning-fast ⚡️ fully differentiable spectral solver with a huge range of different PDEs.
November 27, 2024 at 6:59 AM
The new ACE2 climate emulator from Oliver Watt-Meyer et al has very compelling results, with results that look comparable to NeuralGCM. Congrats to the AI2 team!
arxiv.org/abs/2411.112...
ACE2: Accurately learning subseasonal to decadal atmospheric variability and forced responses
Existing machine learning models of weather variability are not formulated to enable assessment of their response to varying external boundary conditions such as sea surface temperature and greenhouse...
arxiv.org
November 21, 2024 at 6:47 PM
Curious how the latest AI weather models compare?

Keeping WeatherBench2 up to date has been a bit trickier than we thought, but @raspstephan.bsky.social has put together a spreadsheet with quick estimates:
docs.google.com/spreadsheets...

Here's my version of the main plot.
November 20, 2024 at 3:08 AM
My teammates at Google finally published (in Nature!) one of my favorite projects: using millions of cellphones to map the ionosphere and improve GPS location accuracy: research.google/blog/mapping...
Mapping the ionosphere with the power of Android
research.google
November 15, 2024 at 4:58 PM
This year, Google's Research Scholar program for early-career professors is specifically solicitating proposals on large-language and multi-modal machine learning models for science:
research.google/outreach/resea…

Applications will open next week and are due by the end of November.
November 3, 2023 at 4:34 AM
Google Earth Engine has amazing datasets and functionality, but I've always wished it worked well with my favorite Python tools.

XEE (Xarray + Earth Engine) by my friend @alexmerose.com fills that gap!
github.com/google/Xee
GitHub - google/Xee: An Xarray extension for Google Earth Engine
An Xarray extension for Google Earth Engine. Contribute to google/Xee development by creating an account on GitHub.
github.com
October 11, 2023 at 6:58 AM