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Simon Driscoll

@simon-driscoll.bsky.social

Senior Research Associate, ICCS @ Department of Applied Mathematics and Theoretical Physics, Uni of Cambridge. DPhil (PhD) Oxford Physics. Reading Uni (SASIP, 2021-25, Schmidt Sciences). ATI 2025. Advisor Arctic Basecamp. ML/AI, physics, climate, & more.

442 Followers  |  131 Following  |  23 Posts  |  Joined: 20.11.2024  |  2.1217

Latest posts by simon-driscoll.bsky.social on Bluesky

Deadline extended one day to 5pm EDT 31st July! :)

Check out our great presenters and submit your abstracts on ML for SGS parameterizations, emulation and hybrid modelling here: agu.confex.com/agu/agu25/pr...

30.07.2025 23:35 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Deadline: Wednesday, 30 July 23:59 EDT/03:59 UTC

Session Coveners: Simon Driscoll (Cambridge), Sara Shamekh (NYU), Akshay Subramaniam (NVIDIA), Aakash Sane (Princeton), Karan Jakhar (Chicago/Rice)

We look forward to seeing you all there!

08.07.2025 22:54 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Developments in Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation and Hybrid Modeling Machine learning is reshaping the representation of complex physical processes in Earth system models, offering new avenues for parameterization, emulation, and hybrid modeling. This session focuses o...

Join our invited speakers - Ching-Yao Lai (Stanford), Sophie Abramian (Columbia), and Adam Subel (NYU) - at our #AGU25 session, "Developments in Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation and Hybrid Modeling".

Details: agu.confex.com/agu/agu25/pr...

08.07.2025 22:53 β€” πŸ‘ 0    πŸ” 1    πŸ’¬ 1    πŸ“Œ 1

Deadline: Wednesday, 30 July 23:59 EDT/03:59 UTC

Session Coveners: Simon Driscoll (University of Cambridge), Sara Shamekh (New York University), Akshay Subramaniam (NVIDIA), Aakash Sane (Princeton University - @aakashsane.bsky.social), Karan Jakhar (University of Chicago/Rice University)

24.06.2025 05:26 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Developments in Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation and Hybrid Modeling Machine learning is reshaping the representation of complex physical processes in Earth system models, offering new avenues for parameterization, emulation, and hybrid modeling. This session focuses o...

We are excited to announce our AGU 2025 session has been accepted! Join us in New Orleans, December 15–19, 2025 for β€œDevelopments in Machine Learning Across Earth System Modeling: Subgrid-Scale Parameterizations, Emulation and Hybrid Modeling”.

Abstract submission: agu.confex.com/agu/agu25/pr...

24.06.2025 05:24 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

Absolutely! Anytime. :)

28.05.2025 22:53 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Preview
Storm clouds threaten a promised AI revolution in weather prediction New AI models from tech giants are set to revolutionise weather prediction. But as our climate becomes more extreme, we need to ensure broad public access to their forecasts, says Annalee Newitz

Myself and Andrew Charlton-Perez talk to Annalee Newitz @annaleen.bsky.social for the New Scientist about AI, weather and climate - involving some of our/our groups recent (and upcoming) research.

Article out today:

www.newscientist.com/article/mg26...

@newscientist.com #ai #ml #weather #climate

28.05.2025 22:15 β€” πŸ‘ 4    πŸ” 1    πŸ’¬ 1    πŸ“Œ 1
Preview
Anemoi: open-source winds of change in European weather forecasting By: Prof Hannah Cloke, Department of Meteorology, University of Reading and ECMWF Fellow Earlier this month I opened my inbox to the welcome news that the European Meteorological Society has chosen…

An article on "Anemoi: open-source winds of change in European weather forecasting" by Prof. Hannah Cloke (@hancloke.bsky.social) is the topic of the latest @unirdg-met.bsky.social research blog.

You can check it out here!

blogs.reading.ac.uk/weather-and-...

11.05.2025 12:17 β€” πŸ‘ 19    πŸ” 7    πŸ’¬ 0    πŸ“Œ 1

The official link is only in Italian but you can download the call in English from the main page linked below under β€œCall for applications”. Share widely! :)

04.04.2025 16:05 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Preview
Rif. 1508 - Bando per 1 posto da ricercatore a tempo determinato tipo A - DIFA - GSD 02/PHYS-05 - SSD PHYS-05/B - BO

3 years Junior Assistant professor position in the area of DA and ML at the University of Bologna! Deadline: April 18 at 12:00pm CEST.

Contact Prof Alberto Carrassi: alberto.carrassi@unibo.it and apos.ricercatoritempodeterminato@unibo.it for more details.

bandi.unibo.it/s/apos5/rif-...

04.04.2025 16:03 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 2    πŸ“Œ 0
Preview
Applying solar wind data assimilation to the WSA coronal model By: Dr. Harriet Turner The solar wind is a constant stream of charged particles that flows from the Sun and fills the solar system. It is an important aspect of space weather, which is the term we …

An article on "Applying solar wind data assimilation to the WSA coronal model" by Dr. Harriet Turner @harrietturner.bsky.social is the topic of our latest @uor-research.bsky.social research blog.

You can check it out here!

blogs.reading.ac.uk/weather-and-...

30.03.2025 15:05 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Preview
Reconciling Earth’s growing energy imbalance with ocean warming By:Β Prof. Richard Allan (Professor of Climate Science) The exceptional global warmth of 2023 and 2024 generated much idle chit chat in Meteorological circles and following a summer Met department c…

An article on "Reconciling Earth’s growing energy imbalance with ocean warming" by Prof. Richard Allan (@rpallanuk.bsky.social) is the topic of our latest research blog.

You can check it out here!

blogs.reading.ac.uk/weather-and-...

23.03.2025 23:39 β€” πŸ‘ 4    πŸ” 1    πŸ’¬ 1    πŸ“Œ 1
Preview
The value of observations for weather prediction in the age of machine learning By:Β Prof Sarah Dance (Professor of Data Assimilation) Last week, on 25th February 2025, our colleagues at ECMWF (European Centre for Medium-range Weather Forecasts) took their deep-learning-based g…

An article on "The value of observations for weather prediction in the age of machine learning" by Prof. Sarah Dance is the topic of our latest research blog.

You can check it out here!

blogs.reading.ac.uk/weather-and-...

10.03.2025 09:59 β€” πŸ‘ 5    πŸ” 2    πŸ’¬ 0    πŸ“Œ 0
Preview
Is climate change shifting the North Pacific jet stream? By: Dr. Matthew Patterson Wavy bands of fast flowing air, called jet streams, are some of the most recognisable features of the Earth’s atmospheric circulation (figure 1). They have a critical impa…

An article on "Is climate change shifting the North Pacific jet stream?" by Dr. Matthew Patterson is the topic of our latest research blog.

You can check it out here!

blogs.reading.ac.uk/weather-and-...

02.03.2025 21:47 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Preview
Impact of Hydrogen on Atmospheric Composition and Climate By: Dr. Tanusri Chakraborty As we move toward net-zero and low-carbon emissions, Hydrogen (Hβ‚‚) is expected to play a crucial role as an alternative energy source. Hβ‚‚ is considered a clean fuel, as …

An article on the "Impact of Hydrogen on Atmospheric Composition and Climate" by Dr. Tanusri Chakraborty is the topic of our latest research blog.

You can check it out here!

blogs.reading.ac.uk/weather-and-...

23.02.2025 19:13 β€” πŸ‘ 2    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0
Preview
Renewable energy lulls: understanding European weather for when the wind doesn’t blow and the sun doesn’t shine By: Salim Poovadiyil Weather and climate model data play an increasingly vital role in assessing climate risks within energy system operations and planning. The reliability of these assessments hea…

An article on "Renewable energy lulls: understanding European weather for when the wind doesn’t blow and the sun doesn’t shine" by Dr. M Salim Poovadiyil is the topic of our latest research blog.

You can check it out here!

blogs.reading.ac.uk/weather-and-...

21.01.2025 17:07 β€” πŸ‘ 2    πŸ” 1    πŸ’¬ 0    πŸ“Œ 0
Data-Driven Science: Developments in Machine Learning Subgrid-Scale Parameterizations and in Reanalyses Across Earth System Modeling I Oral Subgrid-scale (SGS) parameterizations estimate effects of unresolved processes without modeling them directly and are often a large source of uncertainty in Earth system models (ESMs). The need to imp...

Are you interested in knowing about the latest developments in sub-grid scale parameterizations in Earth System Models? Attend our AGU24 session on Thursday, 12 Dec. from 8.00 to 10.00 am, location: Marquis 12-13 (Marriott Marquis)
agu.confex.com/agu/agu24/me...
🌊

11.12.2024 23:59 β€” πŸ‘ 2    πŸ” 2    πŸ’¬ 1    πŸ“Œ 0

Thank you Dominic! :) Hope things go great, and see you soon indeed! :)

28.11.2024 23:53 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

(4/4) Conveners: Simon Driscoll (Reading), Sara Shamekh (NYU/Courant), Aakash Sane (Princeton - @aakashsane.bsky.social), Laura Mansfield (Stanford/now Oxford - @lauramansfield.bsky.social), Michael Bosilovich (NASA), Arun Kumar (NOAA); ECR: Will Gregory (Princeton - @willjgregory.bsky.social).

28.11.2024 20:21 β€” πŸ‘ 4    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
Data-Driven Science: Developments in Machine Learning Subgrid-Scale Parameterizations and in Reanalyses Across Earth System Modeling I Oral Subgrid-scale (SGS) parameterizations estimate effects of unresolved processes without modeling them directly and are often a large source of uncertainty in Earth system models (ESMs). The need to imp...

(3/4) If this is interesting then consider our AGU session where this and more like it will be being presented as talks: agu.confex.com/agu/agu24/me... and as posters: agu.confex.com/agu/agu24/me... Please get in contact if there’s anything I can help you with. Look forward to seeing you there!

28.11.2024 20:16 β€” πŸ‘ 3    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0

(2/4) Incorporating physics-informed metrics into the equation discovery approach, they developed a model that accurately captures inter-scale energy and enstrophy transfers; leading to the model outperforming traditional physics-based models in representing extreme events and improving forecasting.

28.11.2024 20:16 β€” πŸ‘ 0    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0
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(1/4) Karan Jakhar (University of Chicago and Rice University) and his colleagues used machine learning to develop a subgrid-scale parameterization for geophysical turbulence that is not only effective but also analytically derivable using Taylor series expansion.

28.11.2024 20:15 β€” πŸ‘ 7    πŸ” 1    πŸ’¬ 1    πŸ“Œ 0

Thank you! :)

22.11.2024 07:22 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 0    πŸ“Œ 0

Me too please! :)

22.11.2024 00:26 β€” πŸ‘ 1    πŸ” 0    πŸ’¬ 1    πŸ“Œ 0

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