☁️ ❄️ EPFL atmospheric and climate scientists show that biological particles may induce rain events that could contribute to flooding and snowstorms, owing to their ability to precipitate ice formation in clouds. They call for an update of meteorological and climate models.

#ClimateScience #AtmosphericScience #ClimateModels

Read more: https://go.epfl.ch/UGG-en

Biological particles may be crucial for inducing heavy rain

EPFL atmospheric and climate scientists show that biological particles may induce rain events that could contribute to flooding and snowstorms, owing to their ability to precipitate ice formation in clouds. They call for an update of meteorological and climate models.

Regional climate signals pose new challenges for climate science

#ClimateScience has correctly predicted many aspects of the #climate system and its response to increased atmospheric #CarbonDioxide concentrations. Recently, discrepancies between the real world and our expectations of regional climate changes have emerged, as have disruptive new computational approaches.

What the authors describe as the dominant paradigm or "standard approach" of climate science has been developed over the last 60 years by applying fundamental laws of #physics to the climate system under the assumption that small-scale processes are determined by statistical averages dependent on large scales (parameterization).

As with the evolution of other scientific fields, discrepancies have emerged in climate science with respect to how regional #ClimateChange is evolving. For example, the eastern Tropical #Pacific has cooled contrary to all model predictions. Neither was the increased frequency of blocking weather conditions over #Greenland in summer anticipated.

In particular, discrepancies are accumulating in the tropics where changes in the large-scale tropical circulation are known to grow out of instabilities that occur at small and intermediate scales. These scale-coupling mechanisms do not operate in the current generation of #ClimateModels.

"The challenge for conceptual work will be to identify which physics missing from the standard approach is most important for regional changes, and how to incorporate it," says Stevens.

https://phys.org/news/2025-03-regional-climate-pose-science.html

Regional climate signals pose new challenges for climate science

Climate science has correctly predicted many aspects of the climate system and its response to increased atmospheric carbon dioxide concentrations. Recently, discrepancies between the real world and our expectations of regional climate changes have emerged, as have disruptive new computational approaches.

Phys.org
Warm seawater encroaches on major Antarctic ice shelf, raising sea level concerns

The vast Antarctic Ice Sheet holds more than half of Earth's freshwater. In several places around the continent, the ice extends over the ocean, where it forms large floating shelves. Observations suggest many of these ice shelves are thinning as they melt from below, with implications for ocean dynamics, global sea level, and Earth's climate.

Phys.org

"Whether through agricultural practices, deforestation, or urbanization, how modern humans use land has had an unprecedented impact on the planet. But historical information on human land use is lacking, impacting the quality of the climate models used today".

#climatemodels #impact #landuse
https://phys.org/news/2025-02-impacts-human-south-asia.html

Looking to the past to understand the impacts of human land use in South Asia

Whether through agricultural practices, deforestation, or urbanization, how modern humans use land has had an unprecedented impact on the planet. But historical information on human land use is lacking, impacting the quality of the climate models used today.

Phys.org
https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024EF004561
Looking at the data especially from the last 2 years regarding the growth of global temperatures, CO2 and sea levels, to claim that rude and oversimplified models can somehow represent the progression of climate events from now to 300 yrs is in itself something contrary to any scientific method. Which is the main purpose of the vast majority of currently research ?
#climatemodels #scientificmetod
George Broussard (@georgebsocial@mastodon.gamedev.place)

Attached: 1 image The two states of every programmer. #gamedev #programming

Gamedev Mastodon

After diving into this field for the last year, I very much agree with this bit:

"most of the near-term results using ML will be in areas where the ML allows us to tackle big data type problems more efficiently than we could do before. This will lead to more skillful models, and perhaps better predictions, and allow us to increase resolution and detail faster than expected. Real progress will not be as fast as some of the more breathless commentaries have suggested, but progress will be real."

https://fediscience.org/@Ruth_Mottram/113775294023850288
Ruth_Mottram - One of few #ClimateBlogs to still reliably get good comments, likely because of insightful content : @RealClimate has a very good piece by @climateofgavin on #AI in #climatemodels with which I concur completely

https://www.realclimate.org/index.php/archives/2024/12/ai-caramba/

Ruth Mottram (@Ruth_Mottram@fediscience.org)

One of few #ClimateBlogs to still reliably get good comments, likely because of insightful content : @RealClimate@portal.0svc.com has a very good piece by @climateofgavin@beta.birdsite.live on #AI in #climatemodels with which I concur completely https://www.realclimate.org/index.php/archives/2024/12/ai-caramba/

FediScience.org

One of few #ClimateBlogs to still reliably get good comments, likely because of insightful content : @RealClimate has a very good piece by @climateofgavin on #AI in #climatemodels with which I concur completely

https://www.realclimate.org/index.php/archives/2024/12/ai-caramba/

RealClimate: ¡AI Caramba!

RealClimate: 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 terms to maximize clarity. Machine Learning (ML) is a broad term to distinguish any kind of statistical fitting of large data sets to complicated

RealClimate | Climate science from climate scientists...
One of few #ClimateBlogs to still reliably get good comments, likely because of insightful content : @realclimate.org has a very good piece by @climateofgavin.bsky.social on #AI in #climatemodels with which I concur completely https://www.realclimate.org/index.php/archives/2024/12/ai-caramba/
Bluesky

Bluesky Social

If you've seen the hype about recent accomplishments of "AI" weather forecasting, and you're a #climate nerd, but not nerdy enough to have an informed opinion on what these advances in machine learning imply for modeling the climate of our rapidly warming planet, you may find this post clarifying. I did.

Gavin Schmidt, "¡AI Caramba!", RealClimate, 28 December 2024
https://www.realclimate.org/index.php/archives/2024/12/ai-caramba/

#AI #ML #ClimateModels

RealClimate: ¡AI Caramba!

RealClimate: 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 terms to maximize clarity. Machine Learning (ML) is a broad term to distinguish any kind of statistical fitting of large data sets to complicated

RealClimate | Climate science from climate scientists...