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Combining output from climate model large ensembles with neural networks can be a really useful tool for signal-to-noise metrics, like timing of emergence or distinguishing regional change patterns from internal climate variability. Here's an overview on some of our recent work related to this topic: https://lnkd.in/eZ4tPwQT #MachineLearning #ClimateChange #ClimateVariability #XAI

Deep learning revolutionizing climate science, improving our understanding of the climate system, enhancing weather forecasts, and helping us better prepare for extreme weather conditions. Thanks for posting https://lnkd.in/gcBThQnW Study conducted at ClimRise Lab Kent State University

Excited to share 🌟: SEEDS is pioneering the future of weather forecasting with generative AI! 🌦️💡 https://lnkd.in/eapYmvxa This breakthrough demonstrates how AI can enhance numerical weather prediction, offering a glimpse into faster, more accurate forecasts. We're eager to see how this tech will advance climate risk assessment and uncertainty quantification in climate projections. The future of climate science is here! 🚀🌍 #GenerativeAI #WeatherPrediction #ClimateInnovation

Aurora: The AI Revolution in Weather Forecasting! 🌍 Aurora, a revolutionary foundation model of the atmosphere trained on over 1 million hours of diverse weather and climate data. Aurora leverages vast amounts of data to learn powerful, general-purpose representations. ⚡️With Aurora, we can now generate 5-day global air pollution predictions and 10-day high-res weather forecasts in under a minute. These forecasts outperform state-of-the-art classical simulation tools and specialized deep learning models. A game-changer for environmental forecasting! 🔮 Foundation models like Aurora hold immense promise to transform how we model the Earth's complex, interconnected subsystems like the atmosphere, oceans, land and ice. The future of Earth system modeling is here, and it's powered by AI! https://lnkd.in/gBbx7YGS

AI Reveals Hidden Historical Climate Extremes 🌍 Did you know that artificial intelligence is uncovering previously undetected historical climate extremes? Here's what I learned from recent research: 1. Limitation of Weather Data - Many global weather stations, especially in Africa and polar regions, lack consistent historical data due to damaged equipment and unmonitored periods. - This creates significant gaps in understanding past climate conditions. 2. AI-Powered Reconstruction - A team at the German Climate Computing Center used AI to rebuild the missing parts of historical weather records. - Their tool, Climate Reconstruction and Analysis with AI

Today in #Valencia: The ELLIS/ELISE workshop ‘AI for Learning Weather & Climate’ begins. International experts in #AI and #MachineLearning meet to discuss recent advances for weather prediction, climate emulation and Earth system modeling. AI-based tools are revolutionizing Earth and climate sciences, weather forecast and the way humans analyze and respond to extreme climate events such as droughts, forest fires, heat waves, floods and climate-induced migrations. Read this article, in which Gustau Camps-Valls, Co-Director of the #ELLISProgram ‘Machine Learning for Earth and Climate Sciences’, explains the crucial role of AI in addressing #ClimateChange: https://lnkd.in/eWMHmMgS #AIforClimate #ELLISforEurope

Forschungszentrum Jülich, in collaboration with esteemed partners in the Helmholtz-Gemeinschaft / Helmholtz Association, is revolutionising AI's role in scientific breakthroughs! With a whopping €23 million in funding, the Helmholtz Foundation Model Initiative (HFMI) is propelling the development of cutting-edge AI foundation models. These models, akin to the powerful #ChatGPT from OpenAI, are set to transform various scientific domains, from climate research to materials science. Two out of the four pioneering pilot projects are spearheaded by Forschungszentrum Jülich, with a focus on #ClimateResearch and the global #CarbonCycle. By harnessing the potential of AI, they aim to craft the most precise weather and climate models ever conceived, unravelling mysteries of our planet's ecosystem. The HClimRep project, a standout initiative within HFMI, promises groundbreaking insights into the interactions between the atmosphere, ocean, and sea ice. Through the development of an AI foundation model, researchers envision a future where climate predictions are not only accurate but also accessible to all, empowering us to combat climate change more effectively. Join us in celebrating this monumental leap forward in scientific innovation, made possible by the collaborative efforts of Forschungszentrum Jülich and its esteemed partners! #AIforScience #ClimateResearch #InnovationAtWork https://lnkd.in/exBubHpN

How can we harness the power of #AI to tackle the twin #climate & #biodiversity crises? In our latest ai@cam blog, we speak to Anil Madhavapeddy, Professor of Planetary Computing, about how our new AI-deas project can empower decision-makers to address the biggest challenge of our generation. The new interdisciplinary team aims to build up detailed models of the world that can be queried by #policymakers to help make informed decisions. Prof Madhavapeddy said: "In time, we want to make information about the opportunity cost of the natural world available to anyone who’s making essential decisions in this area." Read the full blog below ⬇ https://lnkd.in/eUVTKYfU

I compulsively read every one of these climate science model articles; they are so interesting and obviously incredibly important given the climate challenges the world is facing. Our previous model FourCastNet (based on Fourier neural operators) could forecast weather to 25km resolution, but the new CorrDiff model uses diffusion to downscale from 25 to 2km accuracy... fine-grained enough to predict local damage to specific infrastructure. #ai #climate #nvidiaresearch