climate

This thread analyzes the rapid intensification of a Super El Niño in 2026-2027, citing NOAA data and projecting significant impacts on global commodity prices, agricultural production, and supply chains, with implications for financial markets.

Despite the expiration of a key US tax credit in 2025, heat pump sales continue to rise, outpacing natural-gas furnaces. The article explores the reasons behind the sustained growth, including efficiency gains and seasonal trends.

This paper proposes TSSM, a triaxial state space model for global station weather forecasting that incorporates historical data aligned by period to improve long-horizon and extreme event prediction. It achieves state-of-the-art performance on the large-scale Weather-5K dataset and demonstrates strong robustness under missing observations.

Researchers have produced the first global map of the underground mycorrhizal fungal network, estimating it spans 110 quadrillion kilometers and stores massive amounts of carbon, with significant implications for climate regulation.

An analysis of California's dairy digester carbon offset program reveals that swapping methane for CO₂ may reduce short-term warming but locks in long-term warming, highlighting flaws in climate credit math.

This paper compares top-down and bottom-up approaches for collecting text-based data about disasters from news articles, using German news about landslides as a case study.

A study reveals that weathering of organic carbon can release CO2, amplifying warming, while silicate weathering still draws down CO2 but must work harder. This adds a small amplifying effect to human-caused warming over centuries.

A UN report reveals that by 2030, AI data centers could consume water equivalent to the basic annual needs of 1.3 billion people, with 80-90% of energy used for daily operations rather than training. Generating a single AI image uses over 1000 times more energy than a basic text task.

The Trump administration took down climate.gov, but volunteers and former staff preserved the data and relaunched it as a nonprofit site (climate.us), restoring lost climate information and planning to expand resources.

Anthropic becomes the first AI startup to join the Frontier carbon removal coalition, contributing to a new $915 million funding tranche that brings total pledges to $1.8 billion for carbon removal projects.

Nairobi entrepreneurs are adopting solar-powered grain mills to reduce costs and emissions. The article highlights Agsol's solar mill used by shop owner Milcah Wanjiru, which is cheaper than diesel and allows small batches.

For the first time, solar power generated more electricity in the US than coal in May, marking a milestone in the country's energy transition. The milestone underscores solar's growth despite federal policies favoring coal, with solar and battery storage now dominating new power generation.

The NSF's decommissioning of Ocean Station Papa, a key ocean monitoring network, will leave Alaskans with reduced weather forecasting capabilities and increased vulnerability for coastal communities.

Amazon employees are urging Seattle to impose a one-year moratorium on new data centers due to concerns about energy consumption, water use, and AI's environmental impact. The Seattle City Council is set to vote on the proposal.

Proposes TriHead-GAN, a transformer-based GAN with a triple-head discriminator that jointly supervises distributional authenticity, cross-variable dependencies, and temporal smoothness for generating realistic carbon emission time series, outperforming baselines on multiple datasets.

The article critically examines the use of machine learning in weather and climate modeling, highlighting its practical strengths and inherent limitations while cautioning against overhyped claims of a revolution.

Researchers propose a Physics-Informed Machine Learning (PIML) framework that integrates hydrological constraints into an LSTM loss function to improve short-term flood forecasting, particularly in data-scarce regimes. A 'Trend Alignment' constraint enforcing consistency between precipitation and discharge trends improves Nash-Sutcliffe Efficiency and eliminates unphysical predictions during extreme events.

CHAM-net introduces a contrastive hierarchical adaptive meta-network that captures site-specific and cross-year dynamics for robust global methane flux prediction, outperforming baseline methods on simulation and observational datasets.

NOAA predicts a below-average 2026 Atlantic hurricane season due to El Niño, but warns that even quiet years can produce catastrophic storms. The agency is deploying AI weather models developed with Google DeepMind to improve hurricane track predictions.

Tom Steyer, billionaire and candidate for California governor, discusses his stance on taxing billionaires, regulating AI, and addressing climate change, while navigating the tension between taxing the wealthy and keeping them in the state.