Research modeling the climate and its extremes. Covers climate extremes, ocean-dipole types, weather forecasting, and AI ecosystem monitoring.
Researchers at Stanford University used machine learning to analyze high-resolution remote-sensing data of ice movements in Antarctica, gaining new insights into the fundamental physics governing the large-scale movements of the Antarctic ice sheet. The study reveals that most of the ice shelf is anisotropic, with different physical pr...
Researchers propose a standardized taxonomy of cascading hazards and interactions between people and urban systems. An integrated risk assessment framework considers multiple dimensions and individual behaviors to improve early warning systems.
A new study shows that climate change affects short-term precipitation events lasting hours by significantly increasing their frequency, while longer-term rainfall events lasting days are influenced by global weather phenomena like El Niéo. This distinction is crucial for assessing the risk of flooding in different regions.
Researchers introduce ClimID-UDA, a novel approach to cross-regional crop classification using climate indicator discrepancies. The method enhances crop classification accuracy by up to 20% and offers a scalable solution for global agricultural monitoring.
Scientists studied plant fossils and climate models to understand the Permian-Triassic mass extinction. The study found a 10°C rise in global temperatures and dramatic changes in ecosystems.
The study categorizes CROP-AP models into four key types, highlighting five major applications in agricultural productivity simulation. Future research priorities focus on strengthening model validation and simulating multi-scale interactions to support sustainable global food production.
A new study reveals that Arctic sea ice loss drives drier weather over California, especially in winter, and wetter conditions over Spain and Portugal. The research isolates the effect of Arctic sea ice melting from other climate change factors.
A study by MIT researchers found that climate change can cause the thermosphere to shrink, reducing atmospheric drag and allowing space junk to remain in orbit for decades. This could lead to increased collisions and debris, threatening the sustainability of satellite operations.
A special issue of the Journal of Dairy Science provides detailed technical recommendations for developing and implementing feed additives to reduce methane emissions from ruminants. The guidelines cover testing, trial, and modeling phases to ensure efficacy and safety.
A study predicts East Coast estuaries will face devastating consequences from increased marine heat waves, with potential ecosystem collapse and job losses. The researchers found strong connections between estuaries in similar geographic regions, driven by atmospheric heat exchange.
A new study combines satellite collar data with specialized cameras to shed light on the mysterious and important stage of maternal denning. The researchers found that using both methods can accurately predict when polar bears will emerge from their dens and how external factors like temperature influence their behavior.
Researchers identify cloud-radiation feedback as dominant source behind differing tropical Pacific sea surface temperature (SST) changes in climate models. The study's findings highlight the critical role of these feedbacks in shaping future warming patterns.
Researchers found a correlation between solar heat and seismic activity, suggesting that incorporating solar activity predictions into detailed Earth temperature models can improve earthquake forecasts. This study sheds light on the role of solar heat in triggering earthquakes, potentially providing a more accurate prediction method.
A new study led by Colorado State University found that agricultural nitrogen fertilizer is the primary cause of seasonal carbon cycle swings. This discovery adds to scientific understanding of the carbon cycle and could help inform climate change mitigation strategies.
The US weather enterprise faces significant risks due to federal science funding cuts, which could lead to reduced weather forecasting accuracy and increased vulnerability to hazardous weather. The value of weather information to the US economy exceeds $100 billion annually.
Emissions from SUVs and light-duty trucks cause 90% of nitrogen dioxide-related deaths, with suburban driving linked to greatest health damages. The study's findings inform geographically targeted transportation policies and climate action plans for Boston and cities nationwide.
A new study led by Qian Cheng found that unusual atmospheric circulation accounted for 83% of a record-breaking cold event in eastern China. The warming effect of climate change reduced the event's severity by up to 22%.
A new study from USC Dornsife finds that LA's urban greenery absorbs up to 60% of daytime fossil fuel CO2 emissions in spring and summer, providing valuable insights into the impact of trees on air quality. The research provides data-driven insights for future planting efforts and informs the USC Urban Trees Initiative.
Researchers will use airborne GPR and ground-based TEM to collect rich geophysical data, estimating carbon storage and gas emissions in peatlands across a latitudinal gradient. The project aims to reduce uncertainty in these predictions and provide valuable information on how to better protect carbon stocks.
Research advances higher-order networks to capture multi-agent interactions, enabling accurate modeling of biological, social, and physical systems. The Dirac-Bianconi operator provides a powerful generalization of the graph Laplacian, encoding local and global interactions across different topological dimensions.
A £4.25m project will investigate 'tipping points' in marine ecosystems, which could have devastating consequences for the UK's fishing industry and global biodiversity. The TiMBER project, led by the University of East Anglia, aims to develop tools to assess risks and predict changes in marine biogeochemistry.
Recent studies suggest that rising temperatures could disrupt the balance of Earth's climate by increasing plant water loss. In extreme heat, plants may lose too much water to conserve it, limiting photosynthesis and reducing their role as a carbon sink.
Researchers discovered rate-induced tipping in Daisyworld, a model that regulates temperature through light and dark daisies. This finding mirrors observations in other models and real-life ecosystems, highlighting the danger of rapid environmental changes.
Archaeologists reconstructed human land use and land cover over the past 12,000 years in South Asia, revealing hunter-gatherer practices as dominant across periods. The study provides critical information for modeling climate impacts of human populations.
The motion of particles in high-energy nuclear collisions follows a Lévy-stable distribution, confirming the interdisciplinary nature of the phenomenon. This finding has implications for fields such as biology, earth sciences, and economics.
A recent study reveals a significant long-term decline in downward surface solar radiation globally, with significant decadal variations observed over land. The research highlights the role of water vapor in DSSR changes, which was previously overlooked, and shows that future DSSR changes will depend heavily on emission scenarios.
A team of scientists found that Earth's current ice-covered state is not typical for the planet's history and was only achieved through a lucky coincidence. The researchers concluded that no single process could drive these cold climates, and that multiple processes working together were necessary.
Research quantifies hydrogen economy's role in making society more sustainable, concluding that electrification is the most cost-efficient route for most economic sectors. Hydrogen use is projected to be around 10% of final energy consumption, with a critical role in heavy industry and transportation.
Researchers at University of Florida identify native species similarity as key driver for invasion spread in eastern US, offering insights for conservationists and land managers. The study updates environmental resistance modeling to consider species similarity, soil type, and human activity.
A new study reveals that dust storms picking up black carbon from heavily-polluted areas and depositing it in the mountains darkens the ice and snow, causing it to melt faster. This regional environmental problem is a second, more local cause of glacier loss in the Himalayas.
A new study reveals that climate change is driving intensifying wildfires by altering vegetation and humidity levels, but not significantly impacting lightning strikes. The simulations predict a 14% increase in global area burned by fires annually with every degree of global warming.
A global real-time monitoring system is being developed to track bleaching severity, crown-of-thorns starfish populations, disease outbreaks, and reef fish abundance. The integrated system aims to provide predictive models for conservation efforts, enabling earlier intervention.
A new study published in Nature Communications Earth and Environment finds that Arctic cyclones may contribute to the underpredicted decline of sea ice extent. The research suggests two theories: turbulent seas breaking up larger ice floes and upwelling increasing temperatures that help melt younger, thinner ice.
Researchers generated a dataset of water flow beneath the entire Antarctic Ice Sheet, improving projections of sea level rise. The model predicts higher degrees of glacier melt and mass loss by the end of the century.
A new study simulates a medium-sized asteroid collision with Earth, revealing dramatic disruptions in climate, atmospheric chemistry, and global photosynthesis. However, ocean plankton growth surprisingly recovers quickly and even increases after the impact, potentially alleviating emerging food insecurity.
A new study by Purdue University reveals that improved crop varieties led to global benefits for the environment and food system sustainability. The analysis found that reduced agricultural land use saved 1,043 animal and plant species, with most avoided losses located in biodiversity hot spots.
A new study by scientists at the University of Rochester suggests that atmospheric wind has a surprising impact on ocean eddies, which are circular currents of water about 100 kilometers wide. The research reveals that wind can both energize and dampen eddies, depending on their spin direction.
A new research group aims to enhance climate models by accounting for 3D cloud radiation transport, combining satellite data with high-resolution ground-based observations. The project involves a large field campaign in 2026 to record optical and microphysical cloud properties.
A recent study analyzed the devastating flood disaster in the Himalayas in October 2023, which destroyed large areas along and surrounding the Teesta River. The researchers reconstructed the exact time of its onset using high-resolution satellite images and digital elevation models.
A study by University of Toronto researchers links polar bear population decline to extended energy deficits caused by a lack of food on dwindling sea ice. The model, tracking the bears' energy balance, shows reduced reproduction and cub survival rates due to shorter hunting seasons.
Researchers found no increase in large iceberg sizes over the last half century, contradicting climate change expectations. Instead, frequent small calving events have dominated ice shelf loss, suggesting 'death by a thousand cuts',
A recent University of Washington study found that a slower increase in atmospheric carbon dioxide levels has less impact on the Atlantic Ocean's circulation. The research, published in PNAS, suggests that this slowdown allows the ocean system more time to adapt to rising CO2 levels and mitigates its effects.
Researchers at Harvard University used photochemical modeling to simulate how ancient Mars' climate was affected by atmospheric chemistry and crustal hydration. They found that episodic warm spells were driven by crustal hydration, leading to the buildup of hydrogen in the atmosphere.
A new study projects global sea-level rise between 0.5 and 1.9 meters by 2100 under a high-emissions scenario, with the very likely range being 90% probability for the event to occur. The fusion approach combines strengths of existing models with expert opinions, offering a clearer picture of future sea-level rise.
A new study challenges conventional models and reveals biochar's exceptional capacity for long-term carbon storage. Biochar is shown to be far more effective at long-term carbon storage than previously thought.
Scientists at the University of Lausanne used AI to simulate the last Alpine glaciation, finding ice covers 35-50% thinner than previous models. The new approach enables unprecedented accuracy and resolution, making it possible to describe complex topography numerically.
A new study by the University of Granada's DaSCI institute uses deep generative vision models to create highly realistic satellite images of future climate-related events. The model outperforms pure deep learning and manual solutions, reducing prediction errors and improving image reliability.
A recent study by Woods Hole Oceanographic Institution scientists found that the AMOC has not declined in the last 60 years, contrary to previous predictions. The research used climate models and reanalysis data to reconstruct the AMOC's past behavior, indicating a more stable system than expected.
Researchers developed an explainable deep learning model to predict and analyze HABs in Chinese lakes and reservoirs, achieving significant improvement over conventional machine learning methods. The model identified water temperature as the most influential factor driving algal bloom dynamics.
Researchers developed a new data assimilation algorithm using the LETKF technique to enhance global precipitation estimates. The model improved accuracy and computational efficiency, making it suitable for large-scale applications, particularly in mountainous regions.
The study introduces a novel framework that accurately predicts global warming caused by greenhouse gas emissions without relying on complex climate models. It confirms human-caused greenhouse gas emissions drive observed global warming, independently of conventional approaches.
A team led by the University of Tokyo has created a nearly 20-year-long dataset of the entire atmosphere, enabling new research on previously difficult-to-study regions. The dataset spans multiple levels of the atmosphere from ground level to the lower edge of space and could improve climate modeling and seasonal weather forecasting.
Researchers at Iowa State University have rewritten the equation for deformation and flow of watery glacier ice, which could lead to more accurate models predicting sea-level rise. The new value of the stress exponent 'n' is 1.0, indicating a linear relationship between stress and deformation speed.
The project creates a comprehensive U.S.-Japan flood risk data inventory and develops a two-way coupled, multi-scale, agent-based model that considers marginalized groups. Researchers will use the developed model to evaluate the impact of insurance policies on these groups.
A new study introduces an AI-driven method for estimating above-ground carbon at individual tree level using high-resolution satellite imagery and machine learning algorithms. This approach offers a more precise tool for measuring carbon sequestration, critical for climate adaptation and land management strategies.
A team of researchers integrated historical records from missionaries and early explorers in Tanzania to enhance the accuracy of climate change models. The study provides a longer record of climate change in the region, which can help verify climate models over the data-sparse Global South.
Computer models predict that climate change will lead to an increase in spongy moth outbreaks, causing widespread damage to forests. The fungus that normally curbs the moths' spread is expected to decline, allowing the moths to destroy more trees as temperatures rise.
A research team led by Dr Sophie Warken analyzed dripstones from the Cloşani Cave in Romania to understand precipitation variability over a period of approximately 20,000 years. The findings show that dynamic processes like the North Atlantic jet stream influence regional changes in precipitation.
Scientists have used data from CryoSat-2 and ICESat-2 to track changes in the Greenland Ice Sheet's thickness, revealing an average thinning of 1.2 meters between 2010 and 2023. The study confirms that combining satellite measurements can produce a more reliable estimate of ice loss.
A team from the University of Cambridge has developed a model to predict desert locust swarms, enabling national agencies to respond quickly. The model uses weather forecast data and computational models to forecast locust swarm movements both short and long-term.