Articles tagged with Weather Simulations
A new study harnesses GNSS-R technology to accurately measure sea ice thickness, offering a vital tool for climate scientists and polar explorers. The three-layer model significantly enhances the precision of thickness estimation, making it applicable to ice thicknesses up to 1.1 meters.
A new model developed by researchers at the University of São Paulo combines physical parameters and machine learning to predict storm tides. The model uses physics-informed machine learning, which harmonizes physical models with measured data to produce more precise forecasts.
Researchers used a weather model to pinpoint the source of wintertime precipitation in Arizona, finding it comes from a central Pacific moisture source rather than El Niño/La Niña events. The study's findings could improve seasonal precipitation forecasts for the region and potentially other areas globally.
Researchers developed a quantum annealing approach to accelerate data assimilation, significantly reducing computational cost. The method achieves comparable accuracy to conventional approaches but in a fraction of the time.
Texas A&M University researchers have developed a 3D visualization technology to identify potential outcomes of hurricane flooding before it occurs. This allows for improved safety and reduced damage costs. The technology can also model specific buildings, accounting for basements, back entrances, and windows.
A study published in Royal Society Open Science reveals that corals use multiple environmental inputs to synchronize their spawning timing. Water temperature is identified as the primary trigger for determining the annual window of opportunity, with rainfall and solar radiation also playing a role.
A new study suggests that the sun's magnetic field could arise from instabilities in the outermost layers of the sun, rather than deep within. This finding may enable scientists to better forecast solar activity and space weather.
Researchers developed an impact-based forecasting system that combines various models to predict flood impacts with high resolution. The system enables early warnings for evacuation, reducing population and property damage.
Professor Cristiana Stan of George Mason University will conduct an evaluation of subseasonal prediction skill using foundational models, focusing on Madden-Julien Oscillation and its teleconnections. The funding will contribute to making weather and climate applications faster and more accurate.
A new model combines wildfire smoke forecasts and ground-based sensor data to help public health officials plan targeted interventions. The researchers found that urban and rural communities already burdened by pollution face higher air pollution levels during unexpected smoke events.
A study found that heavy snowfall and rain contribute to earthquake swarms in northern Japan by altering underground pressure. Climate conditions are linked to seismic activity, with the timing of intense precipitation events correlating with the start of quakes.
A recent study found that approximately 30% of India's PM2.5 air quality improvements can be attributed to favorable meteorological conditions, highlighting the need for additional mitigation measures. The researchers also noted that emissions of key PM2.5 precursors have not decreased and may indicate ineffective or under-enforced pol...
New research shows climate change will cause more severe combined wind-rain extremes in the UK and Ireland, leading to increased flooding and damage. The study found that stronger winds and heavier rainfall are likely to occur together, posing challenges for coastal areas and emergency response resources.
A recent analysis of cloud measurements and satellite data suggests that even tiny aerosol particles may play a significant role in cloud formation. This finding challenges current models and could have significant implications for predicting future climate change.
A new study by the University of Reading demonstrated that AI weather forecasts can predict storm paths and intensities with similar accuracy to traditional models. However, AI systems underestimated Storm Ciaran's maximum wind speeds due to limitations in predicting certain atmospheric features.
Researchers found that modern weather models can accurately predict satellite movements affected by weather events like tropical cyclones with tall clouds. This understanding enhances satellite tracking and control, improving efficiency and reliability of satellite operations.
A team of over 100 scientists from Brazil and the US ran high-resolution simulations of South America's past and future climate using a weather research and forecasting model. The goal is to better understand hydroclimatic processes and inform adaptation measures for millions affected by climate change.
A recent machine learning study has discovered a surprising link between wildfires in the western United States and hailstorms in the central US. The research, led by Jiwen Fan, used ML algorithms to analyze vast datasets spanning two decades, predicting hail storms with remarkable accuracy.
A team of researchers developed an AI-powered computer vision model to detect Brazilian wild animals on roads and warn drivers in real-time. The system uses roadside cameras and portable computers to identify species such as anteaters, wolves, and tapirs, with the potential to save lives and reduce roadkill.
Researchers from Kyushu University found that ocean-atmosphere coupling enhances teleconnection patterns, leading to more meandering jet streams and extreme weather events. The study highlights the significance of extratropical ocean-atmosphere interactions in climate variability.
The University of Leeds says Africa needs significant investment in scientific infrastructure and science careers to adapt to climate change. Gaps in understanding the science behind tropical weather systems hinder African weather forecasting, leaving half the population without early warnings.
Researchers at University of Missouri are developing software that allows drones to fly independently, perceiving and interacting with their environment while achieving specific goals. This technology has the potential to assist in mapping and monitoring applications, such as 3D or 4D advanced imagery for disaster response.
A new MIT-derived algorithm corrects coarse climate model predictions by 'nudging' them toward more realistic patterns, leading to more accurate forecasts of extreme weather events. The approach uses machine learning and dynamical systems theory to improve the resolution of large-scale climate models.
A new study predicts that Australia's soil will become a net emitter of carbon dioxide, releasing more CO2 into the air than it absorbs. This could account for 8.3% of current emissions and worsen climate change unless farming methods are improved.
Research suggests that warmer fall seasons may lead to colony collapse in honey bees due to increased flying time. However, cold storage for colonies could help reduce the risk of colony collapse by allowing bees to cluster earlier and save workers.
A new study finds that extreme tropical cyclone rainfall is increasing across the continental US, while climate warming restricts 'outdoor days' for people living in developing countries. Additionally, air pollution increases mortality risks from heat, especially when combined with other factors like wildfires and reduced aerosols.
A new measure called “outdoor days” describes the number of days per year that outdoor temperatures are neither too hot nor too cold for people to go about normal outdoor activities. This measure reveals significant global disparities, with the North gaining more outdoor days and the South losing them due to rising temperatures.
Researchers unveiled a theoretical model that shows specific structural details on surfaces can influence water's freezing point. The model identifies angles between microscopic bumps on a surface that make it easier for water molecules to crystallize at relatively warmer temperatures.
The study reveals that a specific MP scheme simulates storms with less rain evaporation and weaker air movements compared to others. It also found that this scheme produces more cloud ice but rains less on the ground due to its handling of icy particles.
A new method for correcting glare in plant phenotyping has been developed, using polarized light to improve accuracy and reduce complexity. The technique has been validated in field trials, showing significant improvements in image data accuracy and reduction of error and variance.
Researchers develop a novel approach using SIF and PRI to estimate GPP in rice canopies, showing significant correlations between these indexes and GPP across various timescales. The study reveals the dynamic responses of PRI/SIF to environmental conditions and demonstrates improved correlation by distinguishing between shaded and sunl...
A new study by Penn State researchers reveals that Arctic sea ice loss will deplete the source of cold air for North America, leading to less cold weather events. The loss of sea ice also changes weather patterns, allowing warmer temperatures to reach the surface.
Researchers found that land-atmosphere coupling has a significant impact on Asian monsoons, but its effect varies greatly from year to year. The study suggests that better modeling of land conditions may be crucial for improving seasonal forecasts in the region.
A study published in PLOS ONE predicts that climate change will inundate over 4,200 archaeological sites along the US state's coast, with nearly 5,000 at risk by 2100. The authors used a predictive model to account for storm surge events, highlighting the need for cultural heritage managers to take action.
A new study reveals that increased meltwater in the North Atlantic can trigger hotter and drier European summers. The study suggests a predictable chain of events leading to European summer weather, due to higher levels of freshwater in the North Atlantic.
A new study using a high-resolution global climate model found that cloud clustering causes more extreme rain in the tropics, leading to increased severity of precipitation events. The researchers also discovered that more extreme rain occurs at the cost of expansion of dry areas, further shifting towards extreme weather patterns.
A recent study published in npj Climate and Atmospheric Science reveals that changes in subtropical and midlatitude eddy activity control the variation of the Hadley cell edge latitude. The researchers analyzed 41 years of data and found associations with El Niño, La Niña, and the Arctic oscillation.
Researchers found that compact, faster-moving storms are more susceptible to global warming's effects, while larger, slower-moving typhoons are more resilient. This discovery could lead to improved methods for projecting typhoon strength under warming conditions.
A new compound flooding model predicts that New York City will experience historic and devastating floods every 30 years by the end of this century, a fivefold increase from the present climate. The tool helps city planners prepare and protect against future disasters by providing detailed flood forecasts.
Researchers at Max Planck Institute for Dynamics and Self-Organization developed a precision apparatus to observe non-spherical particles settling in air. They found that particles tend to oscillate as they settle, which could impact collision rates, travel distance, and solar radiation interaction.
A new study reveals that microplastic fibers settle substantially slower than spherical particles in the atmosphere, allowing them to reach remote regions such as Arctic glaciers. The research suggests that these fibers could even reach the stratosphere, with potential implications for cloud processes and ozone depletion.
Korea Maritime & Ocean University researchers have developed a new method for assessing the path-following performance of autonomous ships in adverse weather conditions. The computational fluid dynamics model can provide more accurate predictions of path-following performance and enhance safety in autonomous marine navigation.
A GEOMAR study found that low North Atlantic sea surface temperatures are responsible for heat events on land. The researchers discovered a link between cold ocean temperatures and European heat waves, which contributes to the formation of high pressure systems and clear skies.
Researchers from the University of Córdoba used machine learning models to predict reference evapotranspiration in Southern Spain until 2100. The projections indicate a significant increase in water needs, with air temperature being the key factor in calculating this parameter.
Researchers found that space weather events can trigger 'wrong side' failures in rail signalling systems, which are more hazardous than 'right side' failures. This study highlights the need for the industry to consider the risks of space weather and explore mitigation strategies.
Researchers found that compound energy droughts can occur nationwide, with varying frequencies and durations across regions. Understanding these droughts will help grid planners prepare for energy storage needs and inform deployment of long-duration energy storage projects.
A new study improves thunderstorm forecasting by utilizing Geostationary Operational Environmental Satellite (GOES-R) lightning flash observations. The implementation of the EnVAR assimilation capabilities successfully enhances the forecasting performance, especially over regions lacking operational weather radar observations.
Researchers develop a mathematical model that analyzes the future survival of plants in a changing climate by studying how far wind can carry seeds. The model provides fast and reliable predictions of seed movement, considering factors like seed type, plant height, and wind speed.
A new deep learning-based detection system has been developed by INU researchers to improve the detection capabilities of autonomous vehicles. The system, aided by IoT technology, generates bounding boxes and confidence scores for visible obstacles using point cloud data and RGB images as input.
A new study of 600 years of tree rings from the San Joaquin Valley reveals that climate extremes have been more severe and lasted longer than modern records, highlighting flood and drought risks in California. The research combines paleo information with synthetic weather generation to help understand and anticipate these risks.
Native Americans in Oklahoma have approximately five times increased risk of heavy rainfall, with two-year floods projected to be 632.6% higher than the general population. The study aims to help Native American leaders develop disaster risk reduction plans and protect vulnerable communities.
Researchers found that the coastline produces up to five times more giant sea salt aerosols than the open ocean, affecting cloud formation and rainfall around the Hawaiian Islands. The study's findings can improve numerical weather prediction of nearshore cloud formation and rainfall patterns.
Researchers analyzed microplastics in mountain clouds and found they can modify particles in ways that enable them to affect cloud formation. The study also found that clouds can increase the presence of toxic metals on these particles.
Researchers found that well-designed urban land patterns can moderate or even reduce population exposures to weather extremes, regardless of city size. Properly designed cities can generate a meaningful reduction in the increase in risks from climate change.
A Drexel University study projects 82 more days of water shortfalls in the Schuylkill Watershed, which could only meet demand about 67% of the time due to climate change. This would lead to drought-like conditions and require difficult tradeoffs in resource management.
A new hybrid method developed by Concordia researchers combines data from Weibull probability distribution and numerical weather prediction models to improve wind speed forecasting accuracy. This innovation has the potential to significantly enhance urban power generation, particularly in areas with high variability in wind speeds.
A new jet stream has been discovered in Jupiter's upper atmosphere by the James Webb Space Telescope, showing winds reaching speeds of up to 500 km/h. The discovery provides new insights into the atmospheric dynamics of gas giants and could shed light on global temperature variations.
The National Science Foundation has awarded $1.6 million to Emory University researchers to develop predictive models for farmers to adapt to climate change in Georgia, Iowa and Ohio. The project aims to create a public online tool to explore possible futures of agriculture at regional and state levels.
Researchers from Texas A&M University's Department of Geography and collaborating departments aim to improve understanding of how environmental hazards influence human health outcomes. The project, 'Climate-LEAD,' will create robust models using localized data to inform decision-making in vulnerable communities.
A recent study using SENTINEL-2 satellite images estimated burned areas with 96% accuracy, revealing a much larger area affected by wildfires than previously thought. This higher precision will help improve estimates of greenhouse gas emissions and inform fire management decisions.