Researchers at the University of Leeds and the Met Office have developed a predictive tool to identify regions at increased risk of tornadoes on UK cold fronts. The tool uses wind fields ahead and behind the cold front to compute a percentage probability that tornadoes will occur.
Researchers argue that current approaches to attributing extreme weather events to global warming focus too much on raising the threshold for false alarms, neglecting the importance of accurate warnings. By prioritizing probability of detection, climate scientists can strike a better balance between caution and timely warning.
Researchers aim to improve weather and climate prediction by modeling atmospheric gravity waves using Loon LLC's internet-connected balloon data. The project will help scientists better understand the impact of these wave phenomena on jet streams, polar vortex, and extreme weather.
A large retrospective study suggests that the amount of carbon stored in soils is the biggest predictor of how much carbon will combust during a fire. The study found that soil moisture was also significant in predicting carbon release, and that vegetation patterns were complex and interacted with each other to predict combustion amounts.
Birds breeding earlier due to climate change face increased risk of mortality, as chicks hatch into unpredictable weather conditions. This study examines the impact on Tree Swallows, finding that advancing breeding dates result in reduced availability of food resources, exacerbating the effects of climate change.
A Rutgers study suggests that 5G wireless networks may impact the accuracy of weather forecasts. The study found that even low levels of 5G radiation can affect precipitation and temperature predictions by up to 0.9 millimeters and 2.34 degrees Fahrenheit, respectively.
UMass Lowell researchers are studying the relationship between heat waves and droughts in the Northeast, using moisture-tracking techniques and computer-aided modeling. The team hopes to better understand how well they can predict these extreme weather events and their potential impact on climate change.
A new study by University of Utah researchers found a correlation between media coverage of weather and air quality, and transit ridership. The study suggests that favorable weather conditions and comfort are associated with increased ridership, while poor air quality may discourage usage.
A new study from Oregon State University found that natural disasters alone are not enough to motivate local communities to engage in climate change mitigation or adaptation. Policy change appears to depend on a combination of factors, including fatalities, media coverage, and community politics.
The study evaluates the performance of FY-3D's instruments, showing improved data quality and reduced forecast errors by 0.1% on average. The assimilation of FY-3D microwave observations enhances global weather forecasting, climate prediction, and resilience to extreme weather events.
Georgetown researchers caution that weather does not significantly impact COVID-19 transmission and that lockdowns and re-openings have a stronger influence. The authors suggest that policy should not be tailored to current understandings of the COVID-climate link.
The University of Oklahoma is leading a $100 million NSF AI Institute to advance trustworthy AI in weather, climate, and coastal oceanography. Researchers will develop accurate predictions and improve societal resilience to climate change.
A study of 109 bird species across eastern North America over a 15-year period found that some birds are more resilient to climate change than others. The research, published in Global Change Biology, suggests that conservation efforts should target vulnerable species and locations predicted to experience extreme weather events.
A new study found that cold temperatures are responsible for 94% of temperature-related deaths, even though hypothermia affects only 27% of hospital visits. This highlights the need for improved awareness and education around cold injury risks, particularly among vulnerable populations.
Scientists used an 'ocean-in-a-lab' to show that air pollution can change the makeup of gases and aerosols released by sea spray, influencing atmospheric composition and weather. The study found that adding pollutants like hydroxyl radicals transformed microbe-produced gases into new compounds.
A new method was developed to study fast Coronal Mass Ejections and predict the most extreme space weather events. These events can cause strong geomagnetic storms that affect space and Earth-based engineering systems.
Scientists have made a major breakthrough in predicting North Atlantic pressure patterns, which drive European and eastern North American winter weather. The study suggests that decadal variations in atmospheric pressure are highly predictable, enabling advanced warnings of extreme weather events.
Using a weather-based decision support system can significantly improve Cercospora leaf spot control in table beet by reducing unnecessary fungicide applications. The approach also helps minimize the risk of resistance development due to single-site modes of action.
The COVID-19 pandemic led to a significant reduction in commercial flights, causing less accurate weather forecasts worldwide. Weather forecasts are crucial for daily life, impacting agriculture and the energy sector.
A recent study suggests that long-distance migratory birds are not declining due to an inability to advance their spring migration timing in response to climate change. Instead, improvements in wind conditions and land-use changes play a major role in shaping bird population sizes.
A new £20M research program will enhance UK's space weather monitoring capability, enabling faster and more accurate predictions of solar superstorms and severe space weather events. The University of Birmingham leads the effort, developing data modeling technology to underpin the work.
Researchers used a statistical method to remove weather influences from air pollution data in Saxony, finding that traffic density is the most important factor. Adjusted for weather, NOx concentrations decreased by an average of 10 micrograms per cubic meter between 2015 and 2018.
Researchers have created a new 'sun clock' using 200 years of sunspot observations to map solar activity over 18 solar cycles. The analysis reveals sharp transitions between quiet and active periods in solar activity, allowing scientists to estimate the risk of future solar superstorms.
Researchers improve forecasting of strong convective weather using analogy method, which estimates occurrence environment for similar weather phenomena based on historical model forecasts. The method performs well in predicting potential for strong convection in different regions of China.
Dione will collect energy input and ionospheric-thermospheric data, providing insights into atmospheric drag and improving space weather forecasts. The mission complements the Geospace Dynamics Constellation and marks a new era for CubeSats in gathering similar data.
Researchers found that UAV sounding data can improve Antarctic weather forecasting, especially for temperature, wind speed, and humidity predictions. The limited flight altitude of UAVs restricts the improvement to the atmospheric boundary layer.
New research suggests that the Arctic may impact Eurasian extreme weather events as quickly as two to three weeks, highlighting the need for more robust analysis techniques. The study aims to improve forecast accuracy by targeting specific observations and developing simulation experiments.
An international team of scientists has proposed a method to design climate-resilient energy systems. The study found that urban areas are expected to hold more than two-thirds of the world's population by 2050, and distributed energy systems will play a vital role in climate change adaptation and mitigation.
The article discusses recent findings from WAMC workshops and YOPP meetings, focusing on Antarctic observations, numerical modeling, and weather forecasting. Open access to datasets and improved predictive skills are major aspirations for the Polar Prediction Project.
A new Stanford study found that historical observations can lead to significant underestimates of extreme weather events by about half, particularly heat waves and heavy rainfall in Europe, East Asia, and the U.S. Climate models were more accurate in predicting future occurrence of record-setting events.
Researchers analyzed giant clam shell biogeochemical records from the South China Sea and found pulsed changes matched extreme weather events. The study suggests Tridacna shells could be used to record paleoweather patterns.
Researchers found that consumers mentally visualize using products associated with sunny and snowy conditions, leading to higher product valuation. This effect only works for products related to being outside, such as beach towels or winter gear.
A new method predicts how extreme climate events affect energy systems with a focus on renewable energy sources. Future climate events can have a considerable impact, leading to power supply reliability reductions of up to 16%. Collaboration between energy system experts and climate researchers is necessary for optimization.
The top ten list reveals Hurricane Harvey as the most extreme event, followed by Hurricane Sandy and deadly Hurricane Maria. The cost of all ten events totalled over $400bn, with devastating consequences including widespread flooding and injuries.
A new international advisory system is working to keep aircraft crew and passengers safe from space weather impacts. The system predicts disruptions from solar activity and helps airlines adjust flight paths to minimize impacts on navigation and communications systems.
A new study from UC Davis warns that extreme weather risk is too often ignored in financial markets, putting investors at risk of severe losses. The research highlights the need for better climate risk assessment and pricing to mitigate potential economic consequences.
A new study proposes a methodology for identifying effective hedging strategies based on weather derivatives to protect ski tourism operators' profits despite climate change. The research uses historical snowfall and temperature data to design useful weather derivatives payoff contracts.
Rice University engineers developed a deep learning system that uses capsule neural networks to predict extreme weather events, such as heat waves and winter storms, with high accuracy. The system achieves 85% accuracy in five-day forecasts by identifying patterns in pressure systems and regional areas.
A WVU engineer is developing a new model to improve understanding of energy transfer between the sun's solar wind and Earth's magnetosphere. The goal is to create more accurate space weather forecasts to prevent devastating effects on power grids and technology.
A recent study found that a reduction in air pollution in Europe has led to fewer extremely cold days, as the decrease in aerosol particles caused changes in the wintertime Northern Hemisphere polar jet stream. This suggests that aerosols have a stronger impact on extreme winter weather than greenhouse gases at regional scales.
Researchers found that rapid weather variability, common in warming climates, can kick-start the flu season and lead to densely populated areas experiencing high contagion rates. The study suggests incorporating environmental factors into flu spread models may improve predictions of future epidemic severity.
J. Marshall Shepherd, a renowned meteorologist, has been awarded the 2020 Mani L. Bhaumik Award for Public Engagement with Science. He is recognized for his exceptional ability to communicate complex scientific concepts to broad audiences through various media platforms.
A new study reveals that tropical forests and coral reefs are being threatened by a combination of ongoing climate changes, increasingly extreme weather, and damaging local human activities. The research highlights the urgent need for international action to decrease CO2 emissions and reverse this trend.
Researchers at Oak Ridge National Laboratory developed a computer simulation to compare energy use on similar weather days, helping utility companies and homeowners determine potential energy cost savings. The team also created a geothermal energy storage system that reduces peak electricity demand up to 37% in homes while balancing gr...
A group of scientists has conducted a new analysis that concludes the 'weather-is-not-climate' paradigm is no longer applicable. They found that daily weather data can reveal long-term warming trends, provided global spatial patterns are considered.
A study found that tropical conditions, rather than the Arctic stratosphere, influence three out of four main winter weather patterns in North America. This discovery provides forecasters with an additional tool to predict high-impact weather during winter.
Research finds that community reactions to extreme weather depend on political leanings and resources before the event. Discussion about climate change is more likely in Democratic-leaning communities or those with highly educated residents.
A UM-led experiment has shown promise in improving subseasonal weather forecasting, providing critical lead time for natural hazards like heat waves and polar vortex. The SubX project aims to provide better subseasonal forecasts to the National Weather Service, using complex computer models and large data infrastructure.
A new machine learning tool can analyze massive amounts of satellite data to detect significant features for space weather. The algorithm identifies patterns that humans may miss, enabling faster and more accurate forecasts.
The world's first 'Fisheries Index Insurance' scheme aims to protect Caribbean fishing communities from extreme weather events. However, policymakers must complement climate risk insurance with adaptations actions in coastal ecosystems to ensure its effectiveness.
Research by McGill University scientists found that nanosized metal particles from the Athabasca oil sands accelerate ice nucleation, leading to more frequent and intense extreme weather events. The pollution is also significantly higher near the oil sands than in a Canadian city.
Researchers at Argonne National Laboratory have developed domain-aware neural networks to replace expensive parameterizations in the Weather Research and Forecasting (WRF) model. These algorithms can predict environmental data more accurately with significantly less training data, enabling faster and higher-resolution simulations.
NASA's Global Precipitation Measurement mission captured heavy rainfall exceeding 1.6 inches per hour in Tropical Storm Fengshen. The storm is forecast to intensify through Friday and pass just north of Agrihan, with maximum sustained winds reaching 40 mph.
Researchers at Penn State combined geostationary satellites and traditional weather radar to create a system that produces the best forecasts for severe thunderstorms. The study found that assimilating satellite and radar data simultaneously leads to the most accurate predictions, with warning times increased by up to 40 minutes.
A record number of bushfires are raging on Australia's east coast, spanning across New South Wales and Queensland. The fires, fueled by hot and dry weather, have burned over 365,000 hectares, with temperatures expected to remain high for the next week.
A new warning system, WASAVIES, can estimate radiation doses due to solar energetic particles (SEP) up to 100 km above the ground in real-time. This system enables aircrew radiation dose monitoring and provides information for aviation operation management.
A new study finds that conservatives who report personal harm from extreme weather events, such as wildfires or floods, are more likely to support climate change mitigation policies. The study surveyed over 1,600 residents in communities affected by extreme weather events and found a significant link between reported harm and support f...
Typhoon Bualoi continues to move through the Northwestern Pacific Ocean, experiencing heavy rain around its eye, falling at a rate of over 50 mm/hour. Forecasters incorporate the rainfall data into their forecasts for updated hurricane weather information.
Researchers developed a more efficient statistical model to analyze extreme weather events globally, identifying regions with high precipitation levels and predicting their frequency. The model can handle vast amounts of data from multiple locations, providing valuable insights for disaster planning.
A Japanese research team found that incorporating radiosonde data from Antarctica improves forecasting accuracy for severe cyclones. The study successfully predicted the central pressure, wind speed, and moisture transport of an extreme cyclonic event 2.5 days in advance.