Researchers developed a new model to predict storm damage, allowing for effective resource allocation and reduction in societal consequences. The framework can be applied to various infrastructure systems and weather events, promoting better preparedness and response.
A review of over 500 studies on urban climate and weather reveals significant gaps in current understanding and modeling. The researchers emphasize the need for better observation-model integration, improved communication between scientists and end users, and standardized meteorological stations.
Scientists use a modified drone with a radiation shield to collect high-quality atmospheric data in polar regions. The study shows that the low-cost drone provides accurate data comparable to radiosondes, expanding the observational network and improving weather forecasts.
A German study finds that ambulance call-outs for heart attacks increase when air pollution is high, but decrease with warmer weather. The research highlights the need for better planning and resource allocation by hospitals to address climate change-related changes in weather conditions.
Residents in eastern US cities experience up to 4.9 degrees Celsius increase in nighttime urban heat stress index, with extra 30 minutes of uncomfortable weather per degree C temperature increase. This effect is more pronounced in the southeastern US, where residents face up to five extra hours of uncomfortable weather during summer.
Persistent weather conditions are becoming more common in European summer, leading to prolonged heat waves and intense rainfall events. This trend is linked to increased hydro-climatic risks, especially for densely populated regions.
A new study found that extreme fire weather is being driven by a decrease in atmospheric humidity coupled with rising temperatures. This trend is linked to an increase in naturally occurring extreme fire events, spreading to new areas and burning more intensely than ever before.
NJIT's Institute for Space Weather Sciences will host a Research Experiences for Undergraduates program, providing students with hands-on work at advanced observatories. The 10-week program aims to foster the development of future workforce in solar-terrestrial and space weather sciences.
Environmental engineers at Duke University demonstrated that sharp contrasts in small landscape features refine local weather developments and influence climate trends. The study suggests that incorporating detailed data can improve forecast accuracy.
New research from the University of Arizona suggests that a slowdown in the Atlantic Meridional Overturning Circulation (AMOC) will intensify extreme cold weather in the US. The study found that without the AMOC, extremely cold winter weather would become more frequent and severe.
Researchers at York University have discovered a conveyer-like motion of heat across the equator in the Pacific Ocean called the Cross Equatorial Cell (CEC), which influences El Niño and La Niña. This finding may lead to improved prediction of year-to-year disruptions to weather patterns, benefiting countries worldwide.
A study published in PAIN found that weather-related factors can affect pain tolerance, particularly for cold-induced pain. Temperature, barometric pressure, and humidity were associated with changes in pain tolerance tests, suggesting a dynamic and non-linear relationship between weather and pain.
A new study incorporated water vapor isotope compositions into a general circulation model to improve forecast accuracy by several percentage points. The Isotope-incorporated Global Spectral Model (IsoGSM) demonstrated improved modeling of air temperature and specific humidity.
A new study finds that rapid Arctic warming is driving extreme winter weather in the US, particularly intense snowfall events and anomalous cold snaps. The findings reveal a physical link between Arctic amplification and stratospheric polar vortex disruption, which are contributing to increased frequency of winter weather extremes.
A new study shows that polar vortex disruptions most favorable for extreme US winter weather are increasing, with Arctic change likely contributing to the trend. The analysis demonstrates that a 'stretched' polar vortex state is more common and leads to severe winter weather.
A study published by Sandia National Laboratories reveals that older solar farms are more susceptible to extreme weather events, while snowstorms have the highest impact on electricity production. Machine learning analysis also found that low sunlight levels due to cloud cover and geographical features of the farm are significant factors.
The World Climate Research Programme has made efforts to improve climate prediction, but many problems remain, including predicting extreme weather events. The Center for Climate System Prediction Research (CCSP) aims to tackle these challenges through research on ENSO, extended-range weather forecasting, and interannual-to-decadal cli...
Analysis shows US workers in weather-exposed industries work fewer hours on hot days during economic growth, but not during recession. The study predicts $80 billion in lost wages by 2090 due to high-heat labor conditions.
A Purdue University study suggests that the eastern half of the US is a hotspot for severe thunderstorms due to high terrain, while the Gulf of Mexico plays a relatively weak role. Removing the Gulf would shift storm patterns eastward into Illinois and reduce them over southern Texas.
Researchers created a new sun clock to study the solar seasons. The study reveals that the switch from solar maximum to declining phase is fast, occurring within a few solar rotations. This discovery helps predict space weather events, such as violent activity on our Sun leading to extreme events on Earth.
Researchers are working to improve space weather forecasting to prevent power grid damage and satellite communications disruptions. The University of Michigan's Space Weather Modeling Framework uses a global representation of Earth's Geospace environment to predict magnetic disturbances on the ground.
Naoko Sakaeda, a University of Oklahoma weather researcher, has received a $652,000 NSF CAREER award to study tropical meteorology and improve global weather forecasting. Her research aims to better understand the dynamics of tropical clouds and precipitation at various scales.
Scientists from Incheon National University identified interzonal airflow across household entrance doors as a dominant factor in calculating heating loads. They found that strong stack effect and weather-driven airflow rates were larger than external infiltration rates, making conventional airtightness measures unreliable.
Researchers found that high-impact weather events can be extreme, especially in context of human activities. Detailed hypothermia risk forecasts were not available for the race site, contributing to tragedy. The study highlights the need for improved warning systems and collaborations among scientists, governments, social media, and ci...
Researchers developed an AI method called CU-net to improve weather forecast accuracy by learning from uncertainty. The model corrected four weather variables and showed improved performance using 10-year data, promising innovative diagnostics for climate variability.
A University of Oklahoma researcher is using fluid dynamics principles to improve climate modeling, with a focus on turbulent transport in the lower atmosphere. The project aims to enhance predictability and accuracy in weather and climate patterns.
Scientists use infrared sensors to study the nighttime weather of Venus, discovering that north-south winds run in the opposite direction at night. This observation could help build more accurate models of the Venusian weather system and provide insights into Earth's weather patterns.
A University of Illinois study finds that US corn and soybean varieties have become more resilient to extreme heat and drought but less adapted to normal weather patterns, leading to reduced productivity. The researchers call for crop breeders to focus on developing crop varieties for diverse weather patterns.
Researchers developed a new method to quantify cyclones' influence on atmospheric circulation, improving climate projection accuracy. This approach allows for finer details to be revealed in patterns of cyclones and anticyclones.
The use of additional Metop-C and Fengyun-3 C/D data has been shown to improve regional weather forecasts by filling existing data gaps. By incorporating more PMW satellite radiances, scientists can enhance the quality of forecast models, leading to better short-range predictions.
Researchers found a clear relationship between temperature and aggressive incidents, with hotter weather linked to higher rates of incidents. There were on average 15% more aggressive incidents on days over 30°C compared to cooler days.
Researchers at Shinshu University and the National Polar Research Institute found a Forbush decrease in cosmic ray counts during a CME event, but the CR density exceeded its original level before exiting the Magnetic Flux Rope. The high-speed solar wind caused this unusual enhancement of CR density through local compression of the MFR.
Researchers developed new software for improved space weather prediction, leveraging supercomputers and advanced computing techniques to analyze magnetized solar wind plasma. This effort aims to enhance the accuracy of predictions for coronal mass ejections and their impact on Earth's magnetosphere.
A space physicist from UTA is collaborating with an international team to study the impact of coronal mass ejections on earth's magnetic field and technological systems. The research aims to improve forecasting and mitigation capabilities for solar flares, which can cause widespread blackouts.
Researchers will use accurate weather forecasts to anticipate food shortages, poaching, and other threats to elephants, allowing conservation groups to take action weeks or months in advance. The project aims to reduce human-elephant conflict and help at-risk species withstand climate change.
Scientists have discovered a clear pattern in extreme space weather events, making it possible to predict when they will occur. The findings suggest that Moon missions may be delayed to avoid the most intense periods of solar activity, which can pose risks to astronauts and satellites.
Researchers developed a machine learning model that accurately predicted cardiac arrest risk by combining timing and weather data. The results showed that Sundays, Mondays, public holidays, winter, and low temperatures were associated with higher risks of cardiac arrest.
A new study reveals that many UK farmers are not prioritizing adapting to the effects of climate change due to uncertainty and focus on short-term profitability. However, innovative practices such as improving soil health and adopting risk-spreading strategies can help build resilience within farming businesses.
Scientists create new approach to measure error components, finding more than half of total error variance attributed to misplacement of weather features. The study also reveals that displacement errors dominate structural inaccuracies in forecast fields.
Researchers found that El Niño can accurately predict cacao yields with a high degree of confidence, even 25 months before the harvest. This innovative approach uses machine learning and rigorous data collection to provide valuable insights for farmers and policymakers, enabling them to make informed investment decisions.
Researchers discovered human activities releasing CO2 and pollutants impact North Atlantic weather patterns. The study predicts up to a decade-long warning for changes in weather and climate.
A new study from the University of Illinois finds that US interstate trade can reduce the economic impact of climate change on crop profit, with potential benefits worth up to $14.5 billion by 2050. This approach shifts the paradigm compared to current forecasts, which only consider local drought impacts.
Researchers used weather radar to create a forecasting system for nocturnal bird migration in the US, finding that just 10 nights of action can reduce risk by 50% for avian migrants passing over an area. This data enables more 'mindful' approaches to protect migrating birds from threats like light pollution and collisions with structures.
A preliminary study found that people with multiple sclerosis (MS) are at a higher risk of experiencing worsening symptoms during periods of anomalously warm weather. The study estimated an excess of over 2,900 medical visits related to MS due to rising temperatures.
Researchers at Cornell University are developing a hyperlocal weather forecasting system to improve winter-storm emergency response in rural New York communities. The system, led by professor Max Zhang, will integrate computer vision, numerical weather forecasting, and Internet of Things-based sensing packages.
Researchers developed a framework to better predict extreme rainfall events in Mediterranean countries by analyzing weather data from 1979 to today. The study found strong relations between nine distinct atmospheric patterns and the location of extreme weather events.
A new study published in Frontiers in Earth Science uses citizen science data to identify the temperature cutoff between rain and snow in winter storms in the Lake Tahoe region of the Sierra Nevada. The results show that a warmer temperature threshold of 39.5°F may be more accurate for predicting precipitation in this region.
A study found that variable weather conditions make pre-emergence herbicides less effective, leading to increased use of post-emergence herbicides. Herbicide combinations can help minimize rainfall requirements and improve weed control.
A team of climatologists from Universitat Rovira i Virgili, the State Meteorology Agency, and the University of Bonn have developed homogenization methods to correct spurious trends in temperature measurements. These methods, tested on a large dataset of 1,900 weather stations, improved the accuracy of climate trend estimation.
Researchers found that cloudy weather leads to lower investments in risky equity crowdfunding campaigns, with novice investors reacting more strongly. To mitigate this effect, entrepreneurs can target experienced investors or increase marketing efforts on cloudy days.
Climate scientists have long known that human activities increase wildfire risk, but the specific roles and influences were unclear. A new study quantifies competing anthropogenic influences on extreme fire weather risk, revealing heat-trapping greenhouse gas emissions as a dominant contributor.
A new study has found that COVID-19 lockdowns led to smaller-than-expected reductions in NO2 emissions and increased ozone levels in cities worldwide. Concentrations of fine particles (PM2.5) decreased in most cities except London and Paris.
Researchers identified a severe drought period in 1302-07 Europe, which shares similarities with the 2018 weather anomaly and recent climate trends. The study suggests that transitional phases in the climate are characterized by stable weather patterns, contributing to extreme events like the Great Famine of 1315-21.
A new AI model has shown promise in generating faster and more accurate weather forecasts by analyzing past weather patterns. The model uses about 7,000 times less computing power than traditional forecasting models while still simulating a year's weather around the globe.
A new study by GIST researchers reveals a consistent link between synoptic weather patterns and surface ozone concentrations in South Korea. The research suggests that increasingly frequent dry tropical spells are contributing to the degradation of air quality, with potential health consequences.
A new radar system developed by UC San Diego engineers can accurately predict object shapes and sizes in various weather conditions. The two-sensor setup improves imaging quality compared to traditional single-radar systems.
A new device created by researchers at the University of Texas at Austin can overcome challenges like bad weather to deliver more secure, reliable communications. The chip operates in mid infrared light spectrum, allowing signal to penetrate through clouds, rain and other weather conditions without significant loss.
A 3D-printed weather station was found to be accurate and viable for shorter campaigns, according to researchers. The low-cost sensors measured temperature, pressure, rain, UV, and relative humidity with accuracy comparable to commercial-grade stations.
A new study by UT Austin found that temperature and humidity have no significant role in coronavirus transmission, while human behavior plays a major role. Travel habits and urban density are among the top contributing factors to COVID-19 growth.
The University of Miami is collaborating with Brazilian researchers to share large-scale datasets in real time, improving weather and climate models. This collaboration will test the high-speed FABRIC infrastructure's ability to support fast data exchange.