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.
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.
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 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.
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.
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.
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.
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.
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 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.
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 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.