Articles tagged with Weather Forecasting
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Researchers at Newcastle University and the UK Met Office identified a three-layered atmospheric structure associated with heavy rainfall developing within minutes. The findings help explain record-breaking rainfall and flash floods in the UAE and Oman in April 2024, and may aid future improvements in identifying risk.
A recent study has clarified the record-late monsoon onset in Australia, defining its critical impact on water security and cattle industry. The researchers found that local wind conditions over Darwin prevented the upper-level winds from switching to easterlies.
Researchers at the University of Kansas have developed a tornado-forecast system called Warn-on-Forecast System (WoFS) that can predict tornado formation up to an hour before it occurs. The system uses high-resolution simulations and gauges uncertainties, providing guidance on severe weather threats.
Research from the University of Kansas finds that cuts in sulfur emissions from oceangoing vessels have led to a reduction in lightning stroke density along heavily trafficked shipping routes in the Bay of Bengal and South China Sea. The drop in sulfates from ships can cause fewer cloud condensation nuclei, resulting in weaker convecti...
Researchers improve extreme precipitation forecast accuracy using a novel CNOP-I scheme in a convection-allowing ensemble prediction system. The new method captures nonlinear evolution characteristics of weather systems, leading to more accurate predictions and reduced uncertainty.
Researchers Min Chen and Liangchen Guo developed a new system using Fengyun-4B satellite data and regional numerical forecast model RMAPS-ST to improve ultra-short-term solar irradiance forecasting. The system achieved significant reductions in forecast errors, particularly in warm seasons and short-term forecasts.
Recent research reveals that volcanic eruptions can cause unpredictable weather patterns, including volcanic rain, dust storms, and unstable Antarctic air. The study also found that the Antarctic surface atmosphere has become less stable and more prone to gravity waves since the 1950s.
A team of researchers used innovative approaches, including public data and machine learning models, to create more accurate predictions of coastal erosion and infrastructure damage. The project aims to improve storm preparedness and timeliness.
The 106th Annual Meeting of the American Meteorological Society will focus on the intersection of technology and human decision-making in weather, water, and climate sciences. The meeting will feature keynote presentations, Presidential Sessions, and named symposia highlighting key Earth science topics.
Over half of global coastal settlements have retreated from the coast over the past 30 years in response to intensifying climate hazards. Coastal regions in Africa and Oceania lead the retreat, while poorer regions often expand shoreline settlements due to economic needs.
Researchers at the University of Utah have developed a new model to predict the snow-to-liquid ratio, which varies widely in the Western United States. By training a random forest model on high-quality data from 14 mountain sites, they were able to explain nearly half of the variability in snow density compared to existing methods.
Researchers investigate how adjacent cities exacerbate each other's heat island effects. A study also highlights the need for improved hindcasting infrastructure in climate science. Additionally, a campaign monitors pinned clouds over industrial sources of heat and finds that trees are more reliable against heat stress than buildings.
Researchers at UAlbany are exploring the use of stable water isotopes to improve weather and climate forecasts. By analyzing differences in isotope masses, scientists can track moisture movement and understand related processes.
A new study by Purdue University researchers reveals that hurricanes grow in size faster when traveling over locally warm waters, which can help improve daily forecasting of hurricane size and impacts. This discovery has the potential to better model hurricane size in long-term risk models used by industry.
The UK's new weather-health alert system has been deemed successful in supporting vulnerable groups, but minor confusion remains around its color-coded warnings. Researchers identified areas for improvement, including clearer yellow alert scales and simplified alerts for rapid use on the ground.
A new study developed a flood-forecasting AI that can be tuned for any country, reducing errors in national flood prediction programming. The hybrid model combining the AI with the National Water Model was four to six times more accurate, improving forecast accuracy and potential economic impacts of floods.
A new study predicts an increase in western US wildfires sparked by lightning strikes, with 98% of the region seeing more risk days by 2060. The western US is expected to see a significant rise in lightning days, with areas like Oregon and Idaho experiencing up to 12 more days per summer.
The Madden-Julian Oscillation's speed and intensity are influenced by atmospheric stability, which affects regional convection and tropical cyclones. Uneven ocean warming changes MJO behavior, impacting rainfall patterns and climate forecasts.
Researchers from the University of Maryland tracked lightning storms in real-time using NASA's TEMPO instrument, detecting nitrogen oxide emissions that affect climate and air quality. The study reveals how lightning can produce pollutants that travel long distances, influencing air quality far from the original storm.
A new model incorporates rainfall and storm surge, leading causes of hurricane deaths. The proposed scale aims to improve evacuation decisions by providing a more accurate picture of the storm's severity.
New research from Purdue University reveals how moisture influences atmospheric blocking, a phenomenon that often drives heat waves, droughts, cold outbreaks and floods. The study introduces a new mechanism showing that moisture-induced diabatic heating strengthens ridge blocks but weakens dipole blocks.
A new AI system developed by the University of Miami Rosenstiel School can automatically identify and track tropical easterly waves, separating them from other tropical wind patterns. The model combines historical observations with reanalysis data to produce accurate real-time forecasts.
Researchers improved WRF model precipitation simulation by optimizing Grell-Freitas cumulus scheme and Turbulent Orographic Form Drag scheme. This approach reduced overestimation of precipitation across the Tibetan Plateau.
The China Meteorological Administration has demonstrated significant improvements in both track and intensity prediction accuracy for tropical cyclones. The study finds that track forecast errors have reduced, particularly at longer lead times, while intensity forecasts have also shown advancements.
Researchers developed a 3-km resolution model that achieved unprecedented accuracy, reducing track errors to below 100 km over a 120-hour forecast period. The innovative variable mesh refinement strategy balances computational demands with accuracy while targeting key weather systems influencing typhoon motion.
Recent research from American Meteorological Society journals predicts a new record for lightning and a decrease in hurricane frequency. Additionally, fire forecasts have been updated to better manage water resources in Colorado's Gunnison River Basin.
Researchers at ETH Zurich found that mineral dust particles can trigger freezing of cloud droplets, particularly important in northern regions where clouds form below freezing temperatures. This process affects sunlight reflection and precipitation generation, with major implications for climate models.
The ERIC system combines doorbell cameras and AI to analyze rainfall estimation and automatically adjusts irrigation schedules for more precise water use. Researchers estimate users can save up to $29/month in utility costs and 9,000 gallons of water per month with the innovative irrigation system.
Tiny droplets of sea spray can affect hurricane intensity, but measuring their concentration and size is challenging. Researchers at the University of Texas at Dallas are using lab experiments and simulations to develop a machine learning model that incorporates these factors.
A new framework developed by Northwestern University and UCLA scientists integrates various water-related processes with a machine-learning model to predict landslide threats. The framework identifies three main pathways leading to landslides: intense rainfall, rain on already saturated soils, and melting snow or ice.
Researchers developed a novel deep learning-based framework that improves five-day regional weather forecasting accuracy, even with limited data. The method achieved significant improvements in temperature, precipitation, and wind speed forecasts, outperforming mainstream global AI models.
A new study published in Weather and Forecasting found that Hurricane Hunter flights can increase forecast accuracy by up to 24 percent. The researchers analyzed forecasts for all tropical cyclones in the Atlantic basin from 2018 to 2022, comparing forecasts with and without NOAA G-IV data.
A study found that declining aerosols are up to 2.5 times more influential than greenhouse gases in driving changes in heatwave occurrence in populated areas. Higher levels of aerosols suppressed heatwave exposure by reflecting the sun's rays, but this trend is now reversing due to clean air policies.
Researchers found that indirect effects of tropical cyclones contribute more than twice the direct effect to rainfall during the Habagat season, with 51.5% coming from the monsoon itself. This new understanding can improve extreme weather anticipation and disaster response.
A new study reveals how variations in the stratospheric polar vortex affect where and when extreme cold hits, with a focus on the northwestern US. The research finds two distinct patterns that steer Arctic air into different areas, leading to colder winters in regions like Montana and Texas.
The CNOP-DL method extends classical CNOP for deep learning methods, breaking deterministic causality and attributing forecast errors to all input slices. This new structure identifies critical time steps and locations where additional observations can significantly improve forecasts.
A new study predicts that a 2°C temperature rise could double the frequency of short-lived summer downpours in the Alpine region, causing severe damage and posing risks to lives. The analysis of nearly 300 mountain weather stations found that warm air retains more moisture, intensifying thunderstorm activity.
Researchers estimate that temperatures several degrees above the 2022 UK heatwave are plausible in today's climate, with a simulated maximum of over 45°C (113°F). The likelihood of 40°C will continue to rise as the climate warms.
Scientists at the Naval Research Laboratory are working with NASA to better understand pyrocumulonimbus clouds, which can inject smoke into the upper atmosphere and alter weather patterns. The Injected Smoke and Pyrocumulonimbus Experiment (INSPYRE) aims to enhance predictive weather modeling through detailed analysis of wildfire-induc...
The American Meteorological Society has awarded its 1,000th CBM designation to Ryan Marando, a meteorologist at WHIO-TV in Dayton, OH. This milestone recognizes the expertise of on-air weather communicators in both meteorological science and forecasting.
The Florida Atlantic University Sensing Institute's SEA Econet network provides accurate rainfall and flood forecasting, supporting public safety during severe weather events. With over 160 atmospheric stations and more than 30 water-level stations across Florida, the network delivers real-time data to inform forecasts and warnings.
A team of researchers developed a machine learning model called Aurora that accurately forecasts various Earth systems, including air quality and tropical cyclone tracks. The model outperforms traditional systems at a fraction of the cost, enabling better preparedness for extreme weather events.
A new study projects that wind losses for homeowners in the Southeast will increase by 76% by 2060 and 102% by 2100. Texas is expected to experience the highest increase in losses, followed by Louisiana, Mississippi, and Alabama.
Researchers have discovered that urban areas experience a greater difference in wet bulb globe temperature between 0.5 m and 1.5 m above ground due to surface heat radiation, posing health risks to children and pets during extreme heat events. Total solar eclipses also alter atmospheric conditions and insect behavior, with some species...
A new study reveals that the Pacific Meridional Mode plays a major role in Hawaiian rainfall variability, particularly in spring. The research suggests that El Niño emerges as the primary driver of winter rainfall, but the PMM is crucial for spring rainfall, especially on Maui and the Island of Hawai‘i.
A new study reveals the atmosphere can store moisture over extended periods, creating a physical memory effect. This 'memory' allows monsoon systems to flip between two stable states, with severe consequences for regions relying on monsoon rainfall.
A 19-year study finds that 20,000 people died from heatstroke and 15,000 from cold exposure in India between 2001 and 2019. The study identifies working-age men as most vulnerable to heat-related deaths, highlighting the need for measures such as shaded parking areas and relief provisions.
Researchers develop mathematical modeling to predict aflatoxin outbreaks in Texas using remote sensing satellites and soil properties. The model has the potential to save farmers billions of dollars in losses by providing early risk prediction and targeted prevention strategies.
The American Meteorological Society warns that catastrophic cuts to federal science agencies like NOAA threaten the US weather enterprise, which supports public safety, private sector operations, and national security. A strong weather enterprise is essential for America's economic leadership.
Researchers used satellite data to analyze the impact of dust on snowmelt in the Colorado River Basin. The study found that dust-driven melting tends to peak earliest and be most intense in central-southern Rocky Mountains, accelerating spring melt rates by up to 1 mm water-equivalent per hour.
The US Naval Research Laboratory showcased its latest advancements in defense technology, including the OmniGlobe, a large spherical display visualizing Earth's environmental data. NRL's PROTEUS tool provides near real-time global tracking and analysis of maritime vessels.
A team of climate scientists found that six major oceanic modes influence prolonged heavy rainfall in China, which can lead to severe flooding. Winter sea temperatures in the tropical Pacific can predict summer flood potential with 75% accuracy.
Researchers have developed a new forecasting tool called iDust that offers significant benefits for solar energy production by predicting dust storms with higher accuracy. The system provides critical support for China's expanding solar energy projects in desert regions, minimizing disruptions and financial losses.
A team of scientists analyzed chemical signatures in hailstones to determine their growth histories, finding most hailstones follow simple trajectories rather than the previously assumed recycling motion. The study identified key thresholds for hail growth and suggests that strong updrafts are essential for severe hailstorms.
Recent research highlights increased fire activity in the western US, with wildfires becoming less prone to calming down at night. Meanwhile, extreme turbulence on hurricane flights has led to a new 'bumpiness' metric. Climate extremes are also evident in shifting energy demands for heating and cooling in Chinese megacities.
A new study by the UK Centre for Ecology & Hydrology reveals that soil moisture levels can increase rainfall area and amount in megastorm hotspots globally by up to 30%. This contrast results from atmospheric changes, enabling communities to better adapt to climate change.
The Albert Einstein Jewish Brazilian Hospital launches a project to evaluate the application of quantum computing in developing new drugs and improving disease diagnosis. Researchers aim to use machine learning and quantum optimization algorithms to analyze rainfall data and predict heavy rainfall events.
Researchers evaluate traditional precipitation phase partitioning methods and machine learning models, revealing near-freezing temperatures create inherent limitations in distinguishing between rain and snow. Accurate identification is critical for weather forecasting, hydrologic modeling, and climate research.
A recent study assesses the forecasting skill of subseasonal ensemble models for extreme cold events in East Asia, revealing that some ensemble members exhibit significantly high forecasting skill. These high-skill members can accurately predict rapid changes in surface air temperature and minimum temperature during an event.
Aardvark Weather, a fully AI-driven system, delivers accurate forecasts tens of times faster and using thousands of times less computing power than current systems. The new approach transforms weather forecasting, providing bespoke forecasts for specific industries or locations.