Articles tagged with Weather Forecasting
Researchers built a two-stage warning system predicting solar flares within 48 hours via k-means clustering and neural networks. The model improved recall while increasing precision, but lost some positive sample information, affecting prediction accuracy.
A study found that winter storms in north-west India are 31% more frequent and 45% more intense during positive NAO phases, leading to increased moisture and precipitation in the western Himalayas. This could impact crop yields and water security in states like Jammu and Kashmir.
A new study revisits a deadly 2021 ultramarathon event in China, highlighting the need for ultra-high-resolution forecasts in mountainous terrain. The model accurately recreated the storm conditions and offered greater insight into what may have happened that day.
Researchers from Aarhus University are developing a new approach to turbulence modelling using physics-constrained machine learning to accurately simulate complex turbulent systems. The goal is to reduce computational costs while maintaining accuracy, enabling more efficient designs and predictions in various fields.
A survey of Texas coaches and athletic officials revealed that many are aware of the risks of outdoor workouts during extreme heat, but some don
A recent study found that greenhouse gases are the primary reason for increased temperatures and will likely continue to be the main contributing factor. Simulations show that extreme heatwave events will increase by over 30 percentage points in coming years, primarily due to human-caused emissions.
A study by Brazilian, Chinese, Australian, and German researchers found that North Atlantic temperature can predict reduced rainfall and intense droughts in the Northeast region of Brazil. The findings suggest a more persistent influence of the North Atlantic than previously thought.
Researchers evaluated the prediction of a record-breaking heatwave in the Pacific Northwest, finding that forecasts were able to accurately predict the event. The study highlights the importance of trust, preparedness, and early action when extreme weather is forecasted.
A study predicts UK wine production will increase due to climate change, with areas in England and Wales becoming suitable for sparkling wine grape varieties. The research highlights the potential for high-quality still wine production, particularly for Pinot Noir and other disease-resistant varieties.
Researchers found a correlation between Arctic ozone depletion and extreme weather events in the Northern Hemisphere. Simulations suggest that reduced ozone levels contribute to warmer temperatures and droughts in central Europe, while wet conditions prevail in polar regions.
Researchers analyzed the Hunga Tonga-Hunga Ha'apai volcano's eruption to understand its effects on atmospheric waves. The blast provided an unprecedented view of atmospheric waves, allowing scientists to better predict the weather and climate.
Researchers created a dataset quantifying trends of evaporative water loss from 1.4 million global lakes and artificial reservoirs, revealing a 15.4% increase in long-term lake evaporation volume. This finding highlights the importance of accurate information for water management decision-makers in addressing climate change impacts.
A new study reveals that Nor'easters produce flood levels just as severe as hurricanes, but occur much more frequently in the Mid-Atlantic region. The intense storms can cause significant damage and disruption along the coastline, with some events surpassing those from tropical cyclones.
A recent study by Colorado State University economists and NOAA found that improved wind forecasts result in significant energy savings for consumers. The research shows a net gain of over $150 million in annual savings through better predictions of wind patterns.
Researchers developed a method to predict Western wildfire severity based on winter and spring climate conditions. The study found that April snowpack has a persistent influence on land and atmosphere during the summer, making it more conducive for fires.
Researchers used TACC supercomputers to evaluate latest severe weather forecast tools, testing their performance in real-world settings. The goal was to improve snowfall forecasts and determine optimal model combinations to predict various winter weather aspects.
Scientists identified three atmospheric phenomena orientations near the equator that increase US severe weather event probabilities three to four weeks later. Using machine learning, they found correlations between MJO fluctuations and U.S. severe weather weeks after the event.
Researchers found that improved wind forecasts resulted in at least $384 million in energy savings for US consumers over the last decade. The study used NOAA's HRRR model to compare forecast accuracy and quantify cost savings.
The world's ocean is losing its year-to-year memory due to global warming, making it harder to predict ocean conditions. This decline in ocean memory will have significant impacts on fisheries management, population estimates, and land-based weather forecasts.
A new study provides a framework for predicting snowpack runoff and its impact on flood risk during rain-on-snow events. By leveraging hourly data from existing snow monitoring stations, researchers have created a decision support tool that can help water managers prepare for potential flooding.
A new online portal developed by UKCEH enables forecasters to provide communities with more reliable warnings about large storms in the Sahel region. The portal uses state-of-the-art weather forecast models to predict storm behavior, taking into account factors such as land surface temperatures, soil moisture, and atmospheric humidity.
Scientists developed a method to estimate summer rainfall in the Southwest months in advance, performing well in Arizona. By analyzing lower atmosphere moisture, they created monthly forecasts to aid reservoir storage and water allocation decisions.
A team of scientists has developed a solution to accurately simulate how the atmosphere works by linking large- and small-scale simulations. This helps model winds, transport of pollutants, climate projections, and weather forecasts with greater accuracy.
A severe rainstorm over Kauai in April 2018 resulted in $180 million in damage and 532 homes destroyed. The study found that supercell thunderstorms triggered the deluge, which set a new US 24-hour rainfall record of nearly 50 inches.
Researchers used vertical sounding data to improve forecasting of Zonda windstorms, a severe weather phenomenon affecting Argentina's agricultural communities. By analyzing atmospheric profiles and applying principal component analysis, they achieved reliable forecasts with up to 24 hours of lead time.
Tel Aviv University researchers develop innovative model that explains wave formation, tested in complex experiments. The model takes into account all unstable harmonics and limitations of previous models, providing high reliability for describing physical situation.
A $150,000 grant from the NV Energy Foundation will support DRI's development of a Weather and Research Forecast model to simulate weather, fire, and smoke for firefighting operations. The tool will provide critical air quality forecasts and risk assessment for specific locations.
Researchers at Mainz University created artificial hailstones using a 3D printer to study their behavior in a vertical wind tunnel. The experiments revealed that the form of hailstones determines their velocity before impact, which can affect the severity of precipitation events.
A new machine learning study analyzed 10 years of weather data to identify three major categories of weather patterns and their effects on thunderstorms. The study aims to isolate the impact of aerosols, tiny particles suspended in the atmosphere, on storm severity.
The Texas cold snap highlighted the critical role of electricity in society and the need for improved power system planning to withstand extreme weather events. The event showed that traditional planning based on historical weather patterns is not sufficient, and new information from climate projection models is needed.
The Bureau of Reclamation released a new report evaluating current and emerging snow measurement technologies to enhance water supply forecasting. The report identifies under-utilized emerging technologies with potential to improve forecast accuracy in the near term.
A new study questions a widely-held theory that sudden stratospheric warming caused the extreme cold weather in Texas and other parts of the US. The research suggests that the polar vortex's disruption, which occurred six weeks after the initial warming event, was not significant enough to impact the weather.
Researchers assess predictive skills of ocean heat content in two state-of-the-art seasonal forecasting systems, finding potential to predict sub-surface warming up to two seasons in advance. This could aid mitigation of extreme events and provide early warnings for industries such as aquaculture and fishing.
A $763,930 NSF CAREER Award is supporting OU meteorologist Scott Salesky's project to improve cloud representation in weather and climate models. The research aims to better understand interactions between turbulence and clouds, with potential applications for predicting precipitation and understanding Earth's climate.
A new study reveals a significant shift in the Northern Hemisphere jet stream position, increasing by up to 330 km and speed by 8% during 1871-2011. This shift is linked to warming Arctic winters and decreased temperature gradients, with implications for climate predictions and storm activity.
A new project aims to determine the role of sea ice fragmentation in accelerating Arctic ice-cap retreat. By combining observations, theory, and process modeling, researchers hope to improve climate model accuracy.
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.
The NUIST-CFS1.0 model has positive skill in seasonal precipitation forecasts across Ethiopia, Kenya, Uganda, and Tanzania, with relatively accurate products throughout the rest of East Africa.
Researchers found that machine learning models can help predict village food insecurity outcomes in Sub-Saharan African countries. The models incorporate publicly available data on weather, geography, and food prices to capture a wide variety of factors that can influence food insecurity. Key takeaways include the need for interpretabl...
A new technique combining microwave data with existing computer weather forecast models reduced forecast errors for Hurricane Harvey, improving track, intensity, and rainfall forecasts. This could lead to better warnings and preparedness for tropical cyclone-associated hazards.
Researchers developed a new avalanche forecasting method using computer simulations of snow cover, which can detect weak layers and identify hazard in a different way. The approach showed consistent results with observed frequencies over 16 years, offering potential to support forecasting in the future.
A recent study found that large wildfires and severe heat events worsen air pollution across the western United States, affecting 68% of the region's population in one day. The study revealed an increasing trend in days with high levels of both particulate matter and ozone, tied to rising temperatures and wildfires.
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.
Detailed supercomputer simulations show that the North American monsoon occurs when Mexico's Sierra Madre Occidental mountains divert the eastward-trending jet stream toward the equator, cooling moist tropical air until it condenses and falls as rain. This new understanding will impact forecasts in the region.
The North American Monsoon originates from the interaction of mountain ranges with extratropical atmospheric circulation, deflecting the jet stream and generating a stationary wave. This unique case has implications for models forecasting heavy rainfall events brought by the monsoon.
A new prediction framework can forecast extreme climate events like floods and heatwaves up to two days in advance, allowing for crucial preparation time. This network-based approach analyzes large-scale connectivity patterns in observational data to improve forecasting accuracy.
The Mountain Rain or Snow project collects observations of rain, snow, and mixed precipitation from across mountainous regions. Volunteers can submit their own reports via smartphone or computer to improve satellite monitoring and model predictions, leading to better weather forecasts, skiing conditions, and avalanche risk assessments.
A University of Arizona-led study reconstructs Earth's climate since the last ice age, highlighting unprecedented global temperatures and the speed of human-caused warming. The research combines two independent datasets to create a more complete picture of past temperatures.
A recent survey reveals a new method using cloud-cleared radiances improves forecasting of high-impact weather events like hurricanes and typhoons. The technique is now being applied to numerical models for enhanced daily forecasts.
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.
A Brazilian study reveals that forest fires and wildfires modify the freezing process of cloud droplets, altering natural cloud functioning and potentially impacting precipitation. The research used a large dataset to show that aerosols emitted by fires can affect cloud formation in southern Amazonia during the rainy season.
A study in Nature Communications finds that strong El Niño events can drive nearly 6 million children into undernutrition, affecting 70% or more of children globally. Proactive climate action could prevent this tragedy by providing targeted interventions to vulnerable areas.
A new machine learning approach has been developed by researchers at the Department of Energy's Pacific Northwest National Laboratory to improve hurricane intensity predictions. The model uses artificial intelligence techniques and can run on a commercial laptop, offering more accurate forecasts than existing models. It also enables th...
The new Fengyun-3E satellite provides 100% global data coverage, with 11 instruments on board to observe cloud, radiation, and more. China joins Europe and the US in sharing a global responsibility for early morning orbit observations.
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 recent survey of people affected by hurricanes found that the public is willing to pay more than $500 million a year for improved hurricane forecasts. The study also found that wind speed forecast is the most valuable improvement, with an average willingness to pay of $28.89 per household per year.
Researchers at Stanford University have discovered the physical mechanism behind icy plumes that precede severe thunderstorms and potentially deadly tornadoes. The study reveals a hydraulic jump phenomenon triggered by fluid obstacles in the atmosphere, leading to rapid water vapor injection into the stratosphere.
Researchers found that late-season weeds had a significant impact on corn yields, with minimal control resulting in an average loss of 50% and exacerbating crop losses under hot or dry conditions. The study suggests that climate change is not the only factor affecting corn yield, but rather its interaction with weeds.
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.