Articles tagged with Weather Forecasting
A new radar technique is being tested to track water vapor in the lower atmosphere, helping forecasters predict storm locations and timing. The REFRACTT project uses multiple Doppler weather radars to measure changes in radar signals caused by refraction, revealing the presence or absence of atmospheric moisture.
Scientists at NASA's Marshall Space Flight Center highlight the dangers of lightning during National Lightning Safety Awareness Week. The study reveals that over 8 million cloud-to-ground lighting strikes occur daily worldwide, with an average of 67 deaths annually in the US.
Researchers combined NASA's QuikSCAT satellite data with aircraft sensor data from tropical storms, improving the accuracy of hurricane forecasts. The new generation WRF computer model was able to reproduce the structure of rainfalls that caused flooding during landfall, providing valuable insights into tropical cyclones.
The US Office of Naval Research supports the joint US-Taiwan COSMIC satellite project, which will track hurricanes, monitor climate change, and accelerate space weather research. The constellation will provide real-time atmospheric data daily.
The US has launched a constellation of six low-orbiting satellites called COSMIC to provide real-time atmospheric data over thousands of points on Earth. The system will measure the bending of radio signals from GPS to track hurricanes, typhoons and climate change.
The COSMIC satellite network measures atmospheric data daily in real time over thousands of points on Earth using GPS signals. Temperature and water vapor profiles will help meteorologists forecast storms and study long-term climate change trends.
The HYbrid Coordinate Ocean Model (HYCOM) provides long-range weather prediction, enhances ocean current understanding, and supports real-time maritime operations. This innovative tool enables accurate forecasts and tracking of pollution, algal blooms, and oil spills.
A Purdue University researcher has developed a more accurate weather prediction model by incorporating the amount of moisture surface vegetation releases into the upper atmosphere. This new approach improved forecasts of storm intensity, location, and timing, leading to better severe weather predictions.
A new malaria forecasting tool developed by scientists at the University of Liverpool can predict epidemics of malaria up to five months in advance, using climate variability. The model will assist doctors and health care providers in preventing and controlling the disease.
Researchers developed an early-warning system that uses population vulnerability, rainfall, and health surveillance to predict changes in seasonal disease patterns. The system provides health service managers with warnings of changes in epidemic risk five months before the peak malaria season.
Researchers used NASA's TRMM satellite data to analyze temperature changes inside hurricanes, providing clues about storm transformations. The study sheds light on the stages of extra-tropical storms and helps forecasters better understand hurricane development.
Researchers at UC Davis are studying the Madden-Julian Oscillation to improve weather and climate forecasting. The phenomenon has subtle effects on US weather patterns, including links between intense rainfall and droughts.
The Virtual California model forecasts almost 400 major earthquakes over 40,000 years, with a 25% chance in the next 20 years. The simulation indicates higher probabilities for future quakes by 2086.
Researchers discovered the physics behind coastal wind jets, which can gust up to 40% higher than normal wind speeds. This knowledge could aid sailors in planning strategies and improve weather forecasting for wind energy and flood prevention.
An e-Science project has adapted SARIS software to access near real-time Met Office forecasts of ocean currents and winds, providing more accurate data for rescue predictions. This adaptation aims to reduce the time to rescue and potentially save lives.
The University of Wisconsin-Madison's Tropical Cyclones group is using its specialized tools to help forecasters track Hurricane Ophelia. The tools provide critical information on the storm's trajectory and intensity, enabling more accurate forecasts and helping to save lives.
The Linked Environments Atmospheric Discovery project aims to create a high-speed computing infrastructure for timely and accurate weather forecasts. The system will pool data from various sources, including ground sensors, satellites, and radars, to launch hundreds of simulations at the same time, resulting in more accurate predictions.
The study found that farmers who participated in workshops made better decisions in response to good information, resulting in improved crop yields. The researchers also found that the workshops increased the use of forecast information among farmers, particularly those in subsistence farming.
The newly completed field tests show that the new approach in coupling models can be successful, producing similar temperature and wind outputs globally. The ESMF enables sharing and comparison of alternative scientific approaches from multiple sources, making it easier to develop realistic representations of the Earth as a system.
Scientists at NASA have developed a way to process radar data from the Tropical Rainfall Measuring Mission (TRMM) satellite, providing 3D snapshots of hurricanes. This allows forecasters to access information on heavy rainfall rates and cloud heights within three hours, helping them make more accurate forecasts.
The new Web-based modules, developed by COMET, will acquaint forecasters with the physics behind rip currents and help them use wind and wave forecasts to produce outlooks of rip-current risk. The modules include animated depictions of rip-current evolution in three dimensions.
The WVSS II sensors gather data more often, at higher vertical resolution, and at lower cost than satellites and balloons. This improves forecasts of thunderstorms, microbursts, turbulence, fog, ceiling visibility, rotating wakes from other aircraft, snow and ice storms, and year-round precipitation.
Researchers discovered that the onset of spring is more rapid than previously thought and linked to a phenomenon known as the stratospheric final warming. This event accelerates the weakening of tropospheric winds, allowing for more accurate weather prediction models.
Researchers found a significant increase in tornado warnings after WSR-88D radar installation, with almost doubled warnings and increased lead time. The study also revealed expected fatalities and injuries were 45% lower for tornadoes occurring after radar installation.
NASA has postponed a scheduled satellite launch at Vandenberg Air Force Base in California. The launch, originally set for May 12, will now take place pending favorable weather conditions. NASA TV coverage is available online and via satellite.
The NOAA-N satellite will collect data on Earth's surface and atmosphere for weather forecasts, climate predictions, and search and rescue operations. With advanced imaging and sounding capabilities, the satellite aims to improve understanding of environmental changes worldwide.
Researchers have developed a new model that accurately forecasts US hurricane activity, enabling skilful seasonal predictions to benefit individuals and decision-makers. The model uses height-averaged winds as a predictor, exhibiting significant linkages to US landfalling hurricanes.
A Purdue University study found that many tornadoes form from 'line-shaped' storms associated with large weather fronts, particularly in the Midwest. These tornadoes are more likely to occur late at night and in colder months, challenging traditional notions of severe weather patterns.
El Nino forecasting can aid in managing high-yield fisheries with boom-and-bust cycles, controlling tropical diseases like mosquito-caused malaria, and protecting marine mammals and other ocean species. By predicting ENSO events nine months in advance, scientists can deploy resources effectively.
Researchers used a simple climate model to demonstrate that changes in the strength of winds in the stratosphere can cause changes in tropospheric weather systems. This understanding is crucial for improving seasonal weather forecasts and predicting the effects of ozone depletion and global warming on our climate.
A field study by NCAR and NOAA has provided new insights into bow echoes, revealing that smaller storms can be more destructive than larger ones. The BAMEX experiment used aircraft, ground-based storm chasers, and advanced radar technology to collect detailed data on thunderstorms in the Midwest.
The American Institute of Biological Sciences (AIBS) has been tapped to coordinate the design of a national network dedicated to ecological observations, known as NEON. The project aims to improve scientific understanding of various research areas, including climate change and biodiversity.
A new theory explains how drizzle forms within typical cloud lifetimes, providing insights into local weather and global climate. The research suggests that a statistical barrier speeds up drizzle formation, allowing fewer large drops to dominate the process.
The Soil Moisture Experiment 2004 aims to understand how much moisture is retained in soils, helping estimate potential flooding or water absorption. By analyzing data from satellites, airplanes, and ground teams, researchers can provide better forecasts for monsoon rainfall and water supply.
A six-week field experiment will gather data on regional air quality, intercontinental transport of polluted air masses, and human health effects. The study, ICARTT, involves five countries, universities, and government agencies.
Researchers use the North Alabama Lightning Mapping Array to monitor storm weakening and strengthening, improving severe weather detection. NASA's satellite technology provides near real-time data on severe weather and lightning strikes worldwide, aiming to reduce false alarms and improve forecasting accuracy.
New NASA technology enhances NOAA's weather forecasts by integrating satellite data and lightning tracking, leading to more confident seven-day severe local storm forecasts. This improved prediction capability can also enhance tornado warning lead times and better predict thunderstorm occurrence.
The US Pentagon is using cutting-edge sensors and software tests to protect against airborne hazards, including chemical and biological attacks. The system includes a multiscale weather forecast model, lidars, and other sensors to monitor air flow and turbulence around the building.
A study found that California's beach warning system incorrectly notifies the public about coastal water quality up to 41% of the time. The research identified tidal outlets as major contributors to pollution along the shore, suggesting a need for improved warning systems and approaches to managing storm runoff.
Scientists have developed a real-time operational forecast system using satellite data, providing accurate 3D ocean conditions and helping Coast Guard rescuers determine the direction of stranded individuals. The system uses multiple satellite measurements and sensor data to generate forecasts several days ahead.
A statistical model created at Ohio State University predicts sea surface temperatures in the tropical Pacific Ocean, providing a way to quantify the uncertainty surrounding El Niño. The model can forecast El Niño six months in advance, giving farmers and commercial fishermen time to plan for the coming season.
The SeaWinds scatterometer on NASA's QuikSCAT satellite provides ocean surface wind speed and direction measurements, leading to improved storm predictions at sea. This increased accuracy brings economic savings and reduces weather-related loss of life, especially in global shipping.
The USWRP's improvements to the global computer forecast model developed at NOAA's Environmental Modeling Center have led to a significant boost in hurricane track forecast accuracy. Since 2000, NHC forecasts have benefited from these advancements, predicting Atlantic tropical cyclones' tracks about 35% more accurately than prior to 2000.
Four IU computer science projects will develop new software systems to improve weather forecasting accuracy, protect scientist data, enable grid computing participation and make biomedical instruments accessible globally. These projects aim to increase research collaboration and accessibility.
The National Center for Atmospheric Research/University Corporation for Atmospheric Research has been awarded $11.25 million to develop new weather forecasting tools, including the LEAD project. The tool will enable researchers to access state-of-the-art weather prediction models on demand and collaborate with colleagues in real-time.
The DOWs will deploy at or near the coast in the direct path of the storm, collecting high-resolution data and rapid-scan Doppler radar data from inside the eye. The Rapid-DOW can visualize three-dimensional volumes in 5 to 10 seconds, observing boundary layer rolls, wind gusts, and other phenomena as they evolve.
NASA satellites sample critical 'ingredients' to predict hurricane formation, including sea surface temperature of at least 82 F, rotating winds, air temperature, and humidity. The data helps forecasters determine storm strength, location, and tracks.
Dr. Ginis receives two-year grant to improve hurricane forecasting model and enhance storm prediction capabilities. The model, developed in collaboration with NOAA scientists, aims to better understand and predict extreme winds and heavy rain causing $5 billion in annual damages.
The study improved forecast accuracy for a major winter snowstorm in Washington, D.C. and demonstrated the potential to enhance storm tracking and predict snowfall amounts.
Researchers are using mobile radar to track wind patterns in Montana wildfires, enabling more accurate predictions of fire behavior and helping firefighters fight fires more efficiently. This technology has the potential to transform wildland fire monitoring and improve public safety.
NASA has created high-resolution world maps showing the frequency of lightning strikes worldwide, providing unique insights into climate information. The data indicates uneven distribution of lightning strikes globally, with increased activity in certain regions during El Nino events.
A study by OSU researchers found that their weather forecasting tool, AMPS, outperformed competing models in predicting extreme weather conditions at the South Pole. This achievement has implications for extending the limited summer research season and improving polar forecasting skills.
TRMM allows researchers to daily map areas of potential flooding using precipitation radar data and high-resolution measurements of cloud water content. The satellite provides updated records on a global scale, enabling scientists to track storms, monitor El Nino conditions, and assess crop health in remote regions.
BAMEX will investigate how damaging winds unfold at night, when low-level air cools and stabilizes. The study aims to improve forecast warnings for high winds produced by bow echoes and heavy rains triggered by mesoscale convective systems.
Researchers at Penn State have developed an early flash flood warning system that can potentially save lives and property by forecasting extreme weather events. The system uses a combination of dynamical and statistical models to identify patterns and anomalies in atmospheric conditions, allowing for three-day advance warnings.
A new monsoon forecasting method developed by Professor Peter Webster could guide farmers in choosing optimal planting times and making informed decisions about water management. This technique, applicable to any monsoon region, has the potential to create a significant increase in crop yields without relying on pesticides or fertilizers.
A new web-based system is being tested to improve winter road treatment. The Maintenance Decision Support System (MDSS) uses computer models to project hour-by-hour weather and road conditions up to two days in advance. This allows users to make informed decisions about road treatments, potentially saving lives and reducing costs.
A new GPS-based index improves lightning strike forecasts by nearly 10% and reduces false alarm rates by 26% at the Kennedy Space Center. The index combines data on water vapor in the atmosphere with other meteorological data to provide valuable guidance for forecasters.
Researchers found that changes in SSTs affect the Madden Julian Oscillation, a key driver of South Asian monsoons. The study suggests that warmer sea surface temperatures can predict up to 30% of MJO fluctuations.
A team led by Zhang aims to improve daily weather forecasts by integrating vast amounts of observational data. Ensemble-based data assimilation focuses on incorporating uncertainties surrounding previous forecasts and current observations, using statistics to estimate initial conditions.