Articles tagged with Weather Forecasting
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.
The Navy has built an Air-Sea Interaction Tower to measure atmospheric and ocean conditions, including temperature, humidity, and wave height. The tower will provide better weather forecasts, enabling the avoidance of storms and saving lives.
Scientists are developing a new space weather model that can mimic solar explosions, auroras, and geomagnetic storms. The National Center for Atmospheric Research (NCAR) will provide a computer model of Earth's upper atmosphere to aid the effort.
Since 1992's Category 5 Hurricane Andrew, NASA satellites have provided critical data to improve hurricane forecasts. The Tropical Rainfall Measuring Mission (TRMM), QuikSCAT, and Aqua satellites offer insights into rainfall intensity, wind patterns, and ocean temperatures.
The COSMIC satellite network will collect a global, 3-D data set, improving analyses of both weather and climate change. The satellites will probe the atmosphere using radio occultation to track temperature in the upper atmosphere and measure high-altitude electron density.
The Darwin Site, established in 2002, is the fifth ARM site and first with an international partner. It features state-of-the-art instruments to measure cloud properties and atmospheric conditions, contributing to more accurate climate models. The research aims to improve predictions of global warming and climate change.
Researchers are developing a forecasting technique to predict sea nettle concentrations in Chesapeake Bay using real-time monitoring of environmental factors. The goal is to mitigate the economic impact of sea nettles, which affect tourism and the food web by devouring fish eggs and larvae.
Scientists have improved weather and climate forecast models by using new Terra data to measure albedo, revealing regional variability in the Sahara Desert and Arabian Peninsula. This correlation will help fine-tune weather and climate models, enabling more accurate predictions.
NASA's QuikSCAT satellite data reveals two ITCZs: a northern zone near the equator and a southern zone south of the equator. The southern zone is weaker due to cooler ocean water, affecting wind speeds and precipitation patterns globally.
The Antarctic Mesoscale Prediction System (AMPS) successfully predicted a brief window of favorable weather, allowing helicopters to bring the last passengers aboard. The forecasting support helped guide the ice-strengthened ship SA Agulhas to retrieve the stranded vessel and crew from near Antarctica.
The NOAA-17 satellite has been successfully launched into orbit, providing improved imaging and sounding capabilities for weather forecasting and climate monitoring. The spacecraft will collect meteorological data and transmit it to users worldwide.
The FLAMBE project utilizes geostationary satellites to detect and monitor forest fires every half-hour, providing early warnings of haze events. The system also estimates burned areas, smoke fluxes, and radiative impacts, complementing NASA's Terra satellite products for improved global climate understanding.
The new tool helps decision makers utilize long-range forecasts by explaining and evaluating their performance. It allows users to customize evaluations based on lead-times, seasons, and locations relevant to their specific needs.
The National Center for Atmospheric Research (NCAR) has won a $3.8 million NASA grant to develop the core software for an Earth System Modeling Framework. The framework will enable models to work together, assimilate observational data, and produce more realistic simulations of weather and climate.
A massive weather study is underway in Kansas, Oklahoma, and Texas, using six aircraft and 30 ground sensors to track water vapor and predict heavy rain. The IHOP2002 project aims to improve forecasts from 1 to 12 hours ahead of heavy rain, which could help in flash-flood safety and other applications.
The new model traces water vapor from its source in the atmosphere to where it falls back to Earth, providing a clearer picture of how water moves. This allows for more accurate weather forecasts by identifying regional sources of atmospheric moisture.
Researchers developed a Web-based display, CIP, to describe current icing conditions, which goes into service this week for meteorologists and airline dispatchers. A companion tool, FIP (Forecast Icing Potential), forecasts potential icing up to 12 hours ahead but is still in development.
A new method significantly improves U.S. seasonal forecast accuracy by analyzing changes in sea surface temperatures across various ocean basins. The approach raises the bar for seasonal and inter-annual climate forecasts, with increases in predictability noted during spring and summer months.
A University of Maine professor has developed a classification system to help weather forecasters and the public understand the likely impacts of winter storms. The system assigns an intensity index and category score based on air pressure and forward speed, providing insights into storm strength and duration.
A new research project could help forecast floods and associated cholera outbreaks in Bangladesh, aiding farmers and improving quality of life. The team will use computer modeling to pinpoint Indian Ocean conditions and rainfall patterns, enabling local forecasts that can aid communities.
Researchers have discovered a new source of information to aid in weather forecasting, leveraging shifts in stratospheric winds to predict surface weather two months in advance. The study reveals that changes in the stratosphere can influence storm tracks and extreme cold events in the Northern hemisphere.
Researchers are testing new advanced weather technology to monitor rainfall in watershed basins as small as one square kilometer. The technology will provide more precise and accurate flood and flash flood warnings, helping emergency management officials prepare for events.
The TRANSMAP system combines land and marine data to provide real-time information on road conditions and weather forecasts. It allows users to view current and historic data from multiple sensors, as well as overlay maps from the state's Geographic Information System.
Researchers at the University of Massachusetts are flying into the eyes of hurricanes using advanced airborne sensors to gather real-time data. The new IWRAP system will provide finer resolution than previous systems, enabling better predictions about storm intensity and potential path.
A broad consortium of scientists proposes developing ecological forecasting to forecast environmental changes, protect ecosystems, and predict the impacts of global warming. The initiative aims to improve planning and decision-making by providing reliable forecasts of ecosystem state and services.
The Scripps Institution of Oceanography has developed a groundbreaking wildfire forecast for the western United States, using statistical methods to predict fire seasons and fuel availability. The 2001 forecast suggests a much milder wildfire season compared to 2000, which burned over 7 million acres and caused $1.6 billion in damage.
Researchers at Penn State aim to improve flood prediction by evaluating past storms with different forecasting methods. They found that convective parameterization schemes can help forecast rainfall, but the best scheme varies depending on the season and atmospheric conditions.
Researchers at Johns Hopkins University Applied Physics Laboratory have developed a system to measure magnetic and electrical fields over large areas of the ionosphere, providing the first continuous monitoring of electric currents between space and the upper atmosphere. The advanced system will enable improved understanding and foreca...
New satellite-generated rain maps provide more accurate tropical rainfall measurements, helping manage water resources and understand El Niño-La Niña patterns. The TRMM satellite's high-resolution data also enables better weather forecasting and climate projections.
The Harvard Ocean Prediction System (HOPS) is a modular system that provides forecasts of ocean weather and information about ocean life. HOPS has been used to predict the location of crash debris from EgyptAir Flight 990 and identify promising waters for commercial fishing.
The Web Weather for Kids website has won an award for its online weather forecasting contest, which aims to engage middle schoolers in predicting the weather. The site's success is attributed to its interactive and educational content, which teaches students about thunderstorms, tornadoes, and other phenomena.
The Colorado State University hurricane forecast team predicts a moderate 2000 season with fewer storms than recent years. This is attributed to the La Niña phenomenon weakening by next season, which should reduce its enhancing effect on hurricane formation in the Atlantic Basin.
Researchers developed a model to predict bird flight patterns, enabling pilots to adjust their routes and altitudes. The model can forecast bird locations and altitudes hours in advance, reducing the risk of bird strikes and damage to windshields and turbine engine blades.
The SHOWEX experiment aims to better predict wave formation and severity, improving navigation safety at sea and weather forecasting. Researchers will use a range of instruments, including aircraft, craft, buoys, and subsurface sensors, to study wave components and their interactions.
Researchers at Penn State have developed a new mobile data access system (MDAS) that enables efficient access to diverse data sources through both wired and wireless connections. The system uses multidatabases to provide integrated access to multiple databases with a single query, reducing traffic jams caused by simultaneous queries.