Articles tagged with Weather Simulations
The Coupled Ocean/Atmosphere Mesoscale Prediction System-Tropical Cyclone (COAMPS-TC) offers detailed intensity forecasts of tropical storms, improving accuracy for Navy and civilian officials. The new model will help predict a storm's strength from one to five days out, supporting fleet operations and disaster relief efforts.
Scientists use direct statistical simulation to model fluid jets, fast-moving flows in oceans and atmosphere. The new approach is a key step toward bringing basic physics models to bear on climate science, enabling more efficient climate simulations.
Suomi NPP, a partnership between NASA and NOAA, supports Earth science research and weather forecasting by providing critical data for global change science and improving short-term weather forecasts. The satellite's observations help advance science and increase the accuracy of meteorological predictions.
A BYU mechanical engineering professor's research reveals that internal waves play a crucial role in predicting weather, leading to frequent forecasting mistakes. By understanding how these waves move energy around, forecasters can develop better linear wave models to improve their predictions.
The study reveals that horizontal convective rolls affected fire behaviour, introducing variability in wind, temperature, and humidity conditions. This new understanding has the potential to improve fire management and warning systems, providing a better guide for public warning systems and firefighting resources.
The next generation of Digital Earth seeks to address issues with current digital globes by incorporating local perspectives, temporal information, and open-source partnerships. This shift aims to improve accuracy and inclusivity while maintaining scientific standards.
Researchers at University of Missouri-Columbia discovered that the region's record-warm February and March were linked to a similar La Niña climate pattern in 1889. This finding could help scientists develop more accurate weather prediction models by understanding the variability within climate patterns.
The Office of Naval Research is developing advanced weather prediction models to enhance the Navy's forecasting capability, accuracy, and safety at sea. The new models, such as TC-COAMPS, enable real-time forecasting of storms' track and strength, improving warfighting advantage and reducing fuel consumption.
Researchers found a significant warming effect over wind farms, up to 0.72 degrees Celsius per decade, attributed to turbine wake interactions. The study uses satellite data to quantify the potential impact of wind farms on weather and climate.
A new study published in Environmental Science and Technology found that air pollution from cars, trucks, planes, and powerplants cause 13,000 premature deaths in the UK each year. Car exhaust was the single greatest contributor to premature death, affecting over 3,300 people annually.
Researchers at Syracuse University developed statistical prediction models to help utilities assess risk and identify failing pipes. The models allow for proactive maintenance and reduced costly emergency repairs.
A new study uses weather forecasting models to predict the spread of brain tumors, demonstrating the feasibility of a mathematical approach. The model, known as LETKF, provides accurate and efficient predictions of tumor growth and spread, taking into account errors in model parameters and measurement uncertainties.
Researchers focus on Northern Bettong to understand climate change impact. Short-term weather events reveal clearer insights into animal movements and range boundaries than gradual climate changes.
Researchers propose a new model, 'wrap up', explaining the evolution of low pressure systems. This model addresses weaknesses in the Norwegian meteorological model, providing a better understanding of severe weather conditions.
Research suggests planes may induce odd-shaped holes or canals into clouds, potentially increasing precipitation near airports with frequent cloud cover. This inadvertent seeding process works similarly to intentional cloud seeding and may require more frequent de-icing for planes.
The PhenologyMMS software predicts plant growth stages based on weather reports and soil moisture, providing farmers with a decision-making tool to optimize crop management. The program covers multiple crops, including corn, wheat, barley, and millet varieties, and can be used independently or integrated into existing models.
The new Space Weather App allows users to access real-time images and data on solar events, including coronal mass ejections and X-ray outbursts. Users can customize the app to display information of interest, increasing public awareness of space weather.
A physics-based space weather prediction model is now in operation, offering a one-to-four day warning of high-speed solar plasma streams and Earth-directed coronal mass ejections. This development addresses the growing need to protect global communications infrastructure from severe space weather disruptions.
Researchers used Doppler weather radar data to improve forecast models for monsoon systems, reducing landfall error from 200km to 75km. This enhancement can better prepare people for heavy rains and catastrophic floods in coastal areas of India.
The GOES-P spacecraft is proceeding through final checks before its launch on March 1. The Imager, Sounder and Solar X-Ray Imager have completed cleaning and inspections, while optical port covers are being installed as the last mechanism to be deployed in orbit.
The University of Oklahoma Center for Analysis and Prediction of Storms has been awarded three separate grants worth nearly $3 million to enhance severe weather prediction, improve wildfire management and predict tropical cyclones. The grants will focus on next-generation supercomputing, improved model resolution and advanced data assi...
A Georgia State University professor will use a $1 million grant from the National Science Foundation to develop an integrated model that combines wildfire, weather, and operational models. The model aims to provide firefighters with a decision-making tool for combating wildfires more effectively.
A NASA experiment has successfully 'hindcasted' the path of Cyclone Nargis, which killed over 135,000 people in 2008. The new data integration and mathematical modeling approach uses satellite imagery and atmospheric profiles to provide multi-day advance warnings for cyclones in the Indian Ocean.
Researchers use MODIS data to detect natural oil slicks in the Gulf of Mexico, finding a higher occurrence than previously thought. Meanwhile, studies suggest freak waves may be responsible for shipwrecks in Japan's notorious wave-prone region, with modeling revealing a cascade process governing weather dynamics.
Kristine C. Harper's 2008 book, 'Weather by the Numbers: The Genesis of Modern Meteorology,' has received international acclaim from atmospheric science librarians. The book explores the transformation of meteorology from an art to a scientific discipline, highlighting the development of numerical weather prediction and its impact on w...
Using NASA satellite data, forecasters can now more accurately predict the timing of two out of three dust events. This capability is crucial for issuing early warnings to populations at risk for dust-related health complications.
A team of Arizona State University researchers is investigating human vulnerability to deadly heat exposure in the face of climate change. The study aims to guide policymakers and planners in bolstering protective measures to prevent heat-related illness and deaths.
Researchers plan to develop exascale machines that can process over 10^18 calculations per second, with a focus on virtualization and managing multiple programs on a single platform. The goal is to lay the groundwork for future systems that can guarantee service levels even in the event of machine failure or overload.
Researchers develop novel weather and climate modeling strategy to isolate interactions between weather and climate, applying it to the NCAR's Community Climate System Model. This project aims to advance Earth system science, improve weather and climate predictions, and inform environmental policies.
Researchers develop model predicting disease outbreaks based on weather patterns and climate variability. The study shows an association between high temperature and daily incidence of cryptosporidiosis in Massachusetts, highlighting the need for better understanding of how climate affects disease spread.
A new research project funded by the National Science Foundation aims to improve weather models and analysis for industries such as food, clothing, and energy. The goal is to educate meteorologists on how to apply weather forecasts to real-world business decisions.
A predictive model, sCast, uses October snow cover in Siberia to predict winter temperatures and snowfall in the Northern Hemisphere. The model has been verified to accurately forecast winter conditions over much of eastern United States and Northern Eurasia.
A pilot forecasting program in Bangladesh is delivering 1- to 10-day forecasts directly to over 100,000 people living on floodplains, alerting them to potential floods. The system uses a combination of weather forecast models, satellite observations, and hydrologic modeling techniques to predict flooding.
A new NASA study suggests that greenhouse-gas warming may raise average summer temperatures in the eastern United States nearly 10 degrees Fahrenheit by the 2080s. This could lead to extremely hot summertime temperatures, especially during summers with less-than-average frequent rainfall.
A new model developed by researchers at the University of California - Santa Barbara predicts the survival of coral reefs based on their shape and size. The study found that table corals with broad flat tops are more susceptible to strong wave forces, while bushy or mounded corals are less vulnerable.
Researchers at Purdue University found that considering all interactions among temperature, radiation, precipitation, and land use can aid humans in preparing for extreme shifts in weather patterns. They discovered that a lack of precipitation will have the most dramatic effect on living conditions in the future.
The Weather Research and Forecasting model (WRF) has been adopted for operational use, predicting extreme weather with substantially improved accuracy. The high-resolution WRF serves both public forecasts and cutting-edge research, leading to better forecasts.
Researchers from NASA and international agencies have developed a new tool to predict the timing of ozone hole recovery. They predict the ozone hole will recover around 2068, nearly 20 years later than previously believed.
Scientists at Rutgers have created a computerized model to understand the degree of harmful exposure in the immediate aftermath of the World Trade Center attacks. The model, combining satellite data and regional weather forecasts, provides a way to evaluate human exposure to aerosols released during the disaster.
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.
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.
Researchers at Johns Hopkins University have discovered a new mathematical formula, called the advected delta-vee equation, that can help predict turbulent flow behavior. This equation provides a shortcut to describe a complex characteristic of turbulence called intermittency, which is difficult to include in computer models.
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.
Climate models predict a rapid increase in global temperatures and sea level rise of up to 30cm, with severe consequences for agriculture, ecosystems, and extreme weather events. The study also highlights the impact of human activity on the climate, fuelling global warming.
A new weather model, ARW, uses high-resolution data to predict hurricane intensity and location of fine-scale rain bands. This enables better warning systems for floods, power outages, and road blockage.
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.
A NASA study found that conversion of wetlands to agricultural lands can lead to more severe freezes in south Florida. The researchers analyzed data from the Landsat 5 satellite and weather records to simulate three freeze events, concluding that land-use changes can enhance damage inflicted upon agriculture.
The University Corporation for Atmospheric Research has purchased a large-scale Linux-based computing system, adding significant computing capacity to NCAR's arsenal. The system will enable the evaluation of major community climate and weather codes in a full-scale Linux environment.
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.
Corn earworm moths travel at varying heights influenced by air currents, affecting their migration patterns. By analyzing wind patterns and weather forecasts, researchers aim to forecast the arrival of these pests and develop targeted insecticide strategies to reduce damage.
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.
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 AMPS system uses a tailored computer model, Polar MM5, to provide detailed forecasts for the extreme polar environment. Meteorologists have successfully used AMPS in emergency rescues from Antarctica since 2001, including a recent medical evacuation and ship rescue.
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.
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.
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.
A new computer model has identified a significant link between high-latitude climate phenomena and tropical regions, warming ocean temperatures by up to 1 degree Celsius. The discovery reveals a hidden climate mechanism that significantly influences global and regional climate change.
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.
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.