Articles tagged with Weather Simulations
Researchers at Colorado State University have developed an empirical model that accurately predicts atmospheric river activity in the western US three weeks in advance. This breakthrough could enhance long-term weather forecasting capabilities, allowing for earlier warnings of extreme precipitation, floods, and droughts.
Researchers at the University of New Hampshire found that climate change effects could worsen by mid-century, leading to fewer snow days, more extreme heat, and reduced cold water fish habitats. The study used models benchmarked to field measurements to evaluate the Merrimack River watershed in New Hampshire.
A special issue of Advances in Atmospheric Sciences highlights recent research on Arctic-midlatitude linkages. The study aims to improve understanding and prediction of Arctic change, which influences extreme weather events in the mid-latitudes.
A new IASI channel selection method has been developed to improve weather forecasting accuracy by reducing bias in humidity forecasts. The method used a one-dimensional variational analysis approach to select 200 new channels from the available 314 channels.
A new analysis has calculated the likelihood of a massive rogue wave during Hurricane Joaquin in 2015, which may help improve the prediction of rogue waves to understand risks posed by these unusual wave patterns. The study suggests a one-in-130 chance of a 46ft high rogue wave occurring during the hurricane.
A new weather forecasting model, Subseasonal Experiment (SubX), combines multiple global models to produce more accurate forecasts for the US. The multi-model approach improves temperature and precipitation outlooks for weeks 3-4, providing critical insights for decision makers.
Texas A&M University researchers have developed a predictive model that can identify potential vulnerabilities in electric grids and predict weather hazards. The model uses historical and close-to-real-time data to analyze the impact of these factors on power system outages, enabling utility companies to take proactive measures.
A new study by AAAS predicts climate change will have a devastating impact on certain US counties, with losses exceeding 20% of gross county product in some areas. Southern and midwestern populations are projected to suffer the largest economic damage due to increased cyclone intensification and sea level rise.
Researchers developed a model that uses satellite data to predict malaria outbreaks with one-month lead time, allowing for targeted resource allocation and public health responses.
A new study projects a 50% increase in conducive weather conditions similar to those in January 2013, leading to more frequent severe haze events in Beijing. The researchers developed an effective Haze Weather Index (HWI) to represent such conditions, which are influenced by large-scale circulation changes and climate change.
A new study proposes a risk-based approach for classifying road surface conditions under winter weather events, aiming to improve current road classification systems. The approach estimates driving risk using a collision model calibrated with detailed hourly data of weather, road conditions, traffic, and accidents.
A new tool called EEGGL helps map out the paths of coronal mass ejections (CMEs) before they reach Earth. The model is based on fundamental physics theory and takes into account the magnetic structure of CMEs, providing a better understanding of their behavior in space.
A new $525,000 grant aims to improve understanding of shallow cumulus clouds' behavior, which play a crucial role in atmospheric circulation and global climate. The research will focus on the mixing process called entrainment, aiming to enhance weather forecasts and climate model projections.
A team of researchers from York University, NASA, and Johns Hopkins University have identified icy features on Pluto, including penitentes, which are bowl-shaped depressions with spires around the edge. The study suggests that these features may exist on other planets where environmental conditions are similar.
Researchers at UC San Diego developed practical strategies for building and coordinating balloons within hurricanes, using GPS and cellphone-grade sensors. The approach leverages control theory to distribute balloons horizontally and mitigate turbulence fluctuations, enabling improved in-situ sampling and forecasts.
DeMarco's work on dynamical systems has led to the emergence of arithmetic dynamics, a field that connects number theory with mathematical structures. Her research has also shed light on connections between dynamical systems and elliptic curves in arithmetic geometry.
University of Washington researchers have developed a method to transform lightning strikes into weather-relevant information, improving storm forecasts. The new method uses data from the WorldWide Lightning Location Network and has been tested on several cases, including a 2012 derecho thunderstorm system and a 2013 tornado.
A recent study used a convective-permitting ensemble forecast system to evaluate the extreme rainfall event on July 21, 2012, in Beijing. The results showed that some members of the ensemble forecasting system captured the extreme prediction reasonably well, including the timing and location of extreme precipitation.
The Observation, Prediction and Analysis of Severe Convection of China (OPACC) project aims to improve the prediction skills of convective storms. Researchers have published 224 papers on convective weather in peer-reviewed journals since 2013.
A Rice University-led team demonstrates how to improve the quality of simulations run on supercomputers by using inexact computing methods, which can reduce energy costs and maintain accuracy levels. The approach allows for significant improvements in solution quality within a fixed energy budget.
Rensselaer Polytechnic Institute researchers develop a model to forecast the impact of rising temperatures on lakes' carbon cycle, with potential implications for global warming. By analyzing 2,000 lakes across the US, they aim to understand how lakes will respond to changing weather patterns and emissions.
Researchers have created a more realistic picture of wind energy output in Europe, correcting for biases in existing data. The updated simulations show that the current European average capacity factor is 24.2%, but could increase to over 31% with improved grid interconnection and technology advancements.
A University of Utah study found that traditional lawn watering recommendations are often inaccurate for urban conditions in Los Angeles. By measuring evapotranspiration in shaded areas, researchers developed a new approach to adjust watering rates and achieved higher accuracy than existing models.
A new study found that household use of coal and dirty fuels in households is a major contributor to Beijing's notorious air pollution. Eliminating these emissions could reduce particulate levels by up to 22%. Regional efforts are crucial to address this issue, as individual cities may not have control over surrounding regions.
Researchers created a detailed, high-resolution simulation of weather patterns in the Western US using data from tens of thousands of personal computers. The analysis showed impacts of terrain on local weather and improved accuracy for regional climate predictions.
Researchers at NASA's Goddard Space Flight Center use computer models to study tropical storms and hurricanes. Improved models can lead to better predictions and warnings for natural disasters like flooding and property loss.
Scientists have made significant breakthroughs in predicting weather and climate change by studying the fundamental thermodynamics of water droplets. Understanding how water droplets grow and interact with each other can help improve weather forecasts, but also has industrial relevance and applications.
A new study found that exceptionally warm weather episodes, rather than radiant energy, cause significant melting of the Greenland ice sheet. The research revealed that climate models tend to underestimate the impact of these events, which are expected to occur more frequently in the future due to climate change.
Researchers at University of Oklahoma are developing a higher-resolution model that uses Stampede supercomputer to predict severe hail storms with greater accuracy. The goal is to provide 2-hour warnings for storms like the May 1995 Fort Worth Mayfest storm, which caused over $2 billion in damage.
Researchers developed a framework to address uncertainty in mathematical models by considering the effects of correlated parameters. This approach improves model predictability and reliability, with applications in fields such as catalysis, combustion, environmental sciences, and biology.
A study by Oxford University scientists found that human-induced climate change increased the risk of severe storms in the south of England, leading to devastating flooding. The analysis attributed the increase in extreme rainfall to thermodynamic changes in the atmosphere and westerly air flow.
High-frequency atmospheric observations in the Arctic Ocean improved wind field accuracy, reducing uncertainty in sea-ice forecasts and predicting severe weather phenomena. The study suggests that a cost-effective observing network can be established to enhance polar predictions.
Researchers at UTA are analyzing the energy entering the upper atmosphere following space weather events to refine models used for satellite trajectory forecasting. Current estimates can be off by as much as 100%, resulting in an error of up to 30% in tracking satellites.
A University at Buffalo study uses Twitter data to enhance computer models guiding traffic during snowstorms and adverse weather. By analyzing over 360,000 tweets, researchers found that including such data improves the accuracy of models, particularly during peak tweeting hours and in densely populated areas.
A team of scientists from the National Oceanography Centre are on a six-week expedition to the Bahamas to update and acquire data from ocean instruments. This data helps make long-term forecasts of weather and climate by feeding it into models of the ocean and atmosphere.
Researchers used holographic imaging to analyze cloud mixing behavior, revealing clear boundaries between wet and dry air. The findings challenge current computer models and may enhance weather predictions by providing more accurate insights into cloud interactions.
A new model can measure the magnetic field configuration of a solar eruption significantly further ahead in time, potentially giving forecasters 24-hour advance warning to protect their systems. The model uses NASA's Solar Dynamics Observatory data and has been tested on eight different CMEs with promising results.
Researchers from Boston University, University of Michigan, and Chinese Academy of Sciences develop comprehensive solar wind models. The CISM, CSEM, and SIGMA groups create high-performance coupled models to simulate the complex behavior of solar winds and their impact on Earth's environment.
Researchers found that smoke from spring fires in Central America intensified conditions leading to severe tornadoes in the US. The study's results suggest a novel mechanism by which smoke affects tornado severity, and highlight the importance of considering atmospheric particles in weather prediction models.
A Tel Aviv University study prioritizes reasons for forecast failures across different regions, identifying man-made and natural factors such as land-use changes, topography, particles in the atmosphere, and population density. The researchers found unique factors affecting forecasts in various regions, including Europe, North Africa, ...
A new GPS system on commercial aircraft captures detailed meteorological readings to improve weather models and hurricane forecasts. This technology has the potential to save lives and provide more accurate predictions.
Yiqi Luo, a University of Oklahoma professor, has been named an AAAS Fellow for his work on data assimilation and ecological forecasting. His research aims to predict ecosystem changes in response to environmental shifts, which could inform global responses to climate change.
A new radar network offering higher resolution data and earlier warning of severe weather has been installed in the Dallas-Fort Worth metroplex. The system provides finer resolution and improved data on rainfall amounts, wind shear, and tornado signatures within storms.
UI researchers assessed global numerical weather prediction models' performance in predicting severe flooding in Boulder, Colo. in September 2013. The study found that while models generally performed well, there is room for improvement in capturing persistent rainfall and accurately forecasting flood events.
Researchers create a new computer model that combines cutting-edge simulations of weather and fire with satellite observations to predict the extent and behavior of wildfires. The technique, called CAWFE, allows for updated forecasts every 12 hours, enabling accurate predictions throughout a fire's lifetime.
Researchers at NCAR and University of Maryland create a new model that combines weather simulations with satellite observations to predict wildfire growth. The model can produce accurate forecasts every 12 hours, improving prediction tools for large, intense wildfires.
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.