Articles tagged with Weather Forecasting
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Researchers used a weather model to pinpoint the source of wintertime precipitation in Arizona, finding it comes from a central Pacific moisture source rather than El Niño/La Niña events. The study's findings could improve seasonal precipitation forecasts for the region and potentially other areas globally.
Researchers analyzed a 17-minute film of the eruption to understand how the ash cloud grew upwards and outwards. They calculated the eruption rate, which determines ash cloud extent, and found that it dropped by about half during the eruption.
Texas A&M University researchers have developed a 3D visualization technology to identify potential outcomes of hurricane flooding before it occurs. This allows for improved safety and reduced damage costs. The technology can also model specific buildings, accounting for basements, back entrances, and windows.
A team of researchers found that air turbulence in the thermosphere exhibits the same physical laws as wind in the lower atmosphere, leading to a new unified principle for Earth's environmental systems. This discovery can potentially improve future forecasting of both Earth and space weather.
Researchers have discovered that the sun's magnetic field is generated about 20,000 miles below its surface, contradicting previous theories. This finding helps scientists better understand the sun's dynamic processes and could lead to more accurate forecasts of powerful solar storms.
Climate change is driving sudden onset of drying in South America and southern Africa, while Central Asia sees increased moisture due to warming temperatures
The University of Washington's STRIVE project aims to understand the troposphere and stratosphere, where the ozone layer resides, and their interface. This will help monitor changes in the ozone layer, air quality, and climate processes.
Researchers developed an impact-based forecasting system that combines various models to predict flood impacts with high resolution. The system enables early warnings for evacuation, reducing population and property damage.
A recent study by University of Nebraska-Lincoln professor Cory Armstrong found that roughly 50% of those surveyed in the mid-south region couldn't accurately define a tornado warning. Meanwhile, 35% correctly identified a warning as a tornado being sighted or indicated on weather radar.
A new model combines wildfire smoke forecasts and ground-based sensor data to help public health officials plan targeted interventions. The researchers found that urban and rural communities already burdened by pollution face higher air pollution levels during unexpected smoke events.
A new computer model uses improved artificial intelligence to predict snow and water availability more accurately, considering both time and space. This information can help farmers and water planners make better decisions about water allocation.
Researchers found that modern weather models can accurately predict satellite movements affected by weather events like tropical cyclones with tall clouds. This understanding enhances satellite tracking and control, improving efficiency and reliability of satellite operations.
Climate scientists predict a 7 in 10 chance of record-breaking temperatures and humidity in the tropics, threatening humanitarian aid and medical care. El Niño's impact on tropical heat and humidity is expected to compound the effects of global warming, leading to extreme humid heat stress.
According to GIST researchers, extreme cold events (WACC) have intensified until the 2020s but are expected to decline post-2030s. This drastic shift in WACC trajectory has significant implications for global climate systems and weather patterns.
A team of over 100 scientists from Brazil and the US ran high-resolution simulations of South America's past and future climate using a weather research and forecasting model. The goal is to better understand hydroclimatic processes and inform adaptation measures for millions affected by climate change.
A new decision support system will utilize existing technology to project scenario-based outcomes for producer operations based on possible fluctuations within factors such as continuing drought or changes in input costs. The tool aims to help farmers consider economic, environmental, and production challenges together in one place.
A study from Colorado State University explores how human activity is altering the atmospheric water cycle, leading to changes in precipitation distribution and cloud formation. The research uses science fiction narratives to imagine possible futures and spark conversations around water management policies.
The UK's 2022 drought, the worst since 1976, emphasized the importance of early mitigation measures due to its rapid onset and extensive impacts on water resources, wildlife, and people. Improved monitoring and forecasting systems can help prevent similar extreme weather events in the future.
The University of Leeds says Africa needs significant investment in scientific infrastructure and science careers to adapt to climate change. Gaps in understanding the science behind tropical weather systems hinder African weather forecasting, leaving half the population without early warnings.
A new MIT-derived algorithm corrects coarse climate model predictions by 'nudging' them toward more realistic patterns, leading to more accurate forecasts of extreme weather events. The approach uses machine learning and dynamical systems theory to improve the resolution of large-scale climate models.
A new measure called “outdoor days” describes the number of days per year that outdoor temperatures are neither too hot nor too cold for people to go about normal outdoor activities. This measure reveals significant global disparities, with the North gaining more outdoor days and the South losing them due to rising temperatures.
A Penn State technique combining satellite data with existing computer weather forecast models produces more accurate forecasts of surface gusts in severe thunderstorms. This method can be especially useful in areas lacking ground-based weather monitoring infrastructure, such as radar systems.
A new study finds that extreme tropical cyclone rainfall is increasing across the continental US, while climate warming restricts 'outdoor days' for people living in developing countries. Additionally, air pollution increases mortality risks from heat, especially when combined with other factors like wildfires and reduced aerosols.
Virginia Tech researchers have received a five-year National Science Foundation grant to develop an open-source automated forecasting system for lakes. The system will enable real-time data collection and publishing, allowing researchers to predict water quality in lakes around the globe.
Researchers found that land-atmosphere coupling has a significant impact on Asian monsoons, but its effect varies greatly from year to year. The study suggests that better modeling of land conditions may be crucial for improving seasonal forecasts in the region.
Researchers have developed a non-crossing quantile regression neural network (NCQRNN) model to enhance the statistical reliability of weather forecasts. The NCQRNN model preserves the rank order of output nodes, ensuring lower quantiles stay smaller than higher ones, boosting accuracy and improving forecast interpretability.
A new study reveals that increased meltwater in the North Atlantic can trigger hotter and drier European summers. The study suggests a predictable chain of events leading to European summer weather, due to higher levels of freshwater in the North Atlantic.
Researchers found no clear link between weather conditions and muscle and joint pain, debunking a long-standing medical myth. High temperatures, low humidity, and dehydration may increase the risk of gout flares.
A recent study published in npj Climate and Atmospheric Science reveals that changes in subtropical and midlatitude eddy activity control the variation of the Hadley cell edge latitude. The researchers analyzed 41 years of data and found associations with El Niño, La Niña, and the Arctic oscillation.
A study reveals that consecutive atmospheric river events lead to significantly higher economic losses in California, tripling expected damages compared to standalone events. This is crucial for emergency and water managers balancing flood risks with water shortage needs.
Researchers found that compact, faster-moving storms are more susceptible to global warming's effects, while larger, slower-moving typhoons are more resilient. This discovery could lead to improved methods for projecting typhoon strength under warming conditions.
A new compound flooding model predicts that New York City will experience historic and devastating floods every 30 years by the end of this century, a fivefold increase from the present climate. The tool helps city planners prepare and protect against future disasters by providing detailed flood forecasts.
A research team developed novel graph neural network models that improve precipitation forecasting skills by coupling physical variables, revealing a significant improvement over traditional numerical models. The models demonstrated superior consistency and forecasting skills, especially for heavy rainfall events.
A recent study from the University of Georgia found that over 70% of respondents with chronic pain would alter their daily plans based on weather-based pain forecasts. The study suggests that developing a reliable pain-based weather forecast could help individuals take preventative measures to manage their pain levels.
The Caatinga's ecosystem is projected to lose up to 87% of its mammal species and 70% of plant assemblages due to climate change. This will result in a loss of ecological functions, such as seed dispersal, and make the ecosystem less resilient.
Researchers developed a new framework to understand small-scale turbulent flows, shedding light on the chaotic butterfly effect. The framework uses chaos theory and synchronization theory to explain the critical length scale, which affects data assimilation methods.
A new study improves thunderstorm forecasting by utilizing Geostationary Operational Environmental Satellite (GOES-R) lightning flash observations. The implementation of the EnVAR assimilation capabilities successfully enhances the forecasting performance, especially over regions lacking operational weather radar observations.
Native Americans in Oklahoma have approximately five times increased risk of heavy rainfall, with two-year floods projected to be 632.6% higher than the general population. The study aims to help Native American leaders develop disaster risk reduction plans and protect vulnerable communities.
Researchers found that the coastline produces up to five times more giant sea salt aerosols than the open ocean, affecting cloud formation and rainfall around the Hawaiian Islands. The study's findings can improve numerical weather prediction of nearshore cloud formation and rainfall patterns.
A research team developed a multi-model projection system using the self-calibrating Effective Drought Index to predict drought and recommend cumulative precipitation for recovery. The required rainfall for drought recovery was estimated at 170 mm, 310 mm, and 440 mm for March, April, and May respectively.
Researchers found that green spaces alleviate extreme heat's negative impacts on human health, while densely packed buildings increase mortality risk. Urban design strategies incorporating different types of greenery are recommended to mitigate heatwave-associated mortality.
A new hybrid method developed by Concordia researchers combines data from Weibull probability distribution and numerical weather prediction models to improve wind speed forecasting accuracy. This innovation has the potential to significantly enhance urban power generation, particularly in areas with high variability in wind speeds.
New research identifies two modes of rapid intensification, one linked to favorable environmental conditions and warm surface waters, the other triggered by major bursts of thunderstorms far from the storm's center. These findings may lead to better understanding and prediction of catastrophic hurricanes.
A University of Oklahoma-led study highlights newly measured extremes in stratospheric water vapor recorded during the DCOTSS field project. High-level thunderstorms enhance water vapor in the stratosphere at levels higher than previously understood.
Researchers developed a climate network analysis method to explore teleconnections, which describe how climate events in one part affect others worldwide. The study found areas like southeastern Australia and South Africa are significantly affected by these interconnected events, with stronger connections over time.
A mathematical breakthrough provides new insights into typhoon dynamics, enabling more accurate predictions and advancements in weather forecasting. The study confirms the stability of specific vortex structures, which can be encountered in real-world fluid flows.
A research team led by Yongjie Huang is exploring the complex interactions between convective clouds and their surrounding environments. They aim to understand how convection initiates and how convective cells interact with their environment, ultimately improving computer models for forecasting.
Researchers found that fall snow levels are a good predictor of total snowpack in some western states, particularly in northern regions like Alaska, Oregon, and Washington. This prediction works due to cooler air temperatures and weather patterns that help retain snow on the ground, adding to the total snowpack.
Researchers at the University of Melbourne have developed a new simulation model that can predict flooding during an ongoing disaster more quickly and accurately. The Low-Fidelity, Spatial Analysis and Gaussian Process Learning (LSG) model can produce predictions as accurate as advanced models but at speeds 1000 times faster.
A global network of radiation sensors measured incoming sunlight at 60 locations in Oklahoma, providing important climate data for efficient use of weather satellites and photovoltaic systems. The campaign complements previous data sets and aims to improve short-term forecasts of sunlight for renewable energy.
Researchers at Stevens Institute of Technology have developed more accurate nowcasting algorithms to predict short-term weather forecasts. The study found that probabilistic models are highly accurate in predicting both long- and short-term rainfall events, while deterministic models are better suited for extremely short-term projections.
A new climate modeling method called ensemble boosting can simulate a large set of extreme but plausible heat waves, providing a worst-case scenario for planning and preparation. This method helps prepare for the potential loss of tens of thousands of lives in extreme heat waves.
The University of Cambridge team warns that Africa's lack of hydromet infrastructure will lead to a surge in climate-related disasters and deaths. The continent has just 6% of the number of radar stations as Europe and North America, making it vulnerable to floods, droughts, and heatwaves.
A research group from Nagoya University simulated clear air turbulence using Japan's fastest supercomputer. They found that wind speed disturbances occur due to the collapse of Kelvin-Helmholtz instability waves, creating turbulence in the absence of visible clouds or other atmospheric disturbances.
Scientists at Max Planck Institute for Dynamics and Self-Organization have challenged long-held assumptions about turbulent flows, finding deviations from established scaling laws in highly idealized environments. This discovery has implications for understanding turbulence in engineered flows, weather forecasts, and climate models.
Researchers have identified an operational strategy that can reduce shipping emissions by up to a quarter by combining modern sail technology with efficient routing systems. The study found that this approach can provide greater assurances of carbon savings by mitigating the impact of unpredictable weather patterns.
A new computer model forecasts yield for four key crops in the southeastern US, drawing on climate, groundwater, and agricultural data. The tool helps farmers and water resource managers identify ways to maximize crop yields while efficiently utilizing water and energy.
The UK is investing £11 million to improve forecast accuracy for extreme weather events like storms, floods and droughts. Scientists are focusing on atmospheric turbulence to create more detailed models.
Scientists at Rice University found a natural 150-day cycle in the north-south oscillation of atmospheric pressure patterns, influencing hemispheric-scale precipitation and ocean surface wind stress. This discovery challenges conventional wisdom about atmospheric organization and has implications for climate modeling.
A new study from Tufts University predicts a significant increase in extreme temperatures affecting wheat yields in the US and China. The research warns of potentially disastrous consequences for global food supplies if crops are impacted by heat stress, which can occur at temperatures above 27.8°C.