Researchers at Northumbria University in the UK have been awarded £4m (US$5.4m) to investigate the behavior of Earth’s radiation belts, with the aim of improving space weather forecasting and satellite protection.

The five-year project, funded by the Science and Technology Facilities Council (STFC), will examine why radiation belts can change rapidly and remain difficult to predict.

Radiation belts are regions around Earth where charged particles are trapped by the planet’s magnetic field. Their intensity and size can vary dramatically over just hours or days due to solar activity, but scientists currently cannot predict their behavior.

The project will be led by Clare Watt, professor of space physics at Northumbria University, and will combine spacecraft data from international missions with advanced computer modeling to better understand how energy moves through Earth’s magnetosphere.

Continue reading Northumbria University secures £4m to study Earth’s radiation belts at Meteorological Technology International.

Researchers at the USC Viterbi School of Engineering have developed an artificial intelligence model capable of predicting wildfire spread in near real time by combining satellite data, terrain information and fire simulations.

The system builds on earlier work led by Assad Oberai, Hughes Professor of Aerospace and Mechanical Engineering, and the Computation and Data Driven Discovery (CD3) group. The updated model integrates multiple satellite data sources to improve accuracy and reduce uncertainty in forecasting fire behavior.

The research follows growing concern over increasingly intense wildfires, particularly in regions such as Southern California, where large-scale events have caused widespread damage in recent years.

Continue reading AI model improves real-time prediction of wildfire spread at Meteorological Technology International.

New research from Virginia Tech has identified an atmospheric shift that can rapidly trigger “flash droughts” in Puerto Rico, offering insight that could support earlier warning systems and preparedness.

The study, published in Geophysical Research Letters, examines how drought conditions on the island can develop within days rather than weeks or months.

Flash drought can take hold in as little as five to 10 days, leaving limited time for response. This can disrupt agriculture, water supplies and ecosystems, increasing the risk of crop losses and water shortages.

Researchers identified a key change in atmospheric behavior as the trigger.

Continue reading Study identifies atmospheric trigger behind flash droughts in Puerto Rico at Meteorological Technology International.

Researchers have developed a new deep learning-based method to measure ocean surface currents using data from existing weather satellites, offering higher-resolution insights into interactions between the ocean and atmosphere.

The approach, known as GOFlow (Geostationary Ocean Flow), analyzes thermal imagery from geostationary weather satellites to track how ocean surface temperature patterns evolve over time. By applying artificial intelligence, the system can infer the movement of underlying currents at a much finer temporal and spatial scale than traditional methods.

The study, published in Nature Geoscience, was led by scientists from the UC San Diego Scripps Institution of Oceanography and collaborating institutions.

Continue reading AI tool uses weather satellite data to map ocean currents in near real time at Meteorological Technology International.

A new open-access tool designed to assess the accuracy of climate models has been launched by an international team of researchers, significantly reducing the time required for evaluation.

The Rapid Evaluation Framework (REF) was developed by scientists involved in the Coupled Model Intercomparison Project (CMIP), a global initiative that supports the development and comparison of climate models used in major assessments, including those by the Intergovernmental Panel on Climate Change (IPCC).

Climate models simulate interactions between the atmosphere, oceans and land surface to help scientists understand past climate trends and project future changes. Evaluating how well these models reflect real-world conditions has traditionally been a time-consuming process, often taking months.

Continue reading New tool speeds up climate model evaluation at Meteorological Technology International.

Xiong’an National Climate Observatory was officially inaugurated on April 1 in Xiong’an New Area, Hebei. The facility – China’s 27th national climate observatory – will transmit basic meteorological observation data in real time to the TianQing meteorological big data cloud platform, supporting climate monitoring and assessment, high-resolution forecasting, early warning and sector-specific meteorological services.

National climate observatories in China are ground-based, comprehensive stations designed for long-term, continuous and integrated observation of the climate system and its interactions. They also serve as platforms for scientific research, collaboration and talent development.

The new observatory is expected to support regional priorities in Xiong’an, including ecological protection of Baiyangdian Lake, urban safety operations and the development of emerging sectors such as the low-altitude economy, all of which require higher-precision and continuous climate observations.

Continue reading China inaugurates 27th national climate observatory in Hebei at Meteorological Technology International.

What a negative Arctic oscillation revealed about forecasting winter storms, and why local observations matter

With powerful winter storms, it’s easy to focus on what’s happening at the surface: snowfall totals, wind chills and travel impacts. But the real story often begins thousands of miles away, high in the atmosphere, long before the first flakes ever fall.

In March 2026, a major winter storm swept across the Midwest USA, and it didn’t start with snow or wind. It started with a subtle shift far to the north, where the atmosphere over the Arctic began to lose its usual structure and stability, setting off a chain reaction that would eventually reshape weather across much of the USA.

Continue reading FEATURE: How the Arctic oscillation fueled widespread winter storms at Meteorological Technology International.

The Mauna Loa Solar Observatory (MLSO) in Hawaii has resumed full operations more than three years after a volcanic eruption cut off road access to the site.

Operated by the US National Science Foundation National Center for Atmospheric Research (NSF NCAR), the observatory had been largely inaccessible since Mauna Loa erupted in November 2022, blocking the main access route with lava flows.

With the road now rebuilt, MLSO is returning to normal operations, including daily on-site staffing, and is set to support NASA’s Artemis II mission by providing early warnings of hazardous space weather.

The observatory, established in 1965 on the slopes of Mauna Loa, is positioned to deliver high-altitude solar observations with minimal atmospheric interference.

Continue reading Mauna Loa Solar Observatory reopens to support Artemis II mission at Meteorological Technology International.

NASA is trialling a high-resolution weather modeling system from Meteomatics to improve forecasting for launch and facility operations at the Wallops Flight Facility.

Range meteorologists at Wallops are using Meteomatics’ US1k weather model alongside its MetX forecasting platform to gain more detailed insight into local weather conditions that can affect launch activities and site safety.

According to Meteomatics, the US1k model offers a resolution nine times higher than other commonly used weather models, enabling more precise analysis of localized weather phenomena. The data is integrated into the MetX platform, where it is presented through customizable visualizations to support decision-making.

Continue reading NASA tests high-resolution weather model for launch operations at Meteorological Technology International.

A regional training initiative is underway to strengthen flood forecasting capabilities in Central Africa, where floods are becoming more frequent and severe.

The World Meteorological Organization (WMO), in collaboration with the AGRHYMET Regional Center and the Swedish Meteorological and Hydrological Institute (SMHI), is supporting the development of the FANFAR river flood forecasting system across the region.

FANFAR provides forecasts of river flood risk up to 10 days in advance, using hydrological modeling of major river basins alongside meteorological data.

The initiative follows significant flooding events in 2024, when floods in Chad and the Democratic Republic of Congo affected 1.9 million and 1.2 million people respectively, according to OCHA.

Continue reading Regional training aims to improve flood forecasting in Central Africa at Meteorological Technology International.