Newswise — UPTON, N.Y. — Mike Jensen, a meteorologist and interim chair of the Environmental Science and Technologies Department at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory, is a recipient of the DOE Distinguished Mentor Award for Workforce Development, a new award program that recognizes outstanding mentors from across DOE’s 17 national laboratories and their essential roles in developing STEM professionals.

Jensen is one of four mentors honored by DOE’s Office of Science for their excellence in guiding future scientists, engineers, and technical professionals through unique access to world-leading expertise, scientific user facilities, and research tools found at multidisciplinary national laboratories.

“The establishment of the DOE Distinguished Mentor Award for Workforce Development directly aligns with our strategic objectives to not only recognize exceptional mentorship but also to actively cultivate best practices across our National Laboratories,” said DOE Under Secretary for Science Darío Gil. “By illuminating these exemplary efforts, we reinforce a vibrant mentoring ecosystem crucial for advancing the DOE’s mission and strengthening the U.S. workforce. We look forward to celebrating our inaugural awardees and hearing their insights and experiences.”  

The mentors will be celebrated at a virtual ceremony later this year. Each awardee will receive $10,000 to be used for research and mentoring-related development.

Over the years, Jensen has mentored dozens of students — from high schoolers to graduate-level researchers — through programs supported by DOE’s Office of Science and Brookhaven Lab. His mentees have participated in DOE programs such as Science Undergraduate Laboratory Internships (SULI), Office of Science Graduate Student Research, the Workforce Development for Teachers and Scientists Pathway Summer Schools, and various Brookhaven pre-college offerings such as the High School Research Program (HSRP).

“I’m honored and humbled to be awarded,” said Jensen, who leads his department’s Cloud Processes and Measurement Group and is a principal investigator for the Atmospheric System Research (ASR) program’s Process-level AdvancementS of Coupled Cloud and Aerosol LifecycleS (PASCCALS) Science Focus Area and an active participant with the Atmospheric Radiation Measurement (ARM) User Facility, a multi-laboratory, DOE scientific user facility. “I consider mentorship an important part of my job as a scientist to help with the next generation, and I enjoy that part. It’s nice to be rewarded for something that I like doing.”

In his scientific work, Jensen collects data in the field to analyze and better understand the processes that drive the evolution of cloud systems and their role in the water cycle and the Earth’s energy balance. In field campaigns such as the TRacking Aerosol Convection interactions ExpeRiment, he and the ARM facility team deploy advanced atmospheric instruments to measure cloud structure, precipitation, and radiation.

Through Jensen’s mentorship, students see what atmospheric science looks like in practice. They learn about tools used in the field, such as radars and weather balloons, analyze datasets using coding and visualization tools like Python, and participate in exciting moments when new insights emerge from their data.

Jensen’s mentorship goes beyond helping students leave internships with new skills in data science and experimental analysis, said Aleida Pérez, manager of Brookhaven’s Office of Workforce Development and Science Education.

“He makes sure students are engaged with the broader network of atmospheric science researchers, helping them understand the impact of the research they collaborate on and see themselves as part of the research community,” Pérez said.

Jensen said he and his colleagues encourage students to embrace trial-and-error, whether they’re trying out ideas for experiments or exploring career pathways.

“We talk to them a lot about not being fearful of the research they’re doing and to go ahead and try new things,” Jensen said.

Those who nominated Jensen for the DOE award cited his accessibility, patience, and ability to instill confidence in aspiring scientists.

“To say that Mike had an impact on my life and career would be a severe understatement,” said Diana Apoznanski, a mentee of Jensen’s through HSRP and SULI. “Mike molded a timid high school student who had an interest in weather into a confident Ph.D. candidate studying Earth system modeling and impacts, and he has consistently and enthusiastically supported my career for an entire decade.”

Apoznanski is now pursuing a Ph.D. in atmospheric science at Rutgers University.

Jensen has also served as a mentor to new mentors, inspiring early-career researchers in his department to step into mentoring roles, Pérez said.

“He has supported his colleagues by serving as a co-mentor, providing guidance, and sharing what he has learned from collaborating with many students who have continued in STEM fields,” Pérez said.

Brookhaven National Laboratory is supported by the Office of Science of the U.S. Department of Energy. The Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit science.energy.gov.

Follow @BrookhavenLab on social media. Find us on Instagram, LinkedIn, X, and Facebook.

Newswise — The marginal ice zone marks the boundary between open ocean and sea-ice cover and represents one of the most dynamic environments in polar oceans. Ocean eddies generated near ice edges influence sea-ice transport, mixing processes, and energy exchange between the ocean and atmosphere. These rotating structures can redistribute floating sea ice, modify heat transport, and affect regional ecosystems and climate feedback mechanisms. However, direct observations of eddy evolution remain limited because of harsh polar conditions and sparse in-situ measurements. Satellite synthetic aperture radar (SAR) has become an important tool for detecting eddies through sea-ice patterns, yet most previous studies mainly analyzed spatial distributions rather than the dynamic evolution of individual eddies. Because of these challenges, deeper investigation of the spatiotemporal evolution of ice-edge eddies is required.

Researchers from the Aerospace Information Research Institute of the Chinese Academy of Sciences reported a new framework for analyzing the evolution of ice-edge eddies using sequential SAR satellite imagery. Their findings were published (DOI: 10.34133/remotesensing.1031) on March 2, 2026, in the journal Journal of Remote Sensing. The study focuses on an eddy observed in the Fram Strait, a key passage connecting the Arctic Ocean and the North Atlantic. By integrating sea-ice motion tracking with hydrodynamic vortex modeling, the researchers quantified key physical characteristics of the eddy, including rotational velocity, circulation strength, and radius, providing new insight into polar ocean dynamics.

The study introduces a dynamical parameter inversion framework capable of reconstructing the structure and temporal evolution of ice-edge eddies. Using sequential SAR images, the researchers tracked the displacement of floating sea ice to derive high-resolution surface current fields. These currents were then analyzed using a vortex-based hydrodynamic model to estimate key parameters such as suction intensity, angular velocity, and circulation strength.

Applying the framework to an Arctic eddy revealed a complete life cycle lasting about 22 days. During the early stage, the eddy gradually intensified as both its radius and circulation strength increased. The vortex reached a mature phase when its structure became most coherent and energetic. Afterward, the eddy weakened and gradually dissipated. The results demonstrate how polar ocean eddies evolve dynamically and provide quantitative evidence of their growth, maturity, and decay processes. The research focused on the Fram Strait, where complex interactions between the southward-flowing East Greenland Current and the northward-flowing West Svalbard Current frequently generate ocean eddies. Researchers analyzed time-series SAR images collected by the Sentinel-1A and Sentinel-1B satellites, which provide high-resolution radar observations capable of monitoring sea-ice patterns regardless of cloud cover or lighting conditions. To reconstruct eddy dynamics, the team first tracked the displacement of floating sea ice between consecutive SAR images separated by roughly 50 minutes, allowing them to retrieve the horizontal surface current field associated with the eddy. The retrieved currents were then processed using singular value decomposition to isolate the dominant rotational component while suppressing background currents and noise.

Next, the Burgers–Rott vortex model—derived from the Navier–Stokes equations—was applied to invert the dynamical parameters describing the eddy. Analysis showed that the eddy radius expanded from roughly 28 km to over 35 km, while circulation strength peaked at about 4.5 × 10⁴ m²/s. The reconstructed current fields closely matched satellite-derived observations, confirming the reliability of the proposed method for capturing real ocean dynamics.

The researchers emphasized that ice-edge eddies are crucial components of polar ocean circulation. “These eddies strongly influence sea-ice redistribution and ocean mixing in Arctic waters,” the team explained. By enabling continuous monitoring of eddy evolution using satellite radar imagery, the new framework provides a valuable observational tool for studying ocean–ice interactions and improving understanding of polar climate dynamics.

The framework integrates satellite remote sensing with physical modeling techniques. Sequential SAR images were first preprocessed through radiometric calibration, filtering, and image registration. The displacement of floating sea ice between image pairs was calculated using a maximum cross-correlation method to retrieve horizontal current vectors. Singular value decomposition was then applied to isolate the dominant eddy structure from the current field. Finally, a Burgers–Rott vortex model combined with a Levenberg–Marquardt optimization algorithm was used to invert the eddy’s key dynamical parameters, enabling quantitative analysis of its evolution.

The proposed approach opens new opportunities for monitoring ocean dynamics in polar environments using satellite observations. As high-resolution SAR datasets continue to expand, researchers will be able to track multiple eddies simultaneously and analyze their interactions with sea ice, ocean currents, and atmospheric forcing. Such insights could improve numerical models of Arctic circulation and enhance understanding of how polar oceans respond to climate change. In the future, combining satellite observations with oceanographic models and in-situ measurements may provide a more comprehensive picture of Arctic marine processes and their global impacts.

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References

DOI

10.34133/remotesensing.1031

Original Souce URL

https://doi.org/10.34133/remotesensing.1031

Funding information

This work was supported by the National Natural Science Foundation of China (grant number 62231024).

About Journal of Remote Sensing

The Journal of Remote Sensing, an online-only Open Access journal published in association with AIR-CAS, promotes the theory, science, and technology of remote sensing, as well as interdisciplinary research within earth and information science.

Newswise — For decades, global soil moisture monitoring from space has depended on reference datasets. Satellite observations, while indispensable, are rarely used alone; instead, their retrieval algorithms are typically calibrated or constrained using external soil moisture products derived from other satellites, models, or reanalysis systems. This practice has helped stabilize retrievals, but it has also introduced fundamental limitations—reducing transparency, constraining transferability across regions, and complicating long-term consistency as reference products evolve. A growing question in Earth observation is whether this dependence is truly unavoidable.

In a study published (DOI: 10.34133/remotesensing.0939) on January 7, 2026, in the Journal of Remote Sensing, researchers from the Chinese Academy of Sciences, Peking University, and the China Meteorological Administration present PHYsics-based Soil rEflectivity Retrieval (PHYSER)—a physics-based framework for spaceborne GNSS-R soil moisture retrieval. The study demonstrates that global soil moisture can be retrieved independently, without relying on any external soil moisture referenSatellite Observationce products.

A long-standing constraint in satellite soil moisture retrieval

Soil moisture governs the exchange of water, energy, and carbon between the land surface and the atmosphere, influencing droughts, floods, ecosystem functioning, and agricultural productivity. Satellite remote sensing has become essential for monitoring soil moisture at regional to global scales, yet existing approaches face persistent challenges.

Conventional microwave sensors provide physically meaningful measurements but often struggle to balance spatial resolution, temporal coverage, and mission cost. More recently, Global Navigation Satellite System Reflectometry (GNSS-R) has emerged as a promising alternative. By passively receiving L-band signals continuously transmitted by navigation satellites such as GPS and BeiDou, GNSS-R offers low power consumption, all-weather capability, and dense spatiotemporal sampling.

Despite these advantages, most GNSS-R soil moisture retrieval methods still rely on empirical or semi-empirical relationships calibrated against external soil moisture products. This reliance weakens the physical interpretability of the results and limits their robustness when applied across regions, time periods, or future satellite missions. As GNSS-R constellations rapidly expand, the absence of an independent, physics-based retrieval framework has become a critical bottleneck.

Retrieving soil moisture from physical principles

PHYSER addresses this bottleneck by rethinking GNSS-R soil moisture retrieval from first principles. Rather than fitting GNSS-R observations to existing soil moisture datasets, the framework derives soil moisture directly from the physical interaction between navigation signals and the land surface.

At the core of PHYSER is the accurate reconstruction of soil surface reflectivity from GNSS-R measurements. This is achieved through a stepwise physical correction strategy. First, system-related biases inherent to the GNSS-R “multi-transmitter, single-receiver” observation geometry are corrected using inland water bodies as stable natural calibration targets. This step ensures consistency across different navigation signals and viewing geometries.

Second, land surface effects—particularly vegetation attenuation and surface roughness—are explicitly corrected using a physically based radiative transfer model. These land surface factors are shown to introduce larger uncertainties than satellite system errors, underscoring the importance of addressing them through physics-based correction rather than statistical adjustment.

With these corrections applied, soil reflectivity is transformed into soil permittivity using Fresnel equations. Soil moisture is then retrieved using established dielectric mixing models informed by global soil texture data.

Independent validation across space and ground observations

The PHYSER framework was evaluated using one year of observations from the BuFeng-1 A/B twin satellites, China’s first spaceborne GNSS-R mission designed for technology demonstration. The retrieved soil moisture fields were compared with SMAP satellite products, ERA5-Land reanalysis data, and hundreds of in situ measurement sites worldwide.

Across diverse climatic and land surface conditions, the PHYSER-based retrievals show strong spatial and temporal consistency with these independent datasets. While retrieval errors are comparable to—or only slightly higher than—those of empirical GNSS-R approaches, PHYSER achieves this performance while remaining fully independent of reference soil moisture products.

“This work shows that GNSS-R soil moisture retrieval does not have to be a statistical imitation of other products,” said a member of the research team. “By grounding the retrieval in physics, we gain transparency, robustness, and the ability to extend the method to future missions without retraining against external datasets.”

Implications for future Earth observation missions

As GNSS-R missions multiply and satellite constellations become denser, the need for scalable and physically interpretable retrieval methods is becoming increasingly urgent. PHYSER provides a pathway toward soil moisture monitoring that is not tied to any specific reference product or satellite mission.

The framework has the potential to strengthen climate reanalysis, improve hydrological forecasting, and support agricultural decision-making, particularly in data-sparse regions. With further refinement—especially in densely vegetated environments—PHYSER could help enable operational GNSS-R soil moisture products that complement, and potentially stand alongside, traditional microwave remote sensing systems.

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References

DOI

10.34133/remotesensing.0939

Original Source URL

https://spj.science.org/doi/10.34133/remotesensing.0939

Funding information

This study is supported by the Chinese Academy of Sciences, the Shandong Provincial Natural Science Foundation (Grant No. ZR2024QD048), the National Natural Science Foundation of China (NSFC) project (Grant No. 42471511), the BUFENG-1 Application Extension Program of the China Spacesat Co., Ltd., the ESA-MOST China Dragon5 Programme (ID.58070), the Fengyun Application Pioneering Project (FY-APP-2021.0301), the Beijing Nova Program (Grant Nos. 20230484327 and 20240484540), and the Hunan Provincial Natural Science Foundation project (Grant No. 2024JJ9186).

About Journal of Remote Sensing

The Journal of Remote Sensing, an online-only Open Access journal published in association with AIR-CAS, promotes the theory, science, and technology of remote sensing, as well as interdisciplinary research within earth and information science.

Newswise — As global demand for clothing continues to rise, the textile and apparel industry has become a significant contributor to climate change. In China, the world’s largest textile producer and exporter, rapid urbanization, income growth, and shifting consumption patterns have driven a surge in apparel demand. Traditional studies often focus on factory-level energy use, overlooking emissions embedded in supply chains, exports, and household consumption. This fragmented perspective limits the effectiveness of mitigation strategies. Moreover, fast fashion and short garment lifespans exacerbate resource use and waste. Based on these challenges, there is an urgent need to conduct in-depth research that captures the full carbon footprint of the textile industry and identifies scalable pathways for emission reduction.

Researchers from Nanjing University, in collaboration with international partners, reported (DOI: 10.1007/s11783-026-2109-9) on January 9, 2026, in Engineering Environment a comprehensive analysis of carbon emissions in China’s textile and apparel industry. Using national household consumption data and supply-chain input–output modeling, the team examined emission trends from 2000 to 2018 and projected future mitigation scenarios through 2035. Their study reveals how production, consumption, and exports jointly shape the sector’s carbon footprint and highlights practical strategies—particularly renewable energy and clothing recycling—to curb emissions while supporting sustainable industrial development.

The analysis shows that demand-side forces dominate carbon emissions in China’s textile industry. Household consumption and exports together account for roughly 85% of total emissions growth, far outweighing the contribution from direct energy use in factories. Urban households, in particular, generate more than four times the carbon emissions of rural households due to higher clothing consumption, underscoring the climate impact of lifestyle changes.

By constructing detailed carbon flow diagrams, the study identifies wet processing, electricity use, and long, fragmented supply chains as major emission hotspots. While electrification has reduced emissions from fossil fuels, carbon embodied in upstream sectors—such as chemicals, transportation, and logistics—continues to rise.

To explore mitigation pathways, the researchers modeled five future scenarios. Energy-saving technologies alone delivered limited reductions, while large-scale renewable energy adoption significantly lowered emissions by reducing carbon intensity across the entire supply chain. Clothing recycling emerged as another powerful lever, as extending garment lifespans directly reduces the need for new production. Most notably, a combined strategy integrating renewable energy and recycling could reduce total emissions by nearly 10% compared with a business-as-usual trajectory, effectively flattening long-term emission growth.

“This study shows that decarbonizing the textile industry is not just a technological challenge, but also a consumption challenge,” said the study’s corresponding author. “Focusing only on factories misses the bigger picture. Our results demonstrate that household demand, urban lifestyles, and export-oriented production play decisive roles in driving emissions. By aligning clean energy transitions with circular economy strategies—especially clothing recycling—we can achieve meaningful emission reductions without sacrificing economic vitality. These insights provide a scientific foundation for designing more effective and balanced climate policies.”

The findings have important implications for policymakers, industry leaders, and consumers. For governments, the study highlights the need to integrate demand-side measures—such as promoting clothing reuse and recycling—into climate strategies for the textile sector. For industry, it underscores the value of transitioning to renewable energy while redesigning supply chains to be shorter and more efficient. For consumers, the research quantifies how everyday clothing choices contribute to carbon emissions, reinforcing the climate benefits of longer garment lifespans. Together, these pathways suggest that a shift toward greener production and more responsible consumption can transform textiles from a climate liability into a key contributor to a low-carbon future.

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References

DOI

10.1007/s11783-026-2109-9

Original Source URL

https://doi.org/10.1007/s11783-026-2109-9

Funding information

The study was financially supported by the National Natural Science Foundation of China (Nos. 72304136, 72234003, and 72488101).

About Engineering Environment

Engineering Environment is the leading edge forum for peer-reviewed original submissions in English on all main branches of environmental disciplines. FESE welcomes original research papers, review articles, short communications, and views & comments. All the papers will be published within 6 months after they are submitted. The Editors-in-Chief are Academician Jiuhui Qu from Tsinghua University, and Prof. John C. Crittenden from Georgia Institute of Technology, USA. The journal has been indexed by almost all the authoritative databases such as SCI, EI, INSPEC, SCOPUS, CSCD, etc.

Newswise — Winter Storm Fern swept across a large swath of the southern and eastern United States, delivering not just a wide range of snow accumulation, but also snow types. Experts say one big reason for those differences comes from a meteorological phenomenon — that the same amount of total precipitation can deliver very different amounts of measurable snowfall, depending on the underlying conditions.

Barrett Gutter, a meteorologist at Virginia Tech who teaches classes in weather analysis, weather forecasting, and severe weather, explains that the snow-to-liquid ratio (SLR), or how much moisture is in a snowflake, can be impacted by a number of factors.

“Very dry snow, which often occurs in mountainous terrain and higher latitudes, can have SLR values closer to 20:1 (20″ of snow = 1″ of liquid), while very wet snow, which often occurs in the southeast, can have SLR values closer to 6:1,” he says.

This explains why snow totals in the Rocky Mountains are often much higher than along the east coast ranges. But elevation isn’t the only determining factor.

“Lower temperatures throughout the atmosphere will lead to drier and fluffier snow (higher SLR) since there tends to be less moisture available, while higher temperatures (closer to freezing) will lead to wetter and denser snow.”

Other factors that impact snow-to-liquid ratios include the height in which snowflakes form, moisture content, and wind speed.

This led to record snowfall totals in places like Toronto, which received nearly two feet of accumulation, while the mid-Atlantic got less total snow, but several inches of sleet, which settled into hard-packed ice.

About Gutter
Barrett Gutter is a collegiate assistant professor of meteorology. Gutter teaches a wide variety of courses, including Weather Analysis, Weather Forecasting, Severe Weather, and Radar and Satellite Meteorology. He also leads a two-week storm chase field course during the summer.

Interview
To schedule an interview with Barrett Gutter, contact Noah Frank at nafrank@vt.edu or 805-453-2556.

Newswise — ALBANY, N.Y. (Jan. 22, 2026) — A major winter storm is expected to bring dangerously low temperatures and heavy snow through the weekend across a nearly 2,000-mile stretch of the United States, from the southern Plains to the Northeast. 

The storm is expected to develop on Friday, creating a hazardous mix of heavy snow and ice that could cause power outages for millions of Americans and make roads impassable. 

Allison Finch, lead meteorologist at the University at Albany’s State Weather Risk Communication Center, is closely monitoring the storm. She says snow, freezing rain, sleet, gusty winds and dangerously cold temperatures are all among the hazards expected. 

“From Texas to the Mid-Atlantic states, this storm looks to bring snow and a widespread swath of ice,” Finch said. “Ice is a very impactful hazard to begin with, but when it occurs in areas that doesn’t typically experience it as often, impacts can be exacerbated. Among the impacts is the likelihood of power outages. Anyone who loses a heat source may be impacted since temperatures are not expected to rebound quickly after the storm.” 

Finch points to two main factors fueling the storm — cold air from Canada and moisture moving up from the Gulf of Mexico. 

“A powerful Arctic air mass is sweeping across the U.S. late this week and into next week, bringing temperatures well below average,” Finch said. “At the same time, a large plume of moisture originating from warm ocean waters is being drawn into that Arctic air. When that moisture gets wrapped into the cold air mass, it provides the fuel needed for a widespread and potentially high-impact winter storm.”  

Launched in 2023, the State Weather Risk Communication Center is a first-of-its-kind partnership between UAlbany and the New York State Division of Homeland Security and Emergency Services that leverages the University’s expertise in atmospheric sciences to help emergency managers prepare for and respond to severe weather events. 

The Center provides rapid, tailored, real-time weather information and custom weather services to New York state and local public-sector partners.  

Finch, along with other meteorologists at the State Weather Risk Communication Center, are available to share their insights on this weekend’s winter storm via phone or live/recorded interviews.    

For the latest conditions in New York, follow the NYS Mesonet, a statewide weather observation network operated by UAlbany, which provides real-time data from monitoring sites across the state. 

About the University at Albany:  

The University at Albany is one of the most diverse public research institutions in the nation and a national leader in educational equity and social mobility. As a Carnegie-classified R1 institution, UAlbany faculty and students are advancing our understanding of the world in fields such as artificial intelligence, atmospheric and environmental sciences, business, education, public health, social sciences, criminal justice, humanities, emergency preparedness, engineering, public administration, and social welfare. Our courses are taught by an accomplished roster of faculty experts with student success at the center of everything we do. Through our parallel commitments to academic excellence, scientific discovery and service to community, UAlbany molds bright, curious and engaged leaders and launches great careers.  

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Newswise — WASHINGTON, Feb. 3, 2026 — Arctic sea ice has large effects on the global climate. By cooling the planet, Arctic ice impacts ocean circulation, atmospheric patterns, and extreme weather conditions, even outside the Arctic region. However, climate change has led to its rapid decline, and being able to make real-time predictions of sea ice extent (SIE) — the area of water with a minimum concentration of sea ice — has become crucial for monitoring sea ice health.

In Chaos, by AIP Publishing, researchers from the United States and the United Kingdom reported accurate, real-time predictions of SIE in Arctic regions. Sea ice coverage is at its minimum in September, making the month a critical indicator of sea ice health and the primary target of the work.

“Indigenous Arctic communities depend on the hunting of species like polar bears, seals, and walruses, for which sea ice provides essential habitat,” said author Dimitri Kondrashov. “There are other economic activities, such as gas and oil drilling, fishing, and tourism, where advance knowledge of accurate ice conditions reduces risks and costs.”

The researchers’ approach treats sea ice evolution as a set of atmospheric and oceanic factors that oscillate at different rates — for example, climate memory at long timescales, annual seasonal cycles, and quickly changing weather — while still interacting with one another. They used the National Snow and Ice Data Center’s average daily SIE measurements from 1978 onward to find the relationships between these factors that affect sea ice.

Testing their prediction method live in September 2024, and retroactively for Septembers of past years, the group confirmed their technique is generally accurate and can capture effects from subseasonal to seasonal timescales. They predicted SIE ranging from one to four months out and found their predictions outperformed other models.

In general, long-term climate forecasts tend to be easier and more reliable than short-term predictions. However, by incorporating regional data into their model, the researchers were able to improve short-term ice and weather estimates.

“The model includes several large Arctic regions composing [the] pan-Arctic,” said Kondrashov. “Despite large differences in sea ice conditions from year to year in different regions, the model can pick it up reasonably accurately.”

The group plans to improve their model by including additional oceanic and atmospheric variables, such as air temperature and sea level pressure. These variables can cause fast changes and short-term fluctuations that are not currently reflected in the model, and the researchers hope these additions will further enhance the predictability of summertime Arctic sea ice.

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The article “Accurate and robust real-time prediction of September Arctic sea ice” is authored by Dimitri Kondrashov, Ivan Sudakow, Valerie N. Livina, and QingPing Yang. It will appear in Chaos on Feb. 3, 2026 (DOI: 10.1063/5.0295634). After that date, it can be accessed at https://doi.org/10.1063/5.0295634.

ABOUT THE JOURNAL

Chaos is devoted to increasing the understanding of nonlinear phenomena in all areas of science and engineering and describing their manifestations in a manner comprehensible to researchers from a broad spectrum of disciplines. See https://pubs.aip.org/aip/cha.

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