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Accurate simulation of sea ice is critical for predictions of future Arctic sea ice loss, looming climate change impacts, and more. A key feature in Arctic sea ice is the formation of melt ponds. Each year melt ponds develop on the surface…

Computational Physics · Physics 2023-04-13 Simon Driscoll , Alberto Carrassi , Julien Brajard , Laurent Bertino , Marc Bocquet , Einar Olason

Arctic Sea Ice Concentration (SIC) is the ratio of ice-covered area to the total sea area of the Arctic Ocean, which is a key indicator for maritime activities. Nowadays, we often use passive microwave images to display SIC, but it has low…

Image and Video Processing · Electrical Eng. & Systems 2024-06-04 Zhaomin Fang , Wankun Chen , Feng Gao , Yanhai Gan , Junyu Dong , Yang Zhou

In this work, the seasonal predictive capabilities of Neural Radiance Fields (NeRF) applied to satellite images are investigated. Focusing on the utilization of satellite data, the study explores how Sat-NeRF, a novel approach in computer…

Computer Vision and Pattern Recognition · Computer Science 2024-11-06 Liv Kåreborn , Erica Ingerstad , Amanda Berg , Justus Karlsson , Leif Haglund

Our ability to predict the future of Arctic sea ice is limited by ice's sensitivity to detailed surface conditions such as the distribution of snow and melt ponds. Snow on top of the ice decreases ice's thermal conductivity, increases its…

Pattern Formation and Solitons · Physics 2022-03-09 Predrag Popović , Justin Finkel , Mary C. Silber , Dorian S. Abbot

Arctic amplification has altered the climate patterns both regionally and globally, resulting in more frequent and more intense extreme weather events in the past few decades. The essential part of Arctic amplification is the unprecedented…

Atmospheric and Oceanic Physics · Physics 2023-08-10 Sahara Ali , Jianwu Wang

Dark deposits visible from orbit appear in the Martian south polar region during the springtime. These are thought to form from explosive jets of carbon dioxide gas breaking through the thawing seasonal ice cap, carrying dust and dirt which…

Earth and Planetary Astrophysics · Physics 2022-11-30 Mark D. McDonnell , Eriita Jones , Megan E. Schwamb , K-Michael Aye , Ganna Portyankina , Candice J. Hansen

Monitoring the fuel moisture content (FMC) of vegetation is crucial for managing and mitigating the impact of wildland fires. The combination of in situ FMC observations with numerical weather prediction (NWP) models and satellite…

Climate change, amplified in the far north, has led to rapid sea ice decline in recent years. In the summer, melt ponds form on the surface of Arctic sea ice, significantly lowering the ice reflectivity (albedo) and thereby accelerating ice…

Pattern Formation and Solitons · Physics 2018-04-16 Predrag Popović , B. B. Cael , Mary Silber , Dorian S. Abbot

The weather phenomenon of frost poses great threats to agriculture. As recent frost prediction methods are based on on-site historical data and sensors, extra development and deployment time are required for data collection in any new site.…

Machine Learning · Computer Science 2023-05-16 Ian Zhou , Justin Lipman , Mehran Abolhasan , Negin Shariati

With a growing demand for high-quality fabrication, the interest in real-time process and defect monitoring of laser powder bed fusion (LPBF) has increased, leading manufacturers to incorporate a variety of online sensing methods including…

During the summer melt period, ponds form on the surface of Arctic sea ice as it melts, with important consequences for ice evolution and marine ecology. Due to the ice-albedo feedback, these melt ponds experience uneven heat absorption,…

Data Analysis, Statistics and Probability · Physics 2022-12-16 Wilfred Offord , Michael Coughlan , Ian J. Hewitt , Heather A. Harrington , Gillian Grindstaff

Perhaps the most iconic feature of melting Arctic sea ice is the formation of distinctive, complex ponds on its surface during late spring. The evolution of melt ponds and their geometrical characteristics determines the albedo of sea ice,…

Atmospheric and Oceanic Physics · Physics 2017-08-11 Yi-Ping Ma , Ivan Sudakov , Courtenay Strong , Kenneth M. Golden

As an increasing amount of remote sensing data becomes available in the Arctic Ocean, data-driven machine learning (ML) techniques are becoming widely used to predict sea ice velocity (SIV) and sea ice concentration (SIC). However, fully…

Machine Learning · Computer Science 2025-10-21 Younghyun Koo , Maryam Rahnemoonfar

The search for ephemeral liquid water on Mars is an ongoing activity. After the recession of the seasonal polar ice cap on Mars, small water ice patches may be left behind in shady places due to the low thermal conductivity of the Martian…

Earth and Planetary Astrophysics · Physics 2023-09-12 Mira Gergácz , Ákos Kereszturi

We consider a set of M images, whose pixel intensities at a common point can be treated as the components of a M-dimensional vector. We are interested in the estimation of the modulus of such a vector associated to a compact source. For…

Cosmology and Nongalactic Astrophysics · Physics 2011-01-05 F. Argueso , J. L. Sanz , D. Herranz

Arctic sea ice concentration is often coarsely observed and numerically computed despite its importance for polar climate system. In this work we present three machine-learning methods to recover the original high-resolution images from the…

Atmospheric and Oceanic Physics · Physics 2021-09-02 Jun Zhai , Cecilia M. Bitz

Solar irradiance is fundamental data crucial for analyses related to weather and climate. High-precision estimation models are necessary to create areal data for solar irradiance. In this study, we developed a novel estimation model by…

Atmospheric and Oceanic Physics · Physics 2024-07-08 Jun Sasaki , Maki Okada , Kenji Utsunomiya , Koji Yamaguchi

While multiple sensors are used for real-time monitoring in additive manufacturing, not all provide practical or reliable process insights. For example, high-speed X-ray imaging offers valuable spatial information about subsurface melt pool…

Machine Learning · Computer Science 2025-09-04 Satyajit Mojumder , Pallock Halder , Tiana Tonge

This paper presents a neural-network-based solution to recover pixels occluded by clouds in satellite images. We leverage radio frequency (RF) signals in the ultra/super-high frequency band that penetrate clouds to help reconstruct the…

Computer Vision and Pattern Recognition · Computer Science 2021-06-17 Mingmin Zhao , Peder A. Olsen , Ranveer Chandra

Knowledge on changes in glacier calving front positions is important for assessing the status of glaciers. Remote sensing imagery provides the ideal database for monitoring calving front positions, however, it is not feasible to perform…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Fei Wu , Nora Gourmelon , Thorsten Seehaus , Jianlin Zhang , Matthias Braun , Andreas Maier , Vincent Christlein
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