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  1. Estimating Causal Effects of Greenland Blocking on Arctic Sea Ice Melt using Deep Learning Technique

    23 Jul 2024 | Contributor(s): Sahara Ali, Omar Faruque, Yiyi Huang, Md Osman Gani, Aneesh Subramanian, Nicole Schlegel, Jianwu Wang, Josephine Namayanja (contributor)

    Over the recent decades, Earth scientists have noted a more pronounced shift in climate patterns near the polar regions, specifically the Arctic, in comparison to the rest of the Earth. The increased warming is largely attributed to the diminishing ice cover in the Arctic, which causes solar...

  2. Quantifying Causes of Arctic Amplification via Deep Learning based Time-series Causal Inference

    23 Jul 2024 | Contributor(s): Sahara Ali, Omar Faruque, Yiyi Huang, Aneesh Subramanian, Nicole-Jienne Shchlegel, Md Osman Gani, Jianwu Wang, Josephine Namayanja (contributor)

    The warming of the Arctic, also known as Arctic amplification, is led by several atmospheric and oceanic drivers. However, the details of its underlying thermodynamic causes are still unknown. Inferring the causal effects of atmospheric processes on sea ice melt using fixed treatment effect...

  3. Benchmarking probabilistic machine learning models for arctic sea ice forecasting

    23 Jul 2024 | Contributor(s): Sahara Ali, Seraj Mostafa, Xingyan Li, Sara Khanjani, Jianwu Wang, James Foulds, Vandana Janeja

    The Arctic is a region with unique climate features, motivating new AI methodologies to study it. Unfortunately, Arctic sea ice has seen a continuous decline since 1979. This not only poses a significant threat to Arctic wildlife and surrounding coastal communities but is also adversely affecting...

  4. MT-IceNet - A Spatial and Multi-Temporal Deep Learning Model for Arctic Sea Ice Forecasting

    23 Jul 2024 | Contributor(s): Sahara Ali, Jianwu Wang, Josephine Namayanja (contributor)

    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 sea ice loss as demonstrated by satellite observations....

  5. Incorporating Causality with Deep Learning in Predicting Short-Term and Seasonal Sea Ice

    16 Jul 2024 | Contributor(s): Emam Hossain, Sahara Ali, Yiyi Huang, Nicole Schlegel, Jianwu Wang, Aneesh Subramanian, Md Osman Gani

    Abstract: Arctic sea ice (ASI) is playing a pivotal role in keeping global warming under control. However, the recently amplified decreasing sea ice trend has become a major concern. Since satellites started monitoring the ASI in 1979, every decade the Arctic has lost 13.1% of sea ice and the...

  6. A Survey on Causal Discovery Methods for IID and Time Series Data

    16 Jul 2024 | Contributor(s): Uzma Hasan, Emam Hossain, Md Osman Gani

    Abstract: The ability to understand causality from data is one of the major milestones of human-level intelligence. Causal Discovery (CD) algorithms can identify the cause-effect relationships among the variables of a system from related observational data with certain assumptions. Over the...

  7. Evaluating Machine Learning and Statistical Models for Greenland Bed Topography

    15 May 2024 | Contributor(s): Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Homayra Alam, Omar Faruque, Sikan Li, Mathieu Morlighem, Jianwu Wang

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bed topography in Greenland using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for understanding ice sheet...

  8. Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography

    15 May 2024 | Contributor(s): Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Homayra Alam, Omar Faruque, Sikan Li, Mathieu Morlighem, Jianwu Wang

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bedrock topography under the Greenland ice sheet using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for...

  9. Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography

    15 May 2024 | Contributor(s): Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Homayra Alam, Omar Faruque, Sikan LI, Mathieu Morlighem, Jianwu Wang

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bedrock topography under the Greenland ice sheet using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for...

  10. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science

    23 Apr 2024 | Contributor(s): Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, Don Engel

    Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, and Don Engel. 2023. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA. IEEE,...

  11. Metrics for the Quality and Consistency of Ice Layer Annotations

    23 Apr 2024 | Contributor(s): Naomi Tack, Bayu Adhi Tama, Atefah Jebeli, Vandana P. Janeja, Don Engel, Rebecca Williams

    Naomi Tack, Bayu Adhi Tama, Atefeh Jebeli, Vandana P. Janeja, Don Engel, and Rebecca Williams. 2023. Metrics for the Quality and Consistency of Ice Layer Annotations. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA....

  12. Visualizing the Greenland Ice Sheet in VR using Immersive Fence Diagrams

    23 Apr 2024 | Contributor(s): Naomi Tack, Rebecca Williams, Nicholas Holschuh, Sharad Sharma, Don Engel

    Naomi Tack, Rebecca Williams, Nicholas Holschuh, Sharad Sharma, and Don Engel. 2023. Visualizing the Greenland Ice Sheet in VR using Immersive Fence Diagrams. In Practice and Experience in Advanced Research Computing, ACM, Portland OR USA, 429–432. DOI:...

  13. Initial Development of a WebXR Platform for Ice Penetrating Radar Data, to Improve our Understanding of Polar Ice Sheets.

    23 Apr 2024 | Contributor(s): Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, Don Engel

    Tack, Naomi, Holschuh, Nicholas, Sharma, Sharad, Williams, Rebecca, and Engel, Don. “Initial Development of a WebXR Platform for Ice Penetrating Radar Data, to Improve our Understanding of Polar Ice Sheets.” Poster at the AGU23 meeting, IN43B-0627, December 2023 

  14. Structural architecture and the episodic evolution of the ediacaran Campo Alegre Basin (southern Brazil): Implications for the development of a synorogenic foreland rift and a post-collisional caldera volcano

    09 Apr 2021 | Contributor(s): Lucas Martins Lino, Francy Roxana Quiroz-Valle, Vinicius Abud louro, Miguel Ângelo Stipp Basei, Silvio Roberto Farias Vlach, Mathias Hueck, Patricio Rodrigo Montecinos Munõz, Sérgio Brandolise Citroni

    During the last decades, tectonic models provided new insight into the evolution of the Luis Alves, Curitiba, and Paranaguá terranes, which are all limited by thrust and transpressive shear zones, nowadays outcropping only as deep crustal horizons and presenting poorly known lateral...

  15. Workshop on the Impacts associated with the primary fallout of volcanic ash and subsequent aeolian remobilisation, Consensual Document

    19 May 2020 | Publications | Contributor(s): Lucia Dominguez, Costanza Bonadonna, Donaldo Bran

    The inherent complexity associated with volcanic eruptions and their relationship with societies requires innovative strategies about how we assess and manage risk. The 2011 Cordón Caulle eruption (2011-CC) demonstrated the additional complexity associated with secondary hazards and...

  16. Workshop on Wind-remobilisation processes of volcanic ash, Consensual Document

    20 Feb 2020 | Publications | Contributor(s): Costanza Bonadonna, Paul A Jarvis, Lucia Dominguez, Corine Frischknecht, Pablo Forte, Donaldo Bran, Rigoberto Aguilar, Frances Beckett, Manuela Elissondo, Jack Gillies, ulrich kueppers, Jonathan Merrison, Nick Varley, Kristi L Wallace

    Explosive volcanic eruptions can eject large quantities of tephra into the atmosphere that can be dispersed and deposited over wide areas. Whilst the hazardous consequences of primary tephra fallout are well known, subsequent remobilisation of ash by aeolian processes can continue to present an...

  17. Intra-Conference Field Trip - Natural Park of La Garrotxa volcanic field: magmatic vs phreatomagmatic activity. The role of the basement to control the eruptive dynamics

    29 May 2018 | Publications | Contributor(s): Joan Martí, Xavier Bolós, Llorenç Planagumà

  18. Pre-Conference Field Trip - Monogenetic volcanism of the Catalan Volcanic Zone: Maar craters, scoria cones and rootless volcanoes of the Garrotxa volcanic field, and open fossil excavation in a Pliocene maar crater.

    29 May 2018 | Publications | Contributor(s): Xavier Bolós¹, Joan Marti, Oriol Oms, Gerard Campeny, Bruno Gómez de Soler

  19. Abstract Volume of the 7th International Maar Conference

    29 May 2018 | Publications | Contributor(s): Xavier Bolós, Joan Martí

  20. Size-distribution of scoria cones within the Eğrikuyu Monogenetic Field (Central Anatolia, Turkey)

    26 May 2018 | Publications | Contributor(s): Göksu USLULAR, Gonca Kuşcu, Arda Arcasoy

    Eğrikuyu Monogenetic Field (EMF) is one of the five clusters of monogenetic volcanoes in Quaternary Central Anatolian Volcanic Province (CAVP). EMF consists mainly of scoria cones and a few maars (e.g. Kutören, Obruk). Previous studies on monogenetic volcanoes of CAVP mainly focused on...