Major Melting Event on the Ross Ice Shelf, Antarctica, Connected With Enhanced Atmospheric Turbulence

9 pages, 4 figures, supporting information https://doi.org/10.1029/2025GL120181.-- Data Availability Statement: The GNSS data set used in this study is available through the NSF GAGE Facility operated by the EarthScope Consortium (Bromirski & Gerstoft, 2017). GNSS data were processed using the G...

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Detalhes bibliográficos
Autores: Mondal, Dhiman, Elosegui, Pedro, Ramrajvel, Nathra, Paine, Scott
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2026
País:España
Recursos:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:dnet:digitalcsic_::af97ae789c4712b8ad99666330135d0a
Acesso em linha:http://hdl.handle.net/10261/431970
Access Level:acceso abierto
Palavra-chave:Take urgent action to combat climate change and its impacts
Descrição
Resumo:9 pages, 4 figures, supporting information https://doi.org/10.1029/2025GL120181.-- Data Availability Statement: The GNSS data set used in this study is available through the NSF GAGE Facility operated by the EarthScope Consortium (Bromirski & Gerstoft, 2017). GNSS data were processed using the GipsyX software package (Bertiger et al., 2020) by JPL under license to MIT Haystack Observatory (The software can be requested from: https://gipsyx.jpl.nasa.gov/index.php?page=software). Data analysis was performed using the Python programming language, version 3.11, and publicly available tools and libraries built on top of Python, such as pandas, NumPy, and SciPy. Bayesian analysis was performed using the PyMC Python package (https://www.pymc.io). Figures were produced using Generic Mapping Tools (https://www.generic-mapping-tools.org) and Matplotlib (https://matplotlib.org)

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