TY - CHAP
T1 - BlueMath-Hub
T2 - A Cloud-Based, Open-Source, Python Framework with Interactive Notebooks for Statistical Analysis and Simulation of Coastal Climate Hazards in a Changing Climate
AU - Cagigal, Laura
AU - Fernandez-Quiruelas, Valvanuz
AU - Méndez, Fernando
AU - Tausia, Javier
AU - Ortiz-Angulo, Jared
AU - Ricondo, Alba
AU - Camus, Paula
AU - Cofino, Antonio S.
AU - Anderson, Dylan
AU - Ruggiero, Peter
AU - Leung, Meredith
AU - Merrifield, Mark
AU - Marra, John
AU - Reguero, Borja G.
AU - Gutierrez-Barcelo, David
AU - Hoeke, Ron
AU - Echevarria, Emilio
AU - Antolinez, José A.A.
AU - Coco, Giovanni
AU - Murray, Brad
AU - Obeysekera, Jayantha
N1 - Publisher Copyright:
© The Author(s) 2026.
PY - 2026
Y1 - 2026
N2 - Addressing global challenges such as coastal hazards and climate change requires innovative tools capable of analyzing complex environmental drivers, including waves, storm surges, and cyclones, across varying scales. These tools are vital for predicting floods, assessing risks, and planning adaptive responses. BlueMath-Hub has been developed as a global collaborative initiative to provide accessible, customizable solutions for both researchers and practitioners. It aims to simplify the use of advanced statistical and numerical models, fostering creative and scalable approaches in coastal science and engineering. BlueMath, the core of this platform, is an open-source repository of Python tools accessible via a cloud-based Jupyter Hub environment. It integrates statistical methods and numerical model wrappers within a modular framework. The system includes: (a) BlueMath-Toolkit, providing tools for data mining, interpolation, and model integration; (b) BlueMath-Statistical Downscaling, focusing on extreme events and generalized models; (c) BlueMath-Hybrid Downscaling, combining statistical and numerical approaches for optimized solutions; and (d) BlueMath-Climate Services, supporting integrated applications such as compound flooding assessments. BlueMath is continuously evolving, with its tools already applied in research, publications, and training. By lowering barriers to entry and enabling collaborative workflows, BlueMath-Hub supports the development of innovative solutions to mitigate the impacts of a changing climate.
AB - Addressing global challenges such as coastal hazards and climate change requires innovative tools capable of analyzing complex environmental drivers, including waves, storm surges, and cyclones, across varying scales. These tools are vital for predicting floods, assessing risks, and planning adaptive responses. BlueMath-Hub has been developed as a global collaborative initiative to provide accessible, customizable solutions for both researchers and practitioners. It aims to simplify the use of advanced statistical and numerical models, fostering creative and scalable approaches in coastal science and engineering. BlueMath, the core of this platform, is an open-source repository of Python tools accessible via a cloud-based Jupyter Hub environment. It integrates statistical methods and numerical model wrappers within a modular framework. The system includes: (a) BlueMath-Toolkit, providing tools for data mining, interpolation, and model integration; (b) BlueMath-Statistical Downscaling, focusing on extreme events and generalized models; (c) BlueMath-Hybrid Downscaling, combining statistical and numerical approaches for optimized solutions; and (d) BlueMath-Climate Services, supporting integrated applications such as compound flooding assessments. BlueMath is continuously evolving, with its tools already applied in research, publications, and training. By lowering barriers to entry and enabling collaborative workflows, BlueMath-Hub supports the development of innovative solutions to mitigate the impacts of a changing climate.
KW - Coastal-hazards
KW - Collaboration
KW - Repository
KW - Statistical Models
KW - Toolbox
UR - https://www.scopus.com/pages/publications/105033854192
U2 - 10.1007/978-3-032-15473-6_46
DO - 10.1007/978-3-032-15473-6_46
M3 - Chapter
AN - SCOPUS:105033854192
T3 - Coastal Research Library
SP - 291
EP - 295
BT - Coastal Research Library
PB - Springer Science and Business Media B.V.
ER -