BlueMath-Hub
A Cloud-Based, Open-Source, Python Framework with Interactive Notebooks for Statistical Analysis and Simulation of Coastal Climate Hazards in a Changing Climate
Laura Cagigal (Universidad de Cantabria)
Valvanuz Fernandez-Quiruelas (Universidad de Cantabria)
Fernando Méndez (Universidad de Cantabria)
Javier Tausia (Universidad de Cantabria)
Jared Ortiz-Angulo (Universidad de Cantabria)
Alba Ricondo (Oregon State University)
Paula Camus (Universidad de Cantabria)
Antonio S. Cofino (Instituto de Física de Cantabria)
Dylan Anderson (U.S. Army Corps of Engineers)
Peter Ruggiero (Oregon State University)
Meredith Leung (University Corporation for Atmospheric Research)
Mark Merrifield (Scripps Institution of Oceanography)
John Marra (National Oceanic and Atmospheric Administration)
Borja G. Reguero (University of California)
David Gutierrez-Barcelo (University of California)
Ron Hoeke (CSIRO - Oceans and Atmosphere, Wembley)
Emilio Echevarria (CSIRO - Oceans and Atmosphere, Wembley)
José A.A. Antolinez (TU Delft - Coastal Engineering)
Giovanni Coco (The University of Auckland)
Brad Murray (Duke University)
Jayantha Obeysekera (Florida International University)
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Abstract
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.
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