Workshop: Bluemath: An Open-Source, Python Framework With Interactive Notebooks For Statistical Analysis And Simulation Of Coastal Climate Hazards In A Changing Climate

Convenor: Fernando Mendez, Spain

• Significance and Motivation
  In the face of increasing global challenges such as coastal hazards and climate change, the use of robust statistical and numerical analysis tools is essential. Tools that facilitate the analysis of multivariate met-oceanic climatic drivers (e.g., waves, storm surges, tropical and extratropical tropical cyclones) acting at multiple spatial and temporal scales are key for predicting flooding events, producing risk assessments or planning for adaptation measures. The development of applications for analysing coastal hazards in a changing climate demand not only accessibility to such tools but also the flexibility to combine them seamlessly to generate valuable insights and solutions. Within this context, BlueMath-Hub emerges as a collaborative platform of many research groups and universities around the world working together to democratise the access to advanced models and services, empowering both researchers and non-specialists to generate customised, complex solutions.
  
  To the best of our knowledge, it is the first tool developed for this purpose. BlueMath promotes collaboration and innovation among scientists while enabling a more resilient future through easily accessible, customizable, and scalable solutions.
  
  
• BlueMath
  BlueMath is an innovative, open-source repository of Python-coded tools. The repository is also accessible from the muti-user cloud-based Jupyter Hub environment, leveraging shared computational resources and the user-friendly interface of Jupyter Notebooks. BlueMath integrates state-of-the art statistical techniques and high-fidelity numerical model wrappers in a system framework that includes from standalone models with straightforward applications to hybrid model-tool combinations that produce comprehensive climate services. The individual modules of BlueMath are designed to be highly adaptable to a wide range of needs and applications:
  a) BlueMath-Toolkit: Provides fundamental tools including data mining, interpolation, and wrappers for numerical models such as SWAN or SWASH. It also supports statistical analyses of waves, tides, and tropical cyclones.
  b) BlueMath-Statistical Downscaling: Facilitates extreme value analysis, weather-typing, and generalised linear models.
  c) BlueMath-Hybrid Downscaling: Integrates statistical and numerical models to optimise computational eSiciency. It includes the implementation of hybrid (surrogate) models.
  d) BlueMath-Climate Services: Enables the creation of integrated climate applications by combining functionalities from previous modules. Examples include the TESLA climate emulator, as well as detailed workflows of the integration of these tools on already implemented compound flooding and risk assessment projects. Regarding the scientific content of BlueMath, most of the sub-modules have been published in the last 10 years in high journal impact papers, guarantying the quality of the tools.

Observations: Participants should bring a laptop and have a Google account.