The World Climate Research Programme Global KM-scale Hackathon

Introduction

The WCRP Digital Earths Lighthouse Activity—supported by key initiatives like Destination Earth (DestinE), Next Generation Earth System Modelling (NextGEMS), WarmWorld, Earth Visualization Engines (EVE), European Eddy-Rich Earth System Models (EERIE), WCRP ESMO, and with the endorsement of the CMIP panel—is serving as the primary sponsor and coordinating body for this hackathon.

The goals of the event are to:

• Promote Global Collaboration, by sharing best-practice in process-based analysis of km-scale simulations: this hackathon will encourage global data sharing and collaborative workflows, allowing experts to work together on the analysis of “Storm Resolving Models” at both global and regional levels.

• Enhance Accessibility: our focus is on making high-quality data resources readily available to users, with support from designated ambassadors who can facilitate international collaboration and access to key data nodes.

• Expand Long-Term Access: looking ahead, the aim is to broaden access for a wider user base by applying the lessons learned from these early efforts to support a more connected data-sharing environment.

This hackathon offers a valuable opportunity for experts to collaborate, share insights, and help advance the development of earth system modeling tools and practices.

Expected outcomes

The 2025 global hackathon is designed to:

• Foster Community and Open Access: Encourage a spirit of collaboration and ensure open access to resources, helping to strengthen connections across the community.

• Promote and Share Best Practices in Coding and Data Workflows: Share effective practices for coding, infrastructure, and data-intensive applications to improve workflows and results.

• Establish Common Standards: Support the development of shared standards for weather and climate data, ensuring consistency and reliability in storm-resolving research.

Drive Advances in Storm Resolving Models: Focus on enhancing and analyzing global and regional Storm Resolving Models for more trustworthy predictions.