Towards a scalable architecture

for climate adaptation services (illustration through sea-level change and

coastal flooding)

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A scalable architecture for climate adaptation services

Challenges:

Volume and heterogeneity of data to build climate services;

Network security issues when internal nodes (HPC, big data) are

requested from DMZ (external network, internet);

Management of asynchronous workflows for experts;

Near real-time (on-the-fly) computation for public users;

Scalability and performances;

Efficient communication about possible coastal flooding related to

climate change, and uncertainties (sea-level change scenarios).

Keywords:

Bigdata, High-Performance Data (HPD) and computing (HPC)

Worfklow management, security

(Web) Data diffusion (OGC, INSPIRE):

web portal and web services

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An illustration through sea-level change and coastal flooding

Port-Camargue, +40cm

Computation from LIDAR (Digital

Elevation Model from IGN)

And SHOM data on tides and water

levels.

On-going work:

- Speedup grid-based data analysis including multi-resolution strategies (Rasdaman)

- Increase the complexity of overflow model (Swash, Swan).

- Extend this framework capabilities to tackle large environmental data collections