Project Showcase

Climate Risk Forecasting Dashboard

Problem Statement

Emergency planning teams needed a unified view of climate model outputs to align response timelines across regional partners.

Solution Approach

  • Harmonized CMIP6 ensembles with local sensor networks to calibrate risk thresholds.
  • Delivered an interactive Plotly Dash dashboard with scenario playback and offline exports.
  • Automated data refreshes via AWS Step Functions and event-driven pipelines.

Results & Findings

Stakeholders coordinate faster response plans and simulate mitigation strategies using reproducible forecast bundles.

Forecast accuracy
92% within 5-day horizon
Stakeholder adoption
14 regional partners

Future Work & Improvements

Integrate socio-economic vulnerability layers and automate alerting via CAP feeds.

How to cite

Use the quick export buttons to save citations for reference managers or copy the formatted text directly.

Diogo Ribeiro (2026). Climate Risk Forecasting Dashboard. DataLog | Data Science & Research Theme. https://diogoribeiro7.github.io/analytics-blog-jekyll/portfolio/sample-project/.

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Open science & reproducibility badges

These badges highlight the transparency practices applied to this work. Hover or focus on each badge to learn more about the criteria.

  • Open Data Dataset and code repository published with permissive license. Public repository, DOI issued, README with reproduction steps.
  • Reproducible Workflow Containerized environment and automated tests provided. Continuous integration pipeline with reproducibility checks.
  • Transparent Peer Review Peer review reports archived with DOI and linked to article. Open peer review statement and archived reports on Zenodo.