Climate and Environmental Open Data Analysis
8 weeks · 0 milestones
Analyse a real named publicly available climate or environmental dataset: NOAA Global Surface Temperature, NASA GISS Surface Temperature Analysis, Copernicus Climate Change Service ERA5 reanalysis, EPA Air Quality System historical data, or equivalent. The proof is a documented analysis report: data source and version, preprocessing decisions with rationale, statistical analysis (trend detection, anomaly identification, spatial or temporal comparison), uncertainty quantification, and written conclusions with specific physical interpretation. All sources listed are free and publicly accessible. Real climate datasets contain real measurement uncertainty, coverage gaps, and confounds that require genuine scientific reasoning to navigate — rigorous analysis produces real artifacts of scientific value. Reviewed by an environmental scientist who challenges the statistical methodology — specifically asking whether the identified trend is robust to a specific alternative specification — and asks you to interpret a specific dataset feature you did not discuss in your report.
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Milestone map
3 milestones
Formulate a specific, answerable climate research question and identify the open dataset(s) that contain the relevant data. Open climate datasets are the natural route for this outcome — no physical data collection is required, and the field's most important datasets (ERA5, NOAA Global Surface, NASA GISS, PRISM) are freely available. The quality of the research question determines the quality of the analysis: 'Has [specific variable] changed in [specific region] over [specific time period]?' is answerable; 'Is climate change real?' is not.
Proof required
Submit your research question (one specific sentence), the dataset(s) you have selected with their source URL and access confirmation, a brief description of the dataset's spatial and temporal coverage and resolution, and the dataset's known limitations relevant to your question.
What gets checked
- Research question is specific enough to be answered with a yes, no, or quantified trend from the identified dataset — not a broad descriptive question
- Dataset limitations are described in terms relevant to the analysis question — not a generic 'data may have errors' but the specific spatial resolution, temporal gaps, or measurement biases that affect this question
- Dataset access is confirmed — not just the URL cited but evidence of having downloaded or accessed the data (file size, number of records, date range confirmed)