dailycomp

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Returns per-day observed values with percentiles and z-scores vs a sliding N-day window over a historical baseline. <br><b>When to use:</b> Graph heatwaves, cold spells, and other streaks by showing daily departures from normal. Also compare two separate periods or locations using z-scores or percentiles for normalized severity. <br><b>Date format:</b> YYYYMMDD for ymd_start and ymd_end. Keep ranges ≤30 days for fast response; up to 90 days is feasible. <br><b>Performance:</b> Computed on demand; slower for long date ranges. <br><b>Prerequisites:</b> Use /location to obtain a locid first. <br><b>Investigate:</b> Best for detailed day-by-day anomaly investigation once approximate dates and location are known. Use separate calls for two periods to compare heatwave severity via z-score. Do NOT use for ranking top-N events across years — call /events with criteria for that and post-process the response. <br><b>Augment:</b> Provides the daily series needed to describe the arc of a heatwave or cold snap in a news narrative. Returns: locid, lat, lon, dates, num_years, avg_coverage, metrics, metrics.{key}.values, metrics.{key}.pcts, metrics.{key}.sigmas, metrics.{key}.p1 … p99, metrics.{key}.bmin / bmax, metrics.{key}.mean, metrics.{key}.stddev, metrics.{key}.coverage.