seasonal

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Seasonal (monthly) forecast anomalies for the next six months, with the local climatology they are measured against. Each result gives, per metric: the ERA5 baseline mean (means), its interannual standard deviation (std), the predicted anomaly (anom, in degrees C / mm / km/h) and how unusual that is, both as standard deviations (norm) and as a percentile rank among the last 30 years (perc). <br><b>When to use:</b> Answer 'will next month be hotter/wetter than normal here?' or 'where is the coming season predicted to be most unusual?' <br><b>Date format:</b> ym_start and ym_end are YYYYMM, inclusive. For a single month set both to the same value. Defaults to next month through next month + 5. <br><b>Performance:</b> Filter by locid, ctryid or latlon+radius_km to keep fast; a whole-world month slice is about 4000 rows and fits in one page. <br><b>Prerequisites:</b> None; supply locid, name, latlon+radius_km, ctryid, or nothing at all for a global query. <br><b>Investigate:</b> Rank places by how abnormal the coming months look. Use sort=perc:obs.rain.sum for rainfall and sort=norm:max_t.mean for heat. <br><b>Augment:</b> Back claims about the coming season with the predicted anomaly and how it compares with the local 30-year normal. <br><b>Notes:</b> Monthly resolution only — for daily forecasts use typicalweather. The forecast is ECMWF SEAS5; its anomalies are relative to SEAS5's own 1991-2020 model climatology, so means + anom approximates rather than equals the predicted absolute. Returns: ym_start, ym_end, baseline, metrics, count, truncated, note, error, next_cursor, results, locid, location, ym, run_ymd, basis_type, means, std, anom, norm, perc, criteria_met, criteria_met_count.