Weather Anomaly Explorer

This page focuses only on anomaly views: how recent values depart from long-term climatology.

Temperature Anomaly Statistics

Temperature anomaly plots are not easily accessible online, so this puts them in a single place ¹.

Dew Point Anomaly Statistics

Dew point temperature measures atmospheric moisture content and follows a clean seasonal cycle ².

Maximum Temperature Anomaly Statistics

Maximum temperature anomaly tracks how daily high temperatures compare to historical averages ³.

Minimum Temperature Anomaly Statistics

Minimum temperature anomaly tracks how daily low temperatures compare to historical averages ⁴.

Rainfall Anomaly Statistics

Rainfall anomaly tracks departures from normal precipitation amounts ⁵.

Snowfall Anomaly Statistics

Snowfall anomaly tracks departures from normal snowfall amounts ⁶.

Precipitation Anomaly Statistics

Precipitation anomaly plots are also not easily accessible online, so this puts them in a single place ⁷.

Wind Anomaly Statistics

Wind anomaly plots are built from hourly wind speeds, using rolling sums of cube-root daily mean anomalies ⁸.

Diurnal Temperature Range Anomaly Statistics

Diurnal temperature range (DTR) anomaly tracks how the daily temperature swing compares to historical averages ⁹.

Pressure Anomaly Statistics

Pressure anomaly tracks departures from normal atmospheric pressure using rolling sums of daily anomalies ¹⁰.

Footnotes

1. A periodic LOESS smoother is fit to daily mean temperature climatology over 50 years. ↩

2. A periodic LOESS smoother is fit to daily mean dew point temperature derived from hourly observations. ↩

3. A periodic LOESS smoother is fit to daily maximum temperature climatology. ↩

4. A periodic LOESS smoother is fit to daily minimum temperature climatology. ↩

5. Rainfall anomaly is computed as the difference between observed and climatological daily rainfall. ↩

6. Snowfall anomaly is computed as the difference between observed and climatological daily snowfall. ↩

7. In this case, we favour comparing N-day sums against the climatological average of N-day sums. ↩

8. Daily mean wind speeds are compared to a day-of-year climatology after a cube-root transform and summed over rolling windows. ↩

9. A periodic LOESS smoother is fit to the daily diurnal temperature range (max - min) climatology. ↩

10. Daily mean pressure is compared to a day-of-year climatology and summed over rolling windows. ↩