71% came within 3°F
Local temperature forecast performance
How accurate are temperature forecasts in Tulsa, Oklahoma?
In Tulsa, next-day high and low temperature forecasts performed similarly: the typical miss was 2.6°F for highs and 2.4°F for lows.
Opens ZIP 74103 using the nearest current station, which may differ from the archive station below.
What stands out
Tulsa forecast findings
- By forecast day 7, the typical miss increased to 5.2°F for highs and 4.6°F for lows, showing how precision changed farther ahead.
- On forecast day 1, July lows had the smallest typical miss (1.6°F), while February highs had the largest (5.5°F).
- Across days 1, 3, 5, and 7, Tulsa was close to the national archive average, with less than 0.2°F separating them.
- The strongest monthly directional tendency appeared in January highs, when forecasts averaged 1.9°F cooler than observed.
At a glance
Forecast day 1 accuracy
Highs Lows
Tulsa: 3.6°F typical miss National archive average: 3.5°F
Combined high and low results across forecast days 1, 3, 5, and 7.69% came within 3°F
Error generally grows farther into the forecast
The dots show the typical miss on each forecast day.
See within-3°F percentages and window timing
High and low windows represent the same numbered forecast day, but the high window ends 12 hours later and therefore has 12 more hours of lead time.
How forecasts change through the year
Each tile is forecast day 1’s typical miss.
High temperatures
Low temperatures
Based on archived raw NBM forecasts compared with observed daily highs and lows near Tulsa. Results describe this model archive, not every forecast provider.
How these numbers are calculated
The forecasts are raw NBM median temperature guidance initialized at 12Z. Results include multiple NBM model eras and are retrospective, so they describe this archive rather than guaranteeing future performance.
“Typical miss” is mean absolute error: the average size of the error regardless of direction. Warmer or cooler tendency is signed bias, which can be small even when individual errors are larger.