Variable high temperatures through the week, ranging from 62°F to 76°F. Dry weather expected throughout the week.
This week's forecast shows temperatures running 10 F above the historical average for November. Normal highs for this period are around 61 F with lows around 40 F.
1987 - Twenty-one cities, mostly in the Ohio Valley, reported record high temperatures for the date. The afternoon high of 80 degrees at Columbus OH was their warmest reading of record for so late in the season. Showers and thundershowers associated with a tropical depression south of Florida produced 4.28 inches of rain at Clewiston in 24 hours.
More on this and other weather history
Day: Patchy frost before 7am. Sunny. High near 68, with temperatures falling to around 62 in the afternoon. Southwest wind 0 to 5 mph.
Night: Clear, with a low around 43. South wind around 0 mph.
Day: Sunny. High near 72, with temperatures falling to around 66 in the afternoon. South wind 0 to 10 mph.
Night: Mostly clear, with a low around 46. South southwest wind around 5 mph.
Day: Sunny. High near 76, with temperatures falling to around 69 in the afternoon. Southwest wind around 5 mph.
Night: Mostly clear, with a low around 49. West wind around 0 mph.
Day: Sunny, with a high near 74. Southeast wind 0 to 10 mph.
Night: Mostly clear, with a low around 57. South wind around 5 mph.
Day: Mostly sunny, with a high near 75.
Night: Mostly clear, with a low around 49.
Day: Sunny, with a high near 70.
Night: A slight chance of rain showers before midnight. Mostly clear, with a low around 46. Chance of precipitation is 20%.
Day: Sunny, with a high near 62.
Sun's High Temperature
98 at 6 Miles West-southwest Of Glamis, CA
Sun's Low Temperature
12 at Angel Fire, NM and Crested Butte, CO
When mountain moss is soft and limpid, expect rain.
Current conditions: We use the nearest available station to your location - including professional MESONET/MADIS and local weather stations - often miles closer than regional airports.
Forecasts: National Weather Service point forecasts predict for your specific area, not broad regional zones, making them far more relevant to your location.