High temperatures start near 69°F, reaching 73°F before cooling to 50°F, then recovering to 50°F by week's end. Some rain possible with at least 2 days showing precipitation chances of 20% or higher.
This week's forecast shows temperatures running 5 F above the historical average for November. Normal highs for this period are around 61 F with lows around 37 F.
1890 - The temperature at Los Angeles, CA, reached 96 degrees, a November record for 76 years.
More on this and other weather history
Day: Sunny. High near 69, with temperatures falling to around 63 in the afternoon. South wind 0 to 5 mph.
Night: Mostly clear, with a low around 45. South wind around 5 mph.
Day: Sunny. High near 72, with temperatures falling to around 65 in the afternoon. Southwest wind 5 to 10 mph.
Night: Mostly clear, with a low around 45. North wind 0 to 5 mph.
Day: Sunny. High near 72, with temperatures falling to around 65 in the afternoon. Southeast wind around 5 mph.
Night: Partly cloudy, with a low around 53. South wind 5 to 10 mph.
Day: Rain showers likely before noon, then showers and thunderstorms likely. Partly sunny, with a high near 73. Southwest wind 10 to 15 mph. Chance of precipitation is 70%.
Night: A chance of showers and thunderstorms before midnight. Partly cloudy, with a low around 46. Chance of precipitation is 30%.
Day: Sunny, with a high near 70.
Night: A slight chance of rain showers. Mostly clear, with a low around 44. Chance of precipitation is 20%.
Day: Sunny, with a high near 58.
Night: Mostly clear, with a low around 32.
Day: Sunny, with a high near 50.
                  Mon's High Temperature
96 at 6 Miles West-southwest Of Glamis, CA and 2 Miles South Of Mohawk, AZ
Mon's Low Temperature
13 at 18 Miles West-southwest Of Dillon, MT
Clouds on the setting sun's brow indicate rain.
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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.