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This week's forecast shows temperatures running 4°F above the historical average for October-November. Normal highs for this period are around 71°F with lows around 49°F.
1846 - Eighty-seven pioneers were trapped by early snows in the Sierra Nevada Mountains that piled five feet deep, with 30 to 40 foot drifts. Just 47 persons survived the "Donner Pass Tragedy".
More on this and other weather history
 
Day: Sunny. High near 72, with temperatures falling to around 70 in the afternoon. South wind 0 to 5 mph.
 
Night: Mostly cloudy. Low around 49, with temperatures rising to around 51 overnight. South southeast wind around 5 mph.
 
Day: A slight chance of rain showers between 7am and 10am. Partly sunny. High near 69, with temperatures falling to around 67 in the afternoon. East wind around 5 mph. Chance of precipitation is 20%.
 
Night: Mostly clear, with a low around 42. North northeast wind 0 to 5 mph.
 
Day: Sunny. High near 69, with temperatures falling to around 66 in the afternoon. East southeast wind 0 to 5 mph.
 
Night: Clear, with a low around 49. South southeast wind around 5 mph.
 
Day: Sunny, with a high near 78. South wind 5 to 10 mph.
 
Night: Clear, with a low around 51. South wind 5 to 10 mph.
 
Day: Sunny, with a high near 78. South wind 5 to 15 mph, with gusts as high as 25 mph.
 
Night: Clear, with a low around 55.
 
Day: Sunny, with a high near 81.
 
Night: Clear, with a low around 55.
 
Day: Sunny, with a high near 80.
 
Night: Mostly clear, with a low around 58.
 
   
Thu's High Temperature
98 at 2 Miles West Of Pala, CA and 6 Miles West-southwest Of Glamis, CA
Fri's Low Temperature
4 at Peter Sinks, UT

Everman is a city in Tarrant County, Texas, United States. Its population was 6,154 in the 2020 census, an increase over the figure of 6,108 tabulated in 2010.
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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.