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NWS San Diego Issues Flood Watch for Southwest California Ahead of Tropical Storm Rachel

October 9, 2026 · wweather1 editorial · 2 min read

The National Weather Service in San Diego has issued a Flood Watch for portions of Southwest California from Saturday evening through Sunday evening. Excessive rainfall from Tropical Storm Rachel could cause flooding across multiple counties.

The National Weather Service issued the Flood Watch at 12:16 PM PDT on October 9, covering Saturday evening through Sunday evening. The watch applies to a large portion of Southwest California, including San Diego County coastal areas, valleys, mountains, and deserts, as well as the mountains and deserts of Riverside and San Bernardino counties, Apple and Lucerne Valleys, Coachella Valley, and San Gorgonio Pass near Banning.

Periods of moderate to heavy rain associated with Tropical Storm Rachel are expected across the region. The heaviest rainfall is anticipated between late Saturday night and Sunday afternoon. Hourly rainfall rates may reach 0.50 to 0.60 inches along the San Diego coast and valleys, 0.50 to 0.70 inches in area deserts, and 0.70 to 1.0 inch in mountain areas.

Excessive runoff from the storm may result in the flooding of rivers, creeks, streams, and other low-lying or flood-prone locations. Weather officials advise residents to stay informed as conditions develop.

Why it is dangerous and what to do

⚠️ Safety
• Monitor updated forecasts for changes and potential Flood Warnings.
• Prepare to take action if you reside in a flood-prone area.
• Avoid walking or driving through flooded roads and low-lying spots.
📊 The numbers, from wweather1 data
Palm Springs: now +39°, Mostly clear.
That is 9° above the October climate norm.
The record for this date is +38° (1996).
Three-day forecast: 9 October: +39°/+27° · 10 October: +36°/+24° · 11 October: +24°/+20°
The figures are computed automatically from the Open-Meteo/ERA5 archive — no eyeball estimates.

🌍 Weather in nearby cities

📰 Data source: NWS. Forecast and analysis — wweather1, based on Open-Meteo / met.no data.

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