2024/22/01 San Diego Floods


January 2024 San Diego Flood mostly enhanced by human-driven climate change but natural variability also played a role

Press Summary (First published 2024/25/01)

Event Description

On January 22, 2024, San Diego, known for its relatively dry climate and occasional winter storms, was taken by surprise when an unexpectedly powerful Pacific front hit the region. The convergence of a long-tail jet stream, an atmospheric river, and unstable air masses intensified the storm, resulting in a rare and impactful atmospheric river that brought substantial rainfall to the area. Northeast of downtown San Diego, over 5 inches of rain fell, leading to intense flooding. The city's airport recorded 2.73 inches of rain, establishing a new record for the highest rainfall on any January day. Monday's rainfall also ranked as the fourth-wettest day on record. To provide context, the historical average rainfall in San Diego for the entire month of January is 1.98 inches.

 Looking ahead, Mayor Gloria emphasized the need for federal assistance, recognizing the challenges posed by increasingly unusual weather patterns linked to climate change. Despite initial forecasts, the city experienced its wettest January day on record, catching residents off guard. Mayor Todd Gloria declared a state of emergency due to extreme rainfall and flash flooding, leading to the transformation of a high school into a temporary shelter for around 100 homes affected by flooding. The impact of the storm was widespread, with social media videos capturing cars being swept away by fast-moving waters, turning roads into rivers. The Southcrest neighborhood, southeast of downtown, saw residents requiring rescue as standing water quickly surrounded their apartment complex, although fortunately, no injuries were reported. Tijuana and other parts of northern Baja California were also significantly affected, leading to the rescue of at least eight migrants by U.S. Customs and Border Protection agents and San Diego Fire Department rescuers.

Navy Base San Diego, located south of downtown, reported flooding as a thick cell of precipitation moved over the area, causing multiple streets and Interstate 15, a route leading to Las Vegas, to be effectively shuttered. Mayor Gloria, in a news conference at Lincoln High School, which served as a shelter, urged residents and visitors to stay off roads on Monday, emphasizing that while the weather event was predicted in terms of rain, the amount of rain in such a short time was a surprise to everyone. The storm's impact extended across the region, with Mission Valley experiencing impassable roads and Ocean Beach witnessing flooding. In the north end of San Diego County, State Route 78 was closed east of the city of Oceanside due to lanes buried in floodwaters, and eastbound lanes remained closed Monday night. The storm, drawing moisture from the Pacific and forming an atmospheric river, produced once-in-a-generation effects, reminiscent of the havoc caused by El Niño in 1983 or 1998.

The Surface Pressure Anomalies reveal a large depression area over the analyzed domain of the order of 5 hPa or larger. This configuration led to high Temperature Anomalies along the coast and negative Temperature Anomalies in the inner regions. Precipitation data indicate that the majority of the area experiencing heavy precipitation is on the Pacific Coast, causing intense rain on the western flank. The coastal area experienced extreme precipitation, reaching up to or exceeding 80 mm/day. Windspeed data also indicate moderate winds, sustained mainly over the coast.

Climate and Data Background for the Analysis

According to the IPCC AR6 report, there is robust evidence, based on both detailed modeling and simple physics, that precipitation associated with atmospheric rivers will increase in the future in most areas of the world (high confidence), as the content of water vapor increases over the oceans of about 7% per 1°C of warming. Looking more in detail at the case of California, Chapter 8 states that "Under continued global warming, more intense moisture transport within atmospheric river events is projected to increase the magnitude of heavy precipitation events on the west coast of the USA.". Moreover, "the frequency, magnitude and duration of atmospheric rivers making landfall along the North American west coast are projected to increase".

Our analysis approach rests on looking for weather situations similar to those of the event of interest having been observed in the past. For this event, we have medium-low confidence in the robustness of our approach given the available climate data, as the event is unusual in the data record

ClimaMeter Analysis

We analyze here (see Methodology for more details) how events similar to the low pressure system leading to San Diego floods have changed in the present (2001–2023) compared to what they would have looked like if they had occurred in the past (1979–2001) in the region [-120°E -111°E 27°N 35°N]. The Surface Pressure Changes indicate no changes in the strength of the low-pressure system in the Pacific compared to the past, except in distant areas from the center of the system. Temperature Changes show cooler conditions along coasts and in the Pacific, while no changes are observed in the inner areas. Precipitation Changes show that similar events now produce heavier (up to 11 mm/day) precipitation in the present than in the past in some areas of the Northern Part of the Pacific coast, with also a small amount of heavier precipitation along the coast. Windspeed Changes indicate no significant changes in winds on the coastal areas analyzed. We also find that Similar Past Events occur most frequently in January in the present, while they previously mostly occurred in February. Considering the affected urban areas, San Diego, Tijuana, and Solana Beach experience an increase in precipitation, with up to 3 mm/day more rain in the present than in the past.

Finally, we find that sources of natural climate variability, notably the Atlantic Multidecadal Oscillation, may have only partly influenced the event. This means that the changes we see in the event compared to the past may be mostly due to human driven climate change.

Conclusion

Based on the above, we conclude that events similar to the January 2024 San Diego Floods are up  to  11 mm/day (up to 15%) wetter over the Pacific coast in the present than they have been in the past. We interpret the January 2024 San Diego Floods as a very uncommon event whose extreme characteristics can mostly be ascribed to human-driven climate change and natural climate variability likely played a modest role.

Contact Authors

Tommaso Alberti, INGV, Italy  📨tommaso.alberti@ingv.it  🗣️Italian, English

Davide Faranda, IPSL-CNRS, France  📨davide.faranda@lsce.ipsl.fr  🗣️French, Italian, English

Additional Information : Complete Output of the Analysis

The figure shows the average of surface pressure anomaly (msl) (a), average 2-meter temperatures anomalies (t2m) (e), cumulated total precipitation (tp) (i),  and average wind-speed (wspd) in the period of the event. Average of the surface pressure analogs found in the counterfactual [1979-2000] (b) and factual periods [2001-2022] (c), along with corresponding 2-meter temperatures (f, g),  cumulated precipitation (j, k), and wind speed (n, o).  Changes between present and past analogues are presented for surface pressure ∆slp (d),  2 meter temperatures ∆t2m (h), total precipitation ∆tp (i), and windspeed ∆wspd (p): color-filled areas indicate significant anomalies with respect to the bootstrap procedure. Violin plots for past (blue) and present (orange) periods for Quality Q analogs (q), Predictability Index D (r), Persistence Index Θ (s), and distribution of analogs in each month (t). Violin plots for past (blue) and present (orange) periods for ENSO (u), AMO (v) and PDO (w).  Number of the Analogues occurring in each subperiod (blue) and linear trend (black).  Values for the peak day of the extreme event are marked by a blue dot. Horizontal bars in panels (q,r,s,u,v,w) correspond to the mean (black) and median (red) of the distributions.