2023/01/09-10 California Atmospheric River

Heavy precipitation in California atmospheric river likely strengthen by both human-driven climate change and natural variability  

Press Summary (First published 2023/10/26, Updated 2023/11/22)

Event Description

Atmospheric rivers are long and narrow corridors of extremely humid air, stretching from the tropics across the Atlantic and especially the Pacific ocean, responsible for a large portion of the total precipitation falling over the western parts of Europe and the US. Between December 2022 and January 2023, an impressive sequence of nine atmospheric rivers made landfall in California, bringing the longest period of atmospheric river conditions in the 70 years of available observations. While most of the atmospheric rivers in this sequence mainly affected northern California and the mountain areas, the one that made landfall on 9-10 January 2023 brought heavy precipitation also on the southern coast, including Los Angeles. Atmospheric river had a large impact in California in 2023, buried mountain towns in snow and caused widespread flooding. According to Moody’s RMS, the atmospheric river caused an estimated $5-7 billion dollars in economic losses but only $500 million to $1.5 billion in insured losses

The Surface Pressure Anomalies show a large negative (cyclonic) anomaly between the eastern Pacific and the west Coast of the US. This negative anomaly shows a very active storm track, associated with an intense jet stream, stretching from the tropical Pacific to the coast of California. Precipitation data show several areas of California, especially in mountain regions, with precipitation exceeding 30 mm/day and peaking around 80 mm/day.

Climate and Data Background for the Analysis

According to the IPCC AR6 report, there is robust evidence, based on both detailed modelling 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 low confidence in the robustness of our approach given the available climate data, as the event is largely unique in the data record.

ClimaMeter Analysis

We analyse here (see Methodology for more details) how events similar to the 26 December 2022 - 10 January 2023 California atmospheric river have changed in the present (2000–2021) compared to what they would have looked like if they had occurred in the past (1979–2000) in the region [-155°E -115°E 28°N 54°N]. Surface pressure changes indicate that the storm track associated with atmospheric rivers making landfall in California exhibits pressure anomalies 2 hPa deeper in the present than in the past. The associated Precipitation changes show that the total precipitations associated with these atmospheric rivers are 1-5 mm/day higher over California, and 1-5 mm/day drier on the northern half of the US West Coast (in the states of Oregon and Washington), suggesting a southerly shift of the areas affected by the most intense precipitations. The associated Temperature changes are 3-5 °C higher over California, and 1-2 °C lower on the north. A similar but weaker signal is found for the analysis in the urban areas of Reno, Sacramento and Los Angeles. The latter is getting wetter by 1 mm/day in the present than in the past during rainfall events caused by atmospheric rivers similar to that analysed. We also note that Similar Past Events have become slightly more common in the months of December and March, and less common in February

Finally, we find that sources of natural climate variability, notably the El Nino Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation, may have heavily influenced the event. This means that the changes we see in the event compared to the past may be primarily due to natural climate variability


Based on the above, we conclude that rainfall events similar to the 26 December 2022 - 10 January 2023 California atmospheric river are more intense with lower pressure (2 hPa) and higher precipitation (1 mm/day to 5 mm/day) in the present than in the past. 

Contact Authors

Flavio Pons, IPSL-CNRS, France  📨flavio.pons@lsce.ipsl.fr  🗣️French, 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.