Response of Sea Surface Temperature to Atmospheric Rivers

June 18, 2024

A new article titled “Response of sea surface temperature to atmospheric rivers” by Tien-Yiao Hsu (SIO /CW3E), Matthew R. Mazloff (SIO), Sarah T. Gille (SIO), Mara A. Freilich (Brown University), Rui Sun (SIO/CW3E) and Bruce D. Cornuelle (SIO) was published in Nature Communications on June 12, 2024. This work investigates the impact of atmospheric rivers (ARs) on sea surface temperature (SST) over the North Pacific by analyzing 25 years of ocean reanalysis data using an SST budget equation. Authors show that in the region of strong ocean modification, ocean dynamics can offset over 100% of the anomalous SST warming that would otherwise arise from atmospheric forcing (Figure 1). Among all ocean processes, ageostrophic advection and vertical mixing (diffusion and entrainment) are the most important factors in modifying the SST tendency response. The SST tendency response to ARs varies spatially. For example, in coastal California, the driver of enhanced SST warming is the reduction in ageostrophic advection due to anomalous southerly winds. Moreover, there is a large region where the SST shows a warming response to ARs due to the overall reduction in the total clouds and subsequent increase in total incoming shortwave radiation. This work adds tangible understanding to the Subseasonal to Seasonal Prediction of Extreme Weather priority area in CW3E’s Strategic Plan, where SST prediction is a crucial boundary condition.

Figure 1. (Figure 5 from Hsu et al. 2024). The response of sea surface temperature (SST) tendency to atmospheric rivers (ARs), decomposed into distinct contributing processes. Variables shown are: (a) Θ̅̇_loc, (b) Θ̅̇_ocn, (c) Θ̅̇_adv, (d) Θ̅̇_mix, (e) Θ̅̇_det, (f) Θ̅̇_sfc, (g) Θ̅̇_sw, (h) Θ̅̇_lw, (i) Θ̅̇_sen, and (j) Θ̅̇_lat. Each panel shows the mean of the composite anomalous SST tendency associated with a particular process (shading) and its standard deviation (contours). Dotted areas show response regions that pass the significance test (p = 0.05). For each grid point, we compute the mean and standard deviation by grouping all of the AR day data. The significance test is tested against the climatology group, i.e., every single day. The anomalous SST tendencies Θ̅̇_dilu and Θ̅̇_hdiff are very small such that they are not shown.

Hsu, T.-Y., Mazloff, M. R., Gille, S. T., Freilich, M. A., Sun, R., & Cornuelle, B. D. (2024). Response of sea surface temperature to atmospheric rivers. Nature Communications, 15, 508. https://doi.org/10.1038/s41467-024-48486-9