Anthropogenic Aerosols Contribute to the Recent Decline in Precipitation Over the U.S. Southwest

Abstract

The winter‐spring precipitation over the Southwestern United States (SWUS) decreased since 1980. It is frequently attributed to Pacific internal decadal variability, but recent studies found anthropogenic aerosols (AA) can also induce a transition to a negative Pacific Decadal Variability (PDV) phase. We revisit the attribution of SWUS drying by quantifying the contributions of anthropogenically forced decadal Pacific Sea Surface Temperatures (SSTs). Applying a low‐frequency component analysis to observations, Community Earth System Model version 2 (CESM2) all‐forcings and single‐forcing large ensembles, we find up to 42% of the observed precipitation trend to be related to the AA‐induced negative PDV‐like pattern, which is driven by the emission shift from the Western to the Eastern Hemisphere. In CESM2, other radiative forcings counteract the influence of AA, but it remains unclear whether the model correctly simulates this balance. This implies that the near‐future trajectories of these forcings, in particular Asian aerosols, are important for projections of SWUS precipitation.

Potential Near‐Term Wetting of the Southwestern United States if the Eastern and Central Pacific Cooling Trend Reverses

“…While AO-GCMs predicted a warming SST trend in the Central and East Pacific, the region instead experienced a cooling SST trend from 1970 to 2014 (e.g., Coats & Karnauskas, 2017;Seager et al, 2019), which potentially led to the observed megadrought in the SWUS due to a decrease in precipitation (Delworth et al, 2015;Seager & Hoerling, 2014). The cooling of the Central and East Pacific not simulated by AO-GCMs may have been caused by a forced response to greenhouse gas emissions (Coats & Karnauskas, 2017;Heede et al, 2020), a forced response to aerosols (Heede & Fedorov, 2021;Kuo et al, 2023), internal variability in the climate system (Olonscheck et al, 2020;Watanabe et al, 2021), missing or poorly simulated teleconnections in climate models (e.g., Y. Dong et al, 2022;Kang et al, 2023;Kim et al, 2022), or a combination of these factors.…”