Interannual Variations in Aerosol Sources and Their Impact on Orographic Precipitation over California’s Central Sierra Nevada
Friday, 19 December 2014
Aerosols that serve as cloud condensation nuclei (CCN) and ice nuclei (IN) have the potential to profoundly influence precipitation processes. Furthermore, changes in orographic precipitation have broad implications for reservoir storage and flood risks. As part of the CalWater I field campaign (2009-2011), the impacts of aerosol sources on precipitation were investigated in the California Sierra Nevada Mountains. In 2009, the precipitation collected on the ground was influenced by both local biomass burning and long-range transported dust and biological particles, while in 2010, by mostly local sources of biomass burning and pollution, and in 2011 by mostly long-range transport of dust and biological particles from distant sources. Although vast differences in the sources of residues were observed from year-to-year, dust and biological residues were omnipresent (on average, 55% of the total residues combined) and were associated with storms consisting of deep convective cloud systems and larger quantities of precipitation initiated in the ice phase. Further, biological residues were dominant during storms with relatively warm cloud temperatures (up to ‑15°C), suggesting biological components were more efficient IN than mineral dust. On the other hand, when precipitation quantities were lower, local biomass burning and pollution residues were observed (on average 31% and 9%, respectively), suggesting these residues potentially served as CCN at the base of shallow cloud systems and that lower level polluted clouds of storm systems produced less precipitation than non-polluted (i.e., marine) clouds. The direct connection of the sources of aerosols within clouds and precipitation type and quantity can be used in models to better assess how local emissions versus long-range transported dust and biological aerosols play a role in impacting regional weather and climate, ultimately with the goal of more accurate predictive weather forecast models and water resource management.