4. Conclusions
This study is among the first to observe temporal variation of DOC quantity and quality in precipitation across a range of precipitation events and climatic seasons. Precipitation DOC varied considerably between seasons and individual events for precipitation sampled sequentially over a 1.3-year period. Seasonally, summer and spring storms had much higher amounts of DOC and optically active organic matter than winter, but DOC in winter and spring precipitation was more aromatic than in summer. Higher DOC concentrations appear to be associated with weather types that favor air advection in such a way that cold frontal systems, on average, delivered more than warm/stationary fronts and northeasters. This may have implications for the delivery of DOC to ecosystems with precipitation in the future when changes in regional climate affect the frequency of occurrence of different weather types (Christensen et al., 2013). Similarly, rates of DOC deposition indicated that organic carbon loadings to the watershed in precipitation are highest in summer and lowest in winter. Results from exploratory modeling suggest that precipitation DOC concentrations are affected by storm properties (e.g., characterized here by duration and convective fraction); emission sources (antecedent dry period, air temperature); and atmospheric chemical transformations (e.g., concentrations of ground-level ozone and precipitation nitrogen, as well as by spectral properties indicating molecular weight and abundance of light-absorbing organic matter). Collectively such factors explained more than 60% of the variability observed in DOC concentrations among the storm events sampled. In addition to the emission sources, there are multiple external processes related to meteorology and atmospheric dynamics that likely work in synergy to influence the quantity and chemical properties of DOC in precipitation. Further understanding of how changes in these interactions affect wet atmospheric deposition of organics in response to climate fluctuations is important for improving the predictive models of atmospheric composition (NRC, 2016). Future studies should be directed toward quantifying the suite of factors and source-receptor relationships that control inter-event variability (from storm to storm) and intraevent variability (during storms).