Evaluating CAM‐Chem Modeled Atmospheric Wet Deposition With Observed Long‐Term Records

Abstract Accurate modeling of carbon, nitrogen, and sulfur wet deposition (i.e., through rain, snow, or graupel) flux is important for characterizing and quantifying the role of deposition in global biogeochemical cycles. The simulation of wet deposition of solutes, alongside precipitation rates, in the Community Atmosphere Model version 6 with Chemistry (CAM‐chem) has had limited previous evaluation leaving an opportunity to determine its accuracy in simulating precipitation chemistry. Here, we assessed the accuracy of 1° resolution CAM‐chem outputs of wet deposition over the contiguous U.S. (CONUS) from 2002 to 2022, comparing model outputs for observed equivalents of sulfate (SO 4 2− ), ammonium (NH 4 + ), nitrate (NO 3 − ), and dissolved organic carbon (DOC) wet deposition with long‐term records collected at hundreds of stations across CONUS. After evaluating the temporal, spatial, and quantile differences between modeled and observed wet deposition fluxes, we find the model captures long‐term and seasonal patterns but consistently overestimates NO 3 − , while underestimating SO 4 2− , NH 4 + , and DOC wet deposition fluxes. Model‐measurement agreement improved at higher deposition flux quantiles and site‐specific alignment was strongest for NO 3 − , and moderate for SO 4 2− and NH 4 + . Low model‐measurement agreement for DOC comparisons is likely due to focusing on aerosol contributions. Higher resolution model simulations (∼14 km) resulted in equivalent comparisons as the 1° model, suggesting that wet deposition processes are represented consistently across different model simulations and spatial resolution is not the main driver of inaccuracies of model deposition. Benchmarking modeled deposition outputs is crucial for evaluating CAM‐chem's performance and its utility in understanding landscape drivers of deposition chemistry within Earth system models.