A daily gridded dataset of nitrogen wet deposition over East Asia for 2011 to 2016 based on multisource observation-model fusion
Abstract. East Asia is a global hotspot of atmospheric nitrogen deposition, where episodic wet-deposition pulses can strongly affect ecosystem nutrient inputs and acidification. However, most datasets aggregate observations to monthly or annual scales, masking short-lived high-load deposition pulses from individual rainstorms and hindering the quantification of event-scale deposition dynamics. Here we develop a 45 km gridded daily dataset of oxidized and reduced nitrogen wet deposition over East Asia for 2011–2016. Ground-based measurements from the National Acid Deposition Monitoring Network (NADMN) and the Acid Deposition Monitoring Network in East Asia (EANET), satellite precipitation retrievals, and chemical transport simulations are integrated via a two-step framework. Precipitation adjustment constrains monthly deposition totals and reconstructs event-based daily deposition distributions, followed by measurement–model fusion to assimilate wet-deposition observations. Compared with the raw model output, the dataset reduces oxidized-nitrogen overestimation and better agreement with the observed spread of reduced-nitrogen wet deposition. Station-held-out validation shows improved identification of high-deposition days, with correct classification of the highest observed deposition quartile increasing by 12.7 and 20.8 percentage points for oxidized and reduced nitrogen, respectively. The daily dataset helps identify high-deposition periods and assess when and where short-lived nitrogen inputs occur and how much they contribute to cumulative deposition. It also supports regional nitrogen-budget analyses and model evaluation. However, uneven observational coverage and remaining errors in daily estimates warrant caution when interpreting individual events, particularly in sparsely monitored regions. The NetCDF data are available at https://doi.org/10.57760/sciencedb.015vd (Yang et al., 2026).