Dataset: Numerical experiments on the sensitivity of Chesapeake Bay N2O cycles to climate warming and nutrient reductions and the associated code and input files

A three-dimensional numerical model of the Chesapeake Bay (East Coast of the United States) was used to simulate the N2O cycle. The model is an implementation of the Regional Ocean Modeling System (ROMS, https://www.myroms.org/) with modules for sediment resuspension (Warner et al. 2008) and biogeochemistry (St-Laurent et al. 2020), with the latest addition of N2O as a separate state variable. It simulates hydrodynamics and biogeochemistry with a horizontal resolution of approximately 1.8 km and 20 topography-following vertical levels. Physical forcings include the ERA5 reanalysis (3-hourly) and tidal constituents from Szpilka et al. (2016). The dataset includes four primary numerical experiments designed to highlight the sensitivity of the Chesapeake Bay N2O cycle to climate warming and terrestrial nutrient management. The reference run was conducted for the year 2016, which represents a normal streamflow year. Three sensitivity experiments retained the same model forcings as in the reference run, except for one of the following combinations: Decreased atmospheric N2O concentrations, decreased atmospheric temperature, and increased riverine nitrate and organic nitrogen concentrations to 1986 levels (Test1986). Decreased atmospheric N2O concentrations and increased riverine nitrate and organic nitrogen concentrations to 1986 levels (Test1986warming). Increased atmospheric N2O concentrations, increased atmospheric temperature, and decreased riverine nitrate and organic nitrogen concentrations to 2050 levels (Test2050). The file Results_for_plot.zip includes model outputs used to generate figures, including monthly Bay-wide N2O distribution and the daily N2O budget integrated over the Bay. In addition to the model outputs, this archive contains the computer code (ROMS_Code.zip) and the input files necessary to reproduce the model results (input_files.zip). The total size of the dataset is approximately 5 GB. References: Scavia, D., Kelly, E. L. A., & Hagy, J. D. (2006). A simple model for forecasting the effects of nitrogen loads on Chesapeake Bay hypoxia. Estuaries and Coasts, 29(4), 674–684. https://doi.org/10.1007/bf02784292 St-Laurent, P., Friedrichs, M. A. M., Najjar, R. G., Shadwick, E. H., Tian, H., & Yao, Y. (2020). Relative impacts of global changes and regional watershed changes on the inorganic carbon balance of the Chesapeake Bay. Biogeosciences, 17(14), 3779–3796. https://doi.org/10.5194/bg-17-3779-2020 Warner, J. C., Sherwood, C. R., Signell, R. P., Harris, C. K., & Arango, H. G. (2008). Development of a three-dimensional, regional, coupled wave, current, and sediment-transport model. Computers & Geosciences, 34(10), 1284–1306. https://doi.org/10.1016/j.cageo.2008.02.012本研究采用美国东海岸切萨皮克湾的三维数值模型模拟氧化亚氮（N₂O）循环。该模型基于区域海洋建模系统（Regional Ocean Modeling System, ROMS，https://www.myroms.org/）开发，集成了泥沙再悬浮模块（Warner等，2008）与生物地球化学模块（St-Laurent等，2020），并最新将N₂O作为独立状态变量纳入模型框架。模型以约1.8 km的水平分辨率与20个地形跟随型垂直层数，模拟水动力与生物地球化学过程。模型的物理强迫场采用逐3小时的ERA5再分析数据，以及Szpilka等人（2016）提供的潮汐组分。 本数据集包含四项核心数值试验，旨在探究切萨皮克湾N₂O循环对气候变暖与陆地养分管理的敏感性。基准试验以正常径流年份2016年为模拟时段。其余三项敏感性试验均沿用基准试验的物理强迫场，仅对以下一组参数组合进行调整： 1. 降低大气N₂O浓度、降低大气温度，并将河流输入的硝酸盐与有机氮浓度提升至1986年水平（Test1986）； 2. 降低大气N₂O浓度，并将河流输入的硝酸盐与有机氮浓度提升至1986年水平（Test1986warming）； 3. 提升大气N₂O浓度、升高大气温度，并将河流输入的硝酸盐与有机氮浓度降低至2050年水平（Test2050）。 Results_for_plot.zip压缩包包含用于生成可视化图表的模型输出数据，涵盖全湾逐月N₂O分布与全湾逐日N₂O收支总量。除模型输出数据外，本归档包还包含复现模型结果所需的代码文件（ROMS_Code.zip）与输入参数文件（input_files.zip）。本数据集总容量约为5 GB。 参考文献： Scavia, D., Kelly, E. L. A., & Hagy, J. D. (2006). 预测氮负荷对切萨皮克湾低氧影响的简化模型. 《河口与海岸》, 29(4), 674–684. https://doi.org/10.1007/bf02784292 St-Laurent, P., Friedrichs, M. A. M., Najjar, R. G., Shadwick, E. H., Tian, H., & Yao, Y. (2020). 全球变化与区域流域变化对切萨皮克湾无机碳平衡的相对影响. 《生物地球科学》, 17(14), 3779–3796. https://doi.org/10.5194/bg-17-3779-2020 Warner, J. C., Sherwood, C. R., Signell, R. P., Harris, C. K., & Arango, H. G. (2008). 三维区域耦合波浪、海流与泥沙输运模型的构建. 《计算机与地学》, 34(10), 1284–1306. https://doi.org/10.1016/j.cageo.2008.02.012