Sensitivity of Modeled CO2 Air-Sea Flux in a Coastal Environment to Surface Temperature Gradients, Surfactants, and Satellite Data Assimilation
Sensitivity of Modeled CO2 Air-Sea Flux in a Coastal Environment to Surface Temperature Gradients, Surfactants, and Satellite Data Assimilation
复制标题
沿海环境中模拟的二氧化碳海气通量对地表温度梯度、表面活性剂和卫星数据同化的敏感性
DOI：
10.3390/rs12122038
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
G. Tilstone
中科院分区：
文献类型：
--
作者：
Ricardo Torres;Y. Artioli;V. Kitidis;S. Ciavatta;M. Ruíz;J. Shutler;L. Polimene;V. Martinez;C. Widdicombe;E. Woodward;T. Smyth;J. Fishwick;G. Tilstone
这项工作评估的敏感性CO2海气交换在沿海站点四个不同的模型系统配置的一维耦合水动力生态系统模型GOTM-ERSEM，对确定关键动态的相关性时，专门解决量化的海气CO2交换。欧洲海区域生态系统模型（ERSEM）是一个基于生物量和功能群的生态地球化学模型，包括一个综合的碳酸盐系统，并明确模拟溶解有机碳、溶解无机碳和有机质的产生。该模型在L4海岸站（普利茅斯以南4海里，北纬50° 15.00 '，西经4° 13.02'，水深51米）实施。通过2008-2009年西海岸观测站的活动，使用在L4定期收集的1500多个水文和生物化学观测结果对模型性能进行了评估。除了参考模拟（A）之外，我们还进行了三个不同的实验，以研究碳酸盐系统和模拟的海气通量对（B）海表温度（SST）日周期以及近地表垂直梯度的敏感性，（C）气体交换的生物抑制和（D）使用卫星地球观测数据的数据同化。参考模拟很好地捕捉了物理环境（模拟SST与观测值的相关性等于0.94，p > 0.95）。总体而言，该模型捕捉到了大多数地球化学变量的季节性信号，包括CO2的海气通量和初级生产力，并可以捕捉到一些季节内的变化和短暂的水华。该模型正确地再现了2008-2009年两年运行中营养盐（硅酸盐、硝酸盐和磷酸盐的相关性> 0.80）、表面叶绿素a（相关性> 0.43）和总生物量（相关性> 0.7）的季节性。该模型很好地模拟了DIC的浓度，pH值和水中CO2分压（pCO 2）与0.4-0.5之间的相关性。模型结果表明，L4是一个弱的CO2净源（0.3-1.8 molCm−2 year−1）。三个敏感性实验的结果表明，无论是解决近地面的温度廓线和同化的表面叶绿素a显着影响模拟的技能在L4和所有的碳酸盐化学相关的变量的土壤地球化学。这些结果表明，我们的预测能力的CO2海气通量在陆架海环境和气候模拟的影响，应考虑两个模型的改进，以减少不确定性和误差，在任何未来的气候预测。
This work evaluates the sensitivity of CO2 air–sea gas exchange in a coastal site to four different model system configurations of the 1D coupled hydrodynamic–ecosystem model GOTM–ERSEM, towards identifying critical dynamics of relevance when specifically addressing quantification of air–sea CO2 exchange. The European Sea Regional Ecosystem Model (ERSEM) is a biomass and functional group-based biogeochemical model that includes a comprehensive carbonate system and explicitly simulates the production of dissolved organic carbon, dissolved inorganic carbon and organic matter. The model was implemented at the coastal station L4 (4 nm south of Plymouth, 50°15.00’N, 4°13.02’W, depth of 51 m). The model performance was evaluated using more than 1500 hydrological and biochemical observations routinely collected at L4 through the Western Coastal Observatory activities of 2008–2009. In addition to a reference simulation (A), we ran three distinct experiments to investigate the sensitivity of the carbonate system and modeled air–sea fluxes to (B) the sea-surface temperature (SST) diurnal cycle and thus also the near-surface vertical gradients, (C) biological suppression of gas exchange and (D) data assimilation using satellite Earth observation data. The reference simulation captures well the physical environment (simulated SST has a correlation with observations equal to 0.94 with a p > 0.95). Overall, the model captures the seasonal signal in most biogeochemical variables including the air–sea flux of CO2 and primary production and can capture some of the intra-seasonal variability and short-lived blooms. The model correctly reproduces the seasonality of nutrients (correlation > 0.80 for silicate, nitrate and phosphate), surface chlorophyll-a (correlation > 0.43) and total biomass (correlation > 0.7) in a two year run for 2008–2009. The model simulates well the concentration of DIC, pH and in-water partial pressure of CO2 (pCO2) with correlations between 0.4–0.5. The model result suggest that L4 is a weak net source of CO2 (0.3–1.8 molCm−2 year−1). The results of the three sensitivity experiments indicate that both resolving the temperature profile near the surface and assimilation of surface chlorophyll-a significantly impact the skill of simulating the biogeochemistry at L4 and all of the carbonate chemistry related variables. These results indicate that our forecasting ability of CO2 air–sea flux in shelf seas environments and their impact in climate modeling should consider both model refinements as means of reducing uncertainties and errors in any future climate projections.
影响因子：
2.3
作者：
Kitidis, Vassilis;Hardman-Mountford, Nicholas J.;Smyth, Timothy J.
通讯作者：
Smyth, Timothy J.
影响因子：
4.1
作者：
Morvan K. Barnes;G. Tilstone;D. Suggett;C. Widdicombe;J. Bruun;V. Martínez-Vicente;T. Smyth
通讯作者：
Morvan K. Barnes;G. Tilstone;D. Suggett;C. Widdicombe;J. Bruun;V. Martínez-Vicente;T. Smyth
ERSEM 15.06：海洋生物地球化学和低营养级生态系统动态的通用模型
DOI：
10.5194/gmdd-8-7063-2015
发表时间：
2015
期刊：
--
影响因子：
--
作者：
Butenschön M
通讯作者：
Butenschön M