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Parameter optimisation of a marine ecosystem model at two contrasting stations in the Sub-Antarctic Zone

机译:次南极地区两个对比站海洋生态系统模型的参数优化

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SeaWiFS surface chlorophyll estimates in the Sub-Antarctic Zone show low concentrations south west of Tasmania and high concentrations south east of Tasmania. Data assimilation experiments were performed using simulated annealing to obtain parameter estimates of a simple nitrogen based mixed-layer marine ecosystem model at two locations in this region (station PI at 140°E, 46.5°S and station P3 at 152°E, 45.5°S). The assimilation methods and parameter sensitivities are assessed in a twin experiment. This assessment determined that inversion method was successful at estimating the correct parameters but that only a sub-set of the model parameters can be uniquely determined using chlorophyll a observations. An analysis of parameter uncertainties shows at both stations accurate parameterisations of phytoplankton growth and zooplankton mortality, and the biological recycling processes are required to realistically model chlorophyll. Applying the inversion method to the climatological SeaWiFS chlorophyll a observations from the two sites we estimate model parameters at these two sites. The most significant differences in parameters between the two stations are the parameters relating to phytoplankton growth and zooplankton mortality. The difference in growth parameters results in spring time productivity estimates of esgrng C m~(-2) d~(-1) at PI and 203 mg C m~(-2) d~(-1) at P3. In situ estimates from the SAZ-Sense cruise do not support such dramatic differences in primary production between the two stations. We conclude that the same ecosystem model structure is not applicable at both stations and we need additional processes at P3 to reproduce the observed seasonality of phytoplankton and the observed primary productivity. We hypothesise that the missing processes in the ecosystem model at P3 are iron limitation of phytoplankton and the seasonal variations in atmospheric deposition of iron.
机译:南极次区域的SeaWiFS表层叶绿素估计值显示塔斯马尼亚西南部浓度低,塔斯马尼亚东南部浓度高。使用模拟退火进行数据同化实验,以获取该区域两个位置(140°E,46.5°S的PI站和152°E,45.5°的P3站)的基于氮的简单混合层海洋生态系统模型的参数估计。 S)。在一个双生实验中评估了同化方法和参数敏感性。该评估确定了反演方法可以成功估计正确的参数,但是使用叶绿素a观测值只能唯一确定模型参数的子集。对参数不确定性的分析表明,在两个站点上,浮游植物生长和浮游动物死亡率的参数设置都是准确的,并且需要实际的生物循环过程来模拟叶绿素。将反演方法应用于气候SeaWiFS叶绿素a在两个站点的观测值,我们估计了这两个站点的模型参数。两个站之间参数的最显着差异是与浮游植物生长和浮游动物死亡率有关的参数。生长参数的差异导致春季的生产力估计值在PI时达到C m〜(-2)d〜(-1),在P3时达到203 mg C m〜(-2)d〜(-1)。 SAZ-Sense巡航的原位估算不支持这两个站之间初级生产的巨大差异。我们得出的结论是,相同的生态系统模型结构不适用于两个站,我们需要在P3进行额外的处理才能重现观测到的浮游植物的季节性和观测到的初级生产力。我们假设在P3的生态系统模型中缺失的过程是浮游植物的铁限制和铁在大气中的季节性变化。

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