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Variations in the summer oceanic pCO2 and carbon sink in Prydz Bay using the self-organizing map analysis approach

机译:使用自组织地图分析方法,夏季海洋PCO2和Prydz湾碳汇的变化

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This study applies a neural network technique to produce maps of oceanic surface pCO2 in Prydz Bay in the Southern Ocean on a weekly 0.1° longitude×0.1° latitude grid based on in situ measurements obtained during the 31st CHINARE cruise from February to early March?2015. This study area was divided into three regions, namely, the “open-ocean” region, “sea-ice” region and “shelf” region. The distribution of oceanic pCO2 was mainly affected by physical processes in the open-ocean region, where mixing and upwelling were the main controls. In the sea-ice region, oceanic pCO2 changed sharply due to the strong change in seasonal ice. In the shelf region, biological factors were the main control. The weekly oceanic pCO2 was estimated using a self-organizing map (SOM) with four proxy parameters (sea surface temperature, chlorophyll?a concentration, mixed Layer Depth and sea surface salinity) to overcome the complex relationship between the biogeochemical and physical conditions in the Prydz Bay region. The reconstructed oceanic pCO2 data coincide well with the in situ pCO2 data from SOCAT, with a root mean square error of 22.14μatm. Prydz Bay was mainly a strong CO2 sink in February?2015, with a monthly averaged uptake of 23.57±6.36TgC. The oceanic CO2 sink is pronounced in the shelf region due to its low oceanic pCO2 values and peak biological production.
机译:本研究适用神经网络技术在2月31日至3月初31日至3月初的31°Chinare巡航期间获得的每周0.1°经度×0.1°纬度网格在南海的海洋地面PCO2在南海洋的海洋表面PCO2的地图。2015年。该研究区分为三个地区,即“开阔海洋”区域,“海冰”区域和“货架”区域。海洋PCO2的分布主要受开放海域的物理过程的影响,其中混合和升值是主要对照。在海冰区,由于季节性冰的强劲变化,海洋PCO2变化了大幅变化。在货架区域中,生物因素是主要控制。每周海洋PCO2使用自组织地图(SOM)估计,具有四个代理参数(海面温度,叶绿素?浓度,混合层深度和海表面盐度),以克服生物地球化学和物理条件之间的复杂关系Prydz湾区。重建的海洋PCO2数据与来自SOCAT的原位PCO2数据相一致,具有22.14μATm的根均方误差。 Prydz Bay主要是2月份的强大二氧化碳水槽2015年,每月平均摄取为23.57±6.36TGC。由于其低海洋PCO2值和峰生物生产,海洋二氧化碳水槽在货架区域中发音。

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