Performance of primary production algorithm using absorption coefficient of phytoplankton in the Pacific Arctic
Performance of primary production algorithm using absorption coefficient of phytoplankton in the Pacific Arctic
复制标题
使用北极太平洋浮游植物吸收系数的初级生产算法的性能
DOI：
10.1007/s10872-022-00646-5
复制
发表时间：
2022
影响因子：
2.3
通讯作者：
Watanabe Yutaka W.
中科院分区：
文献类型：
--
作者：
Futsuki Ryosuke;Hirawake Toru;Fujiwara Amane;Waga Hisatomo;Kikuchi Takashi;Nishino Shigeto;Isada Tomonori;Suzuki Koji;Watanabe Yutaka W.
北极的光照条件、日照时长和入射太阳光的量随季节变化很大。基于吸收的初级生产力(PP)模型包含光吸收系数和光合作用有效辐射(PAR)；然而，在北冰洋还没有研究算法对这些参数的敏感性。因此，我们评估了三种基于吸收的垂直广义生产模式(VGPM)的性能和敏感性，该模式与北极太平洋地区夏季和秋季获得的现场和卫星获取的光学和PP数据有关。在VGPM的基础上，研究了基于吸收的算法，以评估它们的性能和灵敏度。这些算法最初是根据北极太平洋浮游植物的吸收系数和浮游植物吸收的辐射(光子)估计真光层中的日浮游植物PP。所有方法对现场输入参数和现场遥感反射率的偏差都很小。当使用卫星数据作为输入时，使用ARP进行的PPeu估计显示出很小的偏差。即使使用现场数据作为输入，无偏均方根差也不小，这表明仅从光学参数估计量子产率存在固有问题。灵敏度分析表明，不仅吸收系数中的误差，而且PAR中的误差也影响PPEu估计，特别是在使用ARP时。该模型使用了应用于第二代全球成像仪数据的吸收系数，在天空条件多变的太平洋北极地区提供了令人满意的PPeu估计。
Light condition, day length, and amount of incident sunlight vary widely with season in the Arctic. Absorption-based primary production (PP) models incorporate light absorption coefficients and photosynthetically active radiation (PAR); however, algorithm sensitivity to such parameters has not been investigated in the Arctic Ocean. Therefore, we assessed the performance and sensitivity of the vertical generalized production model (VGPM) modified with three absorption-based approaches in relation to in situ and satellite-derived optical and PP data acquired in summer and autumn in the Pacific Arctic region. Based on the VGPM, the absorption-based algorithms, which were developed originally to estimate daily phytoplankton PP in the euphotic layer (PPeu) from the absorption coefficient of phytoplankton and the absorbed radiation (photons) by phytoplankton (ARP) in the Pacific Arctic, were investigated to assess their performance and sensitivity. All approaches exhibited little bias for in situ input parameters and in situ remote sensing reflectance. ThePPeuestimation using ARP showed small biases when using satellite data as input. The unbiased root mean square difference was not small, even when using in situ data as input, which suggests inherent problems regarding estimation of quantum yield from only optical parameters. Sensitivity analysis revealed that error not only in the absorption coefficient but also in PAR influencesPPeuestimation, particularly when using ARP. The model using the absorption coefficients applied to Second-generation Global Imager data provided a satisfactory estimation ofPPeuin the Pacific Arctic where sky conditions can be variable.