Schulien Jennifer A, Behrenfeld Michael J, Hair Johnathan W, Hostetler Chris A, Twardowski Michael S
Opt Express. 2017 Jun 12;25(12):13577-13587. doi: 10.1364/OE.25.013577.
Passive ocean observing sensors are unable to detect subsurface structure in ocean properties, resulting in errors in water column integrated phytoplankton biomass and net primary production (NPP) estimates. Active lidar (light detection and ranging) sensors make quantitative measurements of depth-resolved backscatter (bbp) and diffuse light attenuation (Kd) coefficients in the ocean and can provide critical measurements for biogeochemical models. Sub-surface phytoplankton biomass, light, chlorophyll, and NPP fields were characterized using both in situ measurements and coincident airborne high spectral resolution lidar (HSRL-1) measurements collected as part of the SABOR (Ship-Aircraft Bio-Optical Research) field campaign. We found that depth-resolved data are critical for calculating phytoplankton stocks and NPP, with improvements in NPP estimates up to 54%. We observed strong correlations between coincident HSRL-1 and in situ IOP measurements of both bbp (r = 0.94) and Kd (r = 0.90).
被动海洋观测传感器无法探测海洋属性中的次表层结构,导致水柱综合浮游植物生物量和净初级生产力(NPP)估计出现误差。主动激光雷达(光探测和测距)传感器可对海洋中深度分辨的后向散射(bbp)和漫射光衰减(Kd)系数进行定量测量,并能为生物地球化学模型提供关键测量数据。利用现场测量数据以及作为SABOR(船-机生物光学研究)实地考察一部分所收集的同步机载高光谱分辨率激光雷达(HSRL-1)测量数据,对次表层浮游植物生物量、光照、叶绿素和NPP场进行了表征。我们发现,深度分辨数据对于计算浮游植物存量和NPP至关重要,NPP估计的改进幅度高达54%。我们观察到,同步的HSRL-1测量数据与现场bbp(r = 0.94)和Kd(r = 0.90)的原位光学特性测量数据之间存在很强的相关性。