首页> 外文期刊>Journal of Geophysical Research, C. Oceans: JGR >An inversion model based on salinity and remote sensing reflectance for estimating the phytoplankton absorption coefficient in the Saint Lawrence Estuary
【24h】

An inversion model based on salinity and remote sensing reflectance for estimating the phytoplankton absorption coefficient in the Saint Lawrence Estuary

机译:基于盐度和遥感反射率的反演模型估计圣劳伦斯河口浮游植物的吸收系数

获取原文
获取原文并翻译 | 示例
       

摘要

The inversion of individual inherent optical properties (IOPs) is very challenging in optically complex waters and within the violet spectral range (i.e., 380–450 nm) due to the strong light attenuation caused by chromophoric dissolved organic matter, nonalgal particulates, and phytoplankton. Here we present a technique to better discriminate light absorption contributions due to phytoplankton based on a hybrid model (QAA-hybrid) that combines regional Saint Lawrence System estimates of IOPs derived from a quasi-analytical algorithm (hereafter QAA-SLE) and empirical relationships between salinity and IOPs. Preliminary results in the Saint Lawrence System during May 2000 and April 2001 showed that QAA-hybrid estimates of phytoplankton absorption coefficient at 443 nm have a smaller bias with respect to in situ measurements (root-mean-square deviation, RMSD=0.156) than those derived from QAA-SLE (RMSD=0.341). These results were valid for surface waters (i.e., 0–5 m depth) of the lower estuary with a salinity and chlorophyll-a concentration range of 22–28 psu and 2.1–13.8 mg m~(-3), respectively.
机译:由于发色团溶解的有机物,非藻类颗粒和浮游植物引起的强烈光衰减,在光学复杂的水中和在紫光光谱范围内(即380-450 nm),单个固有光学特性(IOP)的转换非常具有挑战性。在这里,我们提出了一种基于混合模型(QAA混合)的,能够更好地区分浮游植物光吸收作用的技术,该模型结合了从拟解析算法(以下称QAA-SLE)得到的IOP的区域圣劳伦斯系统估计值以及两者之间的经验关系盐度和IOP。 Saint Lawrence系统在2000年5月和2001年4月的初步结果表明,QAA混合估计值在443 nm处的浮游植物吸收系数相对于原位测量值具有较小的偏差(均方根偏差,RMSD = 0.156)。源自QAA-SLE(RMSD = 0.341)。这些结果对于盐度和叶绿素浓度范围分别为22-28 psu和2.1-13.8 mg m〜(-3)的下河口地表水(即0-5 m深度)有效。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号