O'Reilly John E, Werdell P Jeremy
Retired, NOAA National Marine Fisheries Service, Narragansett, Rhode Island 02882, USA.
NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA.
Remote Sens Environ. 2019 Aug;229:32-47. doi: 10.1016/j.rse.2019.04.021. Epub 2019 May 7.
A high degree of consistency and comparability among chlorophyll algorithms is necessary to meet the goals of merging data from concurrent overlapping ocean color missions for increased coverage of the global ocean and to extend existing time series to encompass data from recently launched missions and those planned for the near future, such as PACE, OLCI, HawkEye, EnMAP and SABIA-MAR. To accomplish these goals, we developed 65 empirical ocean color (OC) maximum band ratio (MBR) algorithms for 25 satellite instruments using the largest available and most globally representative database of coincident chlorophyll and remote sensing reflectances. Excellent internal consistency was achieved across these OC 'Version -7' algorithms, as demonstrated by a median regression slope and coefficient of determination (R) of 0.985 and 0.859, respectively, between 903 pairwise comparisons of OC-modeled chlorophyll. SeaWiFS and MODIS-Aqua satellite-to- match-up results indicated equivalent, and sometimes superior, performance to current heritage chlorophyll algorithms. During the past forty years of ocean color research the violet band (412 nm) has rarely been used in empirical algorithms to estimate chlorophyll concentrations in oceanic surface water. While the peak in chlorophyll-specific absorption coincides with the 443 nm band present on most ocean color sensors, the magnitude of chlorophyll-specific absorption at 412 nm can reach upwards of ~70% of that at 443 nm. Nearly one third of total chlorophyll-specific absorption between 400 and 700 nm occurs below 443 nm, suggesting that bands below 443 nm, such as the 412 nm band present on most ocean color sensors, may also be useful in detecting chlorophyll under certain conditions and assumptions. The 412 nm band is also the brightest band (that is, with the most dominant magnitude) in remotely sensed reflectances retrieved by heritage passive ocean color instruments when chlorophyll is less than ~0.1 mg m, which encompasses ~24% of the global ocean. To attempt to exploit this additional spectral information, we developed two new families of OC algorithms, the OC5 and OC6 algorithms, which include the 412 nm band in the MBR. By using this brightest band in MBR empirical chlorophyll algorithms, the highest possible dynamic range of MBR may be achieved in these oligotrophic areas. The terms oligotrophic, mesotrophic, and eutrophic get frequent use in the scientific literature to designate trophic status; however, quantitative definitions in terms of chlorophyll levels are arbitrarily defined. We developed a new, reproducible, bio-optically based index for trophic status based on the frequency of the brightest, maximum band in the MBR for the OC6_SEAWIFS algorithm, along with remote sensing reflectances from the entire SeaWiFS mission. This index defines oligotrophic water as chlorophyll less than ~0.1 mg m, eutrophic water as chlorophyll above 1.67 mg m and mesotrophic water as chlorophyll between 0.1 and 1.67 mg m. Applying these criteria to the 40-year mean global ocean chlorophyll data set revealed that oligotrophic, mesotrophic, and eutrophic water occupy ~24%, 67%, and 9%, respectively, of the area of the global ocean on average.
叶绿素算法之间需要高度的一致性和可比性,以实现合并来自同步重叠海洋颜色任务的数据以扩大全球海洋覆盖范围的目标,并扩展现有时间序列,使其涵盖来自最近发射的任务以及计划在不久的将来开展的任务(如PACE、OLCI、HawkEye、EnMAP和SABIA-MAR)的数据。为实现这些目标,我们利用最大且最具全球代表性的叶绿素与遥感反射率同步数据库,为25种卫星仪器开发了65种经验海洋颜色(OC)最大波段比(MBR)算法。这些OC“版本-7”算法实现了出色的内部一致性,在903次OC模拟叶绿素的成对比较中,中位数回归斜率和决定系数(R)分别为0.985和0.859,证明了这一点。SeaWiFS和MODIS-Aqua卫星匹配结果表明,其性能与当前传统叶绿素算法相当,有时甚至更优。在过去四十年的海洋颜色研究中,紫光波段(412纳米)很少用于经验算法来估算海洋表层水中的叶绿素浓度。虽然叶绿素特定吸收峰与大多数海洋颜色传感器上的443纳米波段重合,但412纳米处叶绿素特定吸收的幅度可达到443纳米处的约70%以上。在400至700纳米之间,近三分之一的叶绿素特定吸收总量发生在443纳米以下,这表明443纳米以下的波段,如大多数海洋颜色传感器上的412纳米波段,在某些条件和假设下也可能有助于检测叶绿素。当叶绿素小于约0.1毫克/立方米时,412纳米波段也是传统被动海洋颜色仪器反演的遥感反射率中最亮的波段(即幅度最占主导),这一情况覆盖了约24%的全球海洋。为尝试利用这一额外的光谱信息,我们开发了两个新的OC算法家族,即OC5和OC6算法,它们在MBR中纳入了412纳米波段。通过在MBR经验叶绿素算法中使用这个最亮的波段,在这些贫营养区域可能实现MBR的最高动态范围。贫营养、中营养和富营养这些术语在科学文献中经常用于表示营养状态;然而,基于叶绿素水平的定量定义是任意确定的。我们基于OC6_SEAWIFS算法MBR中最亮、最大波段的频率以及整个SeaWiFS任务的遥感反射率,开发了一种新的、可重复的、基于生物光学的营养状态指数。该指数将贫营养水定义为叶绿素小于约0.1毫克/立方米,富营养水定义为叶绿素高于1.67毫克/立方米,中营养水定义为叶绿素在0.1至1.67毫克/立方米之间。将这些标准应用于40年平均全球海洋叶绿素数据集表明,贫营养、中营养和富营养水分别平均占据全球海洋面积的约24%、67%和9%。