NOAA National Environmental Satellite, Data, and Information Service, Center for Satellite Applications and Research, E/RA3, 5830 University Research Ct., College Park, MD, 20740, USA.
CIRA at Colorado State University, Fort Collins, CO, USA.
Sci Rep. 2021 Nov 18;11(1):22517. doi: 10.1038/s41598-021-01880-5.
The global daily gap-free chlorophyll-a (Chl-a) data derived using the data interpolating empirical orthogonal functions (DINEOF) technique from observations of the Visible Infrared Imaging Radiometer Suite (VIIRS) in 2020 and the in situ measurements at the Tropical Ocean Atmosphere (TAO) moorings are used to characterize and quantify the biological variability modulated by the tropical instability wave (TIW). Our study aims to understand how ocean physical processes are linked to biological variability. In this study, we use the TAO in situ measurements and the coincident VIIRS Chl-a data to identify the mechanism that drives ocean biological variability corresponding to the TIW. Satellite observations show that the TIW-driven Chl-a variability stretched from 90°W to 160°E in the region. The enhanced Chl-a pattern propagated westward and moderately matched the cooler sea surface temperature (SST) patterns in the Equatorial Pacific Ocean. In fact, the Chl-a variation driven by the TIW is about ± 30% of mean Chl-a values. Furthermore, the time series of Chl-a at 140°W along the equator was found to be in phase with sea surface salinity (SSS) at 140°W along the equator at the TAO mooring since late May 2020. The cross-correlation coefficients with the maximum magnitude between Chl-a and SST, Chl-a and SSS, and Chl-a and dynamic height were -0.46, + 0.74, and -0.58, respectively, with the corresponding time lags of about 7 days, 1 day, and 8 days, respectively. The different spatial patterns of the cooler SST and enhanced Chl-a are attributed to the phase difference in Chl-a and SST. Indeed, a Chl-a peak normally coincided with a SSS peak and vice versa. This could be attributed to the consistency in the change in nutrient concentration with respect to the change of SSS. The vertical distributions of the temperature and salinity at 140°W along the equator reveal that the TIW leads to changes in both salinity and nutrient concentrations in the sea surface, and consequently drives the Chl-a variability from late May until the end of the year 2020.
利用数据插值经验正交函数（DINEOF）技术从 2020 年可见红外成像辐射计套件（VIIRS）观测和热带海洋大气（TAO）系泊的现场测量中得出的全球每日无间隙叶绿素 a（Chl-a）数据，用于描述和量化由热带不稳定波（TIW）调制的生物可变性。我们的研究旨在了解海洋物理过程如何与生物可变性相关联。在这项研究中，我们使用 TAO 现场测量和同时的 VIIRS Chl-a 数据来识别驱动与 TIW 对应的海洋生物可变性的机制。卫星观测表明，TIW 驱动的 Chl-a 可变性在该区域从 90°W 延伸到 160°E。增强的 Chl-a 模式向西传播，与赤道太平洋较冷的海面温度（SST）模式中度匹配。事实上，由 TIW 驱动的 Chl-a 变化大约是平均 Chl-a 值的±30%。此外，发现自 2020 年 5 月下旬以来，赤道上 140°W 的 Chl-a 时间序列与赤道上 140°W 的海表面盐度（SSS）呈同相。Chl-a 与 SST、Chl-a 与 SSS 和 Chl-a 与动力高度之间的最大幅度的互相关系数分别为-0.46、+0.74 和-0.58，相应的时间滞后分别约为 7 天、1 天和 8 天。较冷的 SST 和增强的 Chl-a 的不同空间模式归因于 Chl-a 和 SST 的相位差。实际上，Chl-a 峰值通常与 SSS 峰值重合，反之亦然。这可能归因于营养物浓度随 SSS 变化的一致性。赤道上 140°W 的温度和盐度的垂直分布表明，TIW 导致海面盐度和营养物浓度的变化，从而从 5 月下旬到 2020 年底驱动 Chl-a 可变性。
