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Patterns in the temporal complexity of global chlorophyll concentration

Earth Sciences

Patterns in the temporal complexity of global chlorophyll concentration

V. Agarwal, J. Chávez-casillas, et al.

This innovative study by Vitul Agarwal, Jonathan Chávez-Casillas, Keisuke Inomura, and Colleen B. Mouw uncovers intriguing patterns in the temporal variation of chlorophyll-a concentrations across the global ocean using satellite data. A novel metric captures time series complexity, revealing connections between different ocean regions and highlighting the consistency of complexity independent of chl-a magnitude. Discover how these findings enhance global ocean monitoring.

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~3 min • Beginner • English
Abstract
Decades of research have relied on satellite-based estimates of chlorophyll-a concentration to identify oceanographic processes and plan in situ observational campaigns; however, the patterns of intrinsic temporal variation in chlorophyll-a concentration have not been investigated on a global scale. Here we develop a metric to quantify time series complexity (i.e., a measure of the ups and downs of sequential observations) in chlorophyll-a concentration and show that seemingly disparate regions (e.g., Atlantic vs Indian, equatorial vs subtropical) in the global ocean can be inherently similar. These patterns can be linked to the regularity of chlorophyll-a concentration change and the likelihood of anomalous events within the satellite record. Despite distinct spatial changes in decadal chlorophyll-a concentration, changes in time series complexity have been relatively consistent. This work provides different metrics for monitoring the global ocean and suggests that the complexity of chlorophyll-a time series can be independent of its magnitude.
Publisher
Nature Communications
Published On
Feb 19, 2024
Authors
Vitul Agarwal, Jonathan Chávez-Casillas, Keisuke Inomura, Colleen B. Mouw
Tags
chlorophyll-a
time series complexity
global ocean
satellite data
anomalous events
temporal variation
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