Patterns in the temporal complexity of global chlorophyll concentration

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.

Gap-filling of ocean color over the tropical Indian Ocean using Monte-Carlo method

Continuous remote-sensed daily fields of ocean color now span over two decades; however, it still remains a challenge to examine the ocean ecosystem processes, e.g., phenology, at temporal frequencies of less than a month. This is due to the presence of significantly large gaps in satellite data caused by clouds, sun-glint, and hardware failure; thus, making gap-filling a prerequisite. Commonly used techniques of gap-filling are limited to single value imputation, thus ignoring the error estimates. Though convenient for datasets with fewer missing pixels, these techniques introduce potential biases in datasets having a higher percentage of gaps, such as in the tropical Indian Ocean during the summer monsoon, the satellite coverage is reduced up to 40% due to the seasonally varying cloud cover. In this study, we fill the missing values in the tropical Indian Ocean with a set of plausible values (here, 10,000) using the classical Monte-Carlo method and prepare 10,000 gap-filled datasets of ocean color. Using the Monte-Carlo method for gap-filling provides the advantage to estimate the phenological indicators with an uncertainty range, to indicate the likelihood of estimates. Quantification of uncertainty arising due to missing values is critical to address the importance of underlying datasets and hence, motivating future observations.

Seasonal Cycles of Phytoplankton Expressed by Sine Equations Using the Daily Climatology from Satellite-Retrieved Chlorophyll-a Concentration (1997–2019) Over Global Ocean

The global coverage of Chlorophyll-a concentration (Chl-a) has been continuously available from ocean color satellite sensors since September 1997 and the Chl-a data (1997–2019) were used to produce a climatological dataset by averaging Chl-a values at same locations and same day of year. The constructed climatology can remarkably reduce the variability of satellite data and clearly exhibit the seasonal cycles, demonstrating that the growth and decay of phytoplankton recurs with similarly seasonal cycles year after year. As the shapes of time series of the climatology exhibit strong periodical change, we wonder whether the seasonality of Chl-a can be expressed by a mathematic equation. Our results show that sinusoid functions are suitable to describe cyclical variations of data in time series and patterns of the daily climatology can be matched by sine equations with parameters of mean, amplitude, phase, and frequency. Three types of sine equations were used to match the climatological Chl-a with Mean Relative Differences (MRD) of 7.1%, 4.5%, and 3.3%, respectively. The sine equation with four sinusoids can modulate the shapes of the fitted values to match various patterns of climatology with small MRD values (less than 5%) in about 90% of global oceans. The fitted values can reflect an overall pattern of seasonal cycles of Chl-a which can be taken as a time series of biomass baseline for describing the state of seasonal variations of phytoplankton. The amplitude images, the spatial patterns of seasonal variations of phytoplankton, can be used to identify the transition zone chlorophyll fronts. The timing of phytoplankton blooms is identified by the biggest peak of the fitted values and used to classify oceans as different bloom seasons, indicating that blooms occur in all four seasons with regional features. In global oceans within latitude domains (48°N–48°S), blooms occupy approximately half of the ocean (50.6%) during boreal winter (December–February) in the northern hemisphere and more than half (58.0%) during austral winter (June–August) in the southern hemisphere. Therefore, the sine equation can be used to match the daily Chl-a climatology and the fitted values can reflect the seasonal cycles of phytoplankton, which can be used to investigate the underlying phenological characteristics.

Environmental structuring of marine plankton phenology

Seasonal cycles of primary production (phenology) critically influence biogeochemical cycles, ecosystem structure and climate. In the oceans, primary production is dominated by microbial phytoplankton that drift with currents, and show rapid turnover and chaotic dynamics, factors that have hindered understanding of their phenology. We used all available observations of upper-ocean phytoplankton concentration (1995-2015) to describe global patterns of phytoplankton phenology, the environmental factors that structure them, and their relationships to terrestrial patterns. Phytoplankton phenologies varied strongly by latitude and productivity regime: those in high-production regimes were governed by insolation, whereas those in low-production regimes were constrained by vertical mixing. In eight of ten ocean regions, our findings contradict the hypothesis that phytoplankton phenologies are coherent at basin scales. Lastly, the spatial organization of phenological patterns in the oceans was broadly similar to those on land, suggesting an overarching effect of insolation on the phenology of primary producers globally.

Seasonality of North Atlantic phytoplankton from space: impact of environmental forcing on a changing phenology (1998-2012)

Seasonal pulses of phytoplankton drive seasonal cycles of carbon fixation and particle sedimentation, and might condition recruitment success in many exploited species. Taking advantage of long-term series of remotely sensed chlorophyll a (1998-2012), we analyzed changes in phytoplankton seasonality in the North Atlantic Ocean. Phytoplankton phenology was analyzed based on a probabilistic characterization of bloom incidence. This approach allowed us to detect changes in the prevalence of different seasonal cycles and, at the same time, to estimate bloom timing and magnitude taking into account uncertainty in bloom detection. Deviations between different sensors stressed the importance of a prolonged overlap between successive missions to ensure a correct assessment of phenological changes, as well as the advantage of semi-analytical chlorophyll algorithms over empirical ones to reduce biases. Earlier and more intense blooms were detected in the subpolar Atlantic, while advanced blooms of less magnitude were common in the Subtropical gyre. In the temperate North Atlantic, spring blooms advanced their timing and decreased in magnitude, whereas fall blooms delayed and increased their intensity. At the same time, the prevalence of locations with a single autumn/winter bloom or with a bimodal seasonal cycle increased, in consonance with a poleward expansion of subtropical conditions. Changes in bloom timing and magnitude presented a clear signature of environmental factors, especially wind forcing, although changes on incident photosynthetically active radiation and sea surface temperature were also important depending on latitude. Trends in bloom magnitude matched changes in mean chlorophyll a during the study period, suggesting that seasonal peaks drive long-term trends in chlorophyll a concentration. Our results link changes in North Atlantic climate with recent trends in the phenology of phytoplankton, suggesting an intensification of these impacts in the near future.