Abstract
Investigating the variability of phytoplankton phenology plays a key role in regions characterized by cyclonic circulation regimes or convective events, like the north-western Mediterranean Sea (NWM). The main goal of this study is to assess the potential of the robust satellite techniques (RST) in identifying anomalous phytoplankton blooms in the NWM by using 9 years (2008–2017) of multi-sensor chlorophyll-a (chl-a) products from the CMEMS and OC-CCI datasets. Further application of the RST approach on a corresponding time-series of in situ chl-a measurements acquired at the BOUSSOLE site allows evaluation ofthe accuracy of the satellite-based change detection indices and selecting the best indicator. The OC-CCI derived chl-a anomaly index shows the best performances when compared to in situ data (R2 and RMSE of 0.75 and 0.48, respectively). Thus, it has been used to characterize an anomalous chl-a bloom that occurred in March 2012 at regional scale. Results show positive chl-a anomalies between the BOUSSOLE site and the Center of Convection Zone (CCZ) as a possible consequence of an intense convection episode that occurred in February 2012.
Highlights
Variations in atmospheric and oceanic forcing and the effects of climate changes can impact some ecosystem properties, including marine primary production, the phytoplankton community structure and phytoplankton phenology [1,2,3]
We looked at the daily Qnet values at the BOUSSOLE site and in the Convection Zone (CCZ) (Figure 8) to detect episodes of intense heat losses at the sea surface and associated winter deep water convection (WDWC) events that potentially occurred during the January–March 2012 period
The phytoplankton phenology is an invaluable indicator for assessing how marine chl-a anomalies detected on 16 March 2012 fall into the WDWC zone with a percentage of ecosystems react to external forcing [37,66]
Summary
Variations in atmospheric and oceanic forcing (i.e., winds, intermittent upwelling, seasonal change in stratification, sea surface warming) and the effects of climate changes can impact some ecosystem properties, including marine primary production, the phytoplankton community structure and phytoplankton phenology [1,2,3]. Changes in phytoplankton phenology, such as timing and magnitude of the spring bloom, can produce harmful effects for the pelagic ecosystem, including mismatches with fish spawning, impacting fisheries [4,5,6]. In this scenario, characterizing seasonal and inter-annual variations of phytoplankton is a prerequisite for assessing how changes in the marine environment propagate from primary producers to higher trophic levels [7]. Several studies have been conducted to investigate chl-a seasonal patterns at basin/regional scales by using multivariate clustering methods with OCR data [10,11,12,13]. 4.0/).
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