Black Sea Chlorophyll-a trend map from Observations Reprocessing

'''DEFINITION'''

This product includes the Black Sea satellite chlorophyll trend map based on regional chlorophyll reprocessed (MY) product as distributed by CMEMS OC-TAC (OCEANCOLOUR_BAL_BGC_L3_MY_009_133). This dataset, derived from multi-sensor (SeaStar-SeaWiFS, AQUA-MODIS, NOAA20-VIIRS, NPP-VIIRS, Envisat-MERIS and Sentinel3-OLCI) Rrs spectra produced by CNR using an in-house processing chain, is obtained by means of two different regional algorithms developed with the BiOMaP data set (Zibordi et al., 2011): a band-ratio algorithm (B/R) (Zibordi et al., 2015) and a Multilayer Perceptron (MLP) neural net algorithm based on Rrs values at three individual wavelengths (490, 510 and 555 nm) (Kajiyama et al., 2018). The processing chain and the techniques used for algorithms merging are detailed in Colella et al. (2023).  
The trend map is obtained by applying Colella et al. (2016) methodology, where the Mann-Kendall test (Mann, 1945; Kendall, 1975) and Sens’s method (Sen, 1968) are applied on deseasonalized monthly time series, as obtained from the X-11 technique (see e. g. Pezzulli et al. 2005), to estimate, trend magnitude and its significance. The trend is expressed in % per year that represents the relative changes (i.e., percentage) corresponding to the dimensional trend [mg m-3 y-1] with respect to the reference climatology (1997-2014). Only significant trends (p < 0.05) are included. This OMI has been introduced since the 2nd issue of Ocean State Report in 2017.

'''CONTEXT'''

Phytoplankton are key actors in the carbon cycle and, as such, recognised as an Essential Climate Variable (ECV). Chlorophyll concentration - as a proxy for phytoplankton - respond rapidly to changes in environmental conditions, such as light, temperature, nutrients and mixing (Colella et al. 2016). The character of the response depends on the nature of the change drivers, and ranges from seasonal cycles to decadal oscillations (Basterretxea et al. 2018). Therefore, it is of critical importance to monitor chlorophyll concentration at multiple temporal and spatial scales, in order to be able to separate potential long-term climate signals from natural variability in the short term. In particular, phytoplankton in the Black Sea is known to respond to climate variability associated with the North Atlantic Oscillation (NAO) (Oguz et al .2003). Furthermore, chlorophyll analysis also demands the use of robust statistical temporal decomposition techniques, in order to separate the long-term signal from the seasonal component of the time series.

'''KEY FINDINGS'''

The average chlorophyll trend in the Black Sea for the 1997–2024 period closely matches previous estimates (1997–2021,1997–2022 and 1997-2023), showing an average decline of -1.04% per year. The overall trend across the basin is negative, with weaker trends, occasionally non-significant, in the central region. A pronounced negative trend is observed on the western side of the basin, although slightly weaker compared to the overall 1997–2023 period. In the Sea of Azov, negative values are observed, with a notable reversal near the offshore area of the Don River. This widespread negative trend aligns with the findings of Bengil and Mavruk (2018), who reported a decline in chlorophyll levels during the post-eutrophication phase between 1997 and 2017.

'''DOI (product):''' 
https://doi.org/10.48670/moi-00212