Baltic Sea summer bloom coverage

'''DEFINITION'''

The time series are derived from the regional chlorophyll reprocessed (MY) product for the Baltic Sea (OCEANCOLOUR_BAL_BGC_L3_MY_009_133) as distributed by CMEMS which, in turn, result from the application of the regional chlorophyll algorithm over remote sensing reflectances (Rrs) provided by the Plymouth Marine Laboratory using an ad-hoc configuration for CMEMS of the ESA OC-CCI processor version 6 (OC-CCIv6) to merge at 1km resolution (rather than at 4km as for OC-CCI) MERIS, MODIS-AQUA, SeaWiFS, NPP-VIIRS and OLCI-A data. The chlorophyll product is derived from a Multi-Layer Perceptron neural-net (MLP) developed on field measurements collected within the BiOMaP program of JRC/EC (Zibordi et al., 2011). The algorithm is an ensemble of different MLPs that use Rrs at different wavelengths as input. The processing chain and the techniques used to develop the algorithm are detailed in Brando et al. (2021; 2024). 
In the Baltic Sea, the phytoplankton blooms occurring during summer are dominated by nitrogen-fixing cyanobacteria that can have subsurface and/or surface accumulations (Kahru et al., 2007). Consistent with the HELCOM environmental reporting (e.g. Öberg 2018) the cyanobacterial subsurface and surface summer blooms are detected the applying the thresholds on Rrs at the wavelength of 555 and 670 nm. The chlorophyll dataset of the Baltic Sea MY product (OCEANCOLOUR_BAL_BGC_L3_MY_009_133) contains the cyanobacteria summer bloom mask variable (CYANOBLOOM) which reports whether the thresholds for the cyanobacterial blooms was exceeded on the daily Rrs images (Brando et al. 2024). The spatiotemporal coverage for cyanobacterial blooms is then computed as detailed in the Ocean State Report issues 2 (Raudsepp et al 2018) and in Brando et al. (2021).

'''CONTEXT'''

Phytoplankton   and chlorophyll concentration as a proxy for phytoplankton   respond rapidly to changes in environmental conditions, such as light, temperature, nutrients and mixing (Gregg and Rousseaux, 2014). The character of the response in the Baltic Sea depends on the nature of the change drivers, and ranges from seasonal cycles to decadal oscillations (Kahru and Elmgren 2014). 
As cyanobacterial blooms are extremely patchy and the surface scum is unlikely to totally cover a 1 km resolution pixel, it is possible for both thresholds to be exceeded concurrently. Following Hansson and Håkansson (2007), the cyanobacteria summer bloom mask variable (CYANOBLOOM) in the MY regional chlorophyll dataset was aggregated from June to September (i.e., days 161 to 270) of each year for the three possible values (subsurface =1; surface=2, and 3: both subsurface and surface summer blooms detected).


'''KEY FINDINGS'''

Over the 19982024 period, the spatiotemporal coverage of cyanobacteria summer bloom in the Baltic Sea increased from 1998 to 2005, decreased from 2005 to 2012, and then increased from 2012 to 2019 and decreased to 2024. These oscillations without a consistent decadal trend, are inline to those reported from 1979 to date by previous satellite-based studies and the HELCOM results (e.g. Kahru and Elmgren,2014; Brando et al. ,2021). The maximum values were recorded in 2019 and 2005 (2.95 and 2.56 106 day km2, respectively). The lowest values observed between 1998 and 2001 are likely to reflect the lower spatial coverage of the OC-CCIv6 dataset in that period due to the availability of only one sensor. 

'''DOI (product):''' 
https://doi.org/10.48670/mds-00366