Global variability of high-nutrient low-chlorophyll regions using neural networks and wavelet coherence analysis

Abstract

Abstract. We examine 20 years of monthly global ocean color data and modeling outputs of nutrients using self-organizing map (SOM) analysis to identify characteristic spatial and temporal patterns of high-nutrient low-chlorophyll (HNLC) regions and their association with different climate modes. The global nitrate-to-chlorophyll ratio threshold of NO3 : Chl > 17 (mmol NO3 mg Chl−1) is estimated to be a good indicator of the distribution limit of this unproductive biome that, on average, covers 92 × 106 km2 (∼ 25 % of the ocean). The trends in satellite-derived surface chlorophyll (0.6 ± 0.4 % yr−1 to 2 ± 0.4 % yr−1) suggest that HNLC regions in polar and subpolar areas have experienced an increase in phytoplankton biomass over the last decades, but much of this variation, particularly in the Southern Ocean, is produced by a climate-driven transition in 2009–2010. Indeed, since 2010, the extent of the HNLC zones has decreased at the poles (up to 8 %) and slightly increased at the Equator (< 0.5 %). Our study finds that chlorophyll variations in HNLC regions respond to major climate variability signals such as the El Niño–Southern Oscillation (ENSO) and Meridional Overturning Circulation (MOC) at both short (2–4 years) and long (decadal) timescales. These results suggest global coupling in the functioning of distant biogeochemical regions.