Attribution and Predictability of Climate-Driven Variability in Global Ocean Color

For over two decades, satellite ocean color missions have revealed spatio-temporal variations in marine chlorophyll. Seasonal cycles and interannual changes of the physical environment drive the nutrient and chlorophyll variations. In order to identify contributions of seasonal and interannual components on chlorophyll, the present study investigates total chlorophyll variance (TCV) of a 24 year records (September 1997 to December 2021) across satellite generations. First-order contributions of the seasonal cycle in the mid-latitude (25°-35°) oceans in the Northern and Southern Hemispheres explain 59.5% and 69.9% of TCV, respectively. In contrast, the contribution of seasonal cycle only explain 30.9% in the tropical oceans (20°N-20°S). Both seasonal cycle- and climate-driven variability (26.3%) explain 57.2% on TCV in the tropical oceans. A multiple linear regression model was forced by instantaneous and delayed effects of oceanic memory of eight climate indices based on sea surface temperature anomalies to reconstruct chlorophyll anomalies. Delayed climate effects generally boost the anomaly correlation coefficients (ACC) between the observed and reconstructed chlorophyll timeseries (ACC skills: 0.64 to 0.72 in the Indian Ocean, 0.74 to 0.82 in off-equatorial Northern Pacific, and 0.58 to 0.71 in the off-equatorial Southern Pacific). Such delayed climate effects provide a source of predicted chlorophyll ACC (ACC_predic) skills one season ahead in some ocean regions (ACC_predic skill: 0.63 in the overall tropical ocean, 0.67 in the tropical Pacific, and 0.60 in the Indian Ocean). The attribution of chlorophyll variability indicates promising avenues for improving marine ecosystem predictions with Earth system models by incorporating delayed climate effects.