ALBERT

Description: Phytoplankton biomass exhibits significant year-to-year changes, and understanding these changes is crucial for fisheries management and projecting future climate. These annual changes are usually attributed to low-frequency climate modes that also lead to variations in sea surface temperature (SST). We evaluate the contribution of small scales to annual fluctuations based on a global analysis of satellite observations of sea surface chlorophyll (SChl), an indicator of phytoplankton biomass, and of SST from 1999 to 2018. To quantitatively disentangle the spatio-temporal scales of variability, we utilize a timeseries decomposition method that isolates distinct frequency bands. We show that besides the prominent seasonal cycle, SChl is dominated by high-frequency fluctuations (〈3 months) at small spatial scales (〈50 km)—which accumulate over annual scales, in contrast to SST. This implies that slow variations in the environment linked to climate modes can’t fully explain the annual variations in phytoplankton biomass. Instead, the cumulative effect of fine-scale variations drives the year-to-year changes. This result is further examined over the Southern Ocean, where large annual variations are evident. We find that the Southern Annular Mode (SAM), the dominant low-frequency climate signal in the region, can explain only 10% of the annual variations in SChl. Rather, most of the annual variations are associated with small spatial-scale, high-frequency fluctuations, which are not correlated with the SAM. Our results suggest that observations and models with high spatio-temporal resolutions are necessary to understand annual variations in phytoplankton biomass and to detect climate change driven trends.