ALBERT

Beschreibung: Anaerobic oxidation of ammonium (anammox) in oxygen minimum zones (OMZs) is a major pathway of oceanic nitrogen loss. Ammonium released from sinking particles has been suggested to fuel this process. During cruises to the Peruvian OMZ in April–June 2017 we found that anammox rates are strongly correlated with the volume of small particles (128–512 µm), even though anammox bacteria were not directly associated with particles. This suggests that the relationship between anammox rates and particles is related to the ammonium released from particles by remineralization. To investigate this, ammonium release from particles was modelled and theoretical encounters of free-living anammox bacteria with ammonium in the particle boundary layer were calculated. These results indicated that small sinking particles could be responsible for ~75% of ammonium release in anoxic waters and that free-living anammox bacteria frequently encounter ammonium in the vicinity of smaller particles. This indicates a so far underestimated role of abundant, slow-sinking small particles in controlling oceanic nutrient budgets, and furthermore implies that observations of the volume of small particles could be used to estimate N-loss across large areas.

Beschreibung: Earth's climate can be understood as a dynamical system that changes due to external forcing and internal couplings. Essential climate variables, such as surface air temperature, describe this dynamics. Our current interglacial, the Holocene (11 700 yr ago to today), has been characterized by small variations in global mean temperature prior to anthropogenic warming. However, the mechanisms and spatiotemporal patterns of fluctuations around this mean, called temperature variability, are poorly understood despite their socioeconomic relevance for climate change mitigation and adaptation. Here we examine discrepancies between temperature variability from model simulations and paleoclimate reconstructions by categorizing the scaling behavior of local and global surface air temperature on the timescale of years to centuries. To this end, we contrast power spectral densities (PSD) and their power-law scaling using simulated and observation-based temperature series of the last 6000 yr. We further introduce the spectral gain to disentangle the externally forced and internally generated variability as a function of timescale. It is based on our estimate of the joint PSD of radiative forcing, which exhibits a scale break around the period of 7 yr. We find that local temperature series from paleoclimate reconstructions show a different scaling behavior than simulated ones, with a tendency towards stronger persistence (i.e., correlation between successive values within a time series) on periods of 10 to 200 yr. Conversely, the PSD and spectral gain of global mean temperature are consistent across data sets. Our results point to the limitation of climate models to fully represent local temperature statistics over decades to centuries. By highlighting the key characteristics of temperature variability, we pave a way to better constrain possible changes in temperature variability with global warming and assess future climate risks.