Global Characterization of Atmosphere-Biosphere Dynamics Across Time Scales

In times of climate change it is important to deeply understand how the biosphere responds to climate drivers. However, these interactions are (i) not happening instantaneously, and (ii) may differ depending on the time scale under scrutiny. For instance, at the seasonal scale we may expect a different sensitivity of vegetation to temperature than on monthly or inter-annual scale. However, so far there is no systematic assessment of this phenomenon reported at the global scale. Here we explore long-term (>30 year) remote sensing records and climate data to characterize atmosphere-biosphere interactions explicitly on different time scales. We use time series decomposition to explore sub-monthly oscillations to decadal trends. Our results show that interactions between a vegetation index (NDVI), air temperature and precipitation strongly differ across time scales. Importantly, they often strongly diverge from the relationship of the integrated signal. This suggests that processes need to be characterized specifically on the temporal scale under investigation. Furthermore, we correlate variables on a global map for each time scale and observe complex spatial patterns in ecosystem variability not resolved with conventional methods. For example, our results indicate that the tropics constitute a highly heterogeneous system in terms of atmosphere-biosphere interactions on different temporal scales. Both instantaneous and delayed interactions between atmosphere and biosphere are important in understanding and predicting ecosystem trajectories under changing climatic conditions. Our results suggest that process parameters and sensitivities can vary strongly across time scales. This could help explain heterogeneity of ecosystem responses on different scales. These dynamics should be taken into account for accurate long- and short-term climate modeling