Misrepresentation of the temperature sensitivity of respiration in terrestrial biosphere models

Large uncertainty in current estimates of photosynthesis and respiration precludes an accurate assessment of the terrestrial carbonclimate feedback. While the recent decade has seen a proliferation of novel methods to improve photosynthesis estimates on regional scales, respiration remains stubbornly uncertain due to the lack of scalable measurements and the difficulty in disentangling atmospheric CO2 signals. Bottom-up models thus remain the primary way to obtain large-scale respiration estimates, but model divergence in estimates casts a shadow on our understanding of the magnitude, distribution, and temperature response of respiration. To address this issue, we seek to diagnose the causes of model divergence in estimates of respiration by evaluating carbon flux estimates from a large set of terrestrial biosphere models against atmospheric CO2 measurements over North America. Surprisingly, we find that for a large subset of models, estimates of gross primary productivity (GPP) explain the observed variability in atmospheric CO2 better than those models estimates of net ecosystem exchange (NEE). These models appear to misrepresent the seasonal amplitudes of respiration, due to an overestimate of the temperature sensitivity of respiration. These results indicate that an improved representation of the temperature sensitivity of respiration is needed for robust projections of the terrestrial carbon cycle.