A long-standing challenge in studying the global carbon cycle has been understanding the factors controlling inter–annual variation (IAV) of carbon fluxes related to vegetation photosynthesis and respiration, and improving their representations in existing biogeochemical models. Here, we compared an optimality-based mechanistic model and a semi-empirical light use efficiency model to understand how current models can be improved to simulate IAV of gross primary production (GPP). Both models simulated hourly GPP and were parameterized for (1) each site–year, (2) each site with an additional constraint on IAV (CostIAV), (3) each site, (4) each plant–functional type, and (5) globally. This was followed by forward runs using calibrated parameters, and model evaluations at different temporal scales across 198 eddy covariance sites. Both models performed better on hourly scale than annual scale for most sites. Specifically, the mechanistic model substantially improved when drought stress was explicitly included. Most of the variability in model performances was due to model types and parameterization strategies. The semi-empirical model produced statistically better hourly simulations than the mechanistic model, and site–year parameterization yielded better annual performance for both models. Annual model performance did not improve even when parameterized using CostIAV. Furthermore, both models underestimated the peaks of diurnal GPP in each site–year, suggesting that improving predictions of peaks could produce a comparatively better annual model performance. GPP of forests were better simulated than grassland or savanna sites by both models. Our findings reveal current model deficiencies in representing IAV of carbon fluxes and guide improvements in further model development.

To explain the inequality between aerodynamic and radiometric surface temperature, we used an analytical surface energy balance model where evaporation is directly estimated by constraining the state equations of aerodynamic temperature and biophysical conductances through radiometric temperature. While the derived aerodynamic temperature was comparable with a flux-inverted counterpart, evaporation and sensible heat fluxes also showed good correspondence with in-situ eddy covariance observations over contrasting aridity in Australia. Results showed aerodynamic temperature frequently exceeds the radiometric temperature in arid and semiarid ecosystems for two reasons: (i) declining canopy-surface conductance and evaporative fraction due to escalated water stress and vapor pressure deficit, and (ii) a simultaneous increase in aerodynamic conductance, air temperature and sensible heat flux. The analytical approach provides valuable insights into the long-lasting debate of aerodynamic versus radiometric temperature paradox by recognizing the feedback between biophysical conductances and the supply-demand limit of solar radiation, soil moisture, and vapor pressure deficit.