Using atmospheric observations to evaluate the spatiotemporal variability of CO2 fluxes simulated by terrestrial biospheric models

[摘要] Terrestrial biospheric models (TBMs) are used to extrapolate localobservations and process-level understanding of land-atmosphere carbonexchange to larger regions, and serve as predictive tools for examiningcarbon-climate interactions. Understanding the performance of TBMs is thuscrucial to the carbon cycle and climate science communities. In this study,we present and assess an approach to evaluating the spatiotemporal patterns,rather than aggregated magnitudes, of net ecosystem exchange (NEE) simulatedby TBMs using atmospheric CO₂ measurements. The approach is based onstatistical model selection implemented within a high-resolution atmosphericinverse model. Using synthetic data experiments, we find that currentatmospheric observations are sensitive to the underlying spatiotemporal fluxvariability at sub-biome scales for a large portion of North America, andthat atmospheric observations can therefore be used to evaluate simulatedspatiotemporal flux patterns as well as to differentiate between multiplecompeting TBMs. Experiments using real atmospheric observations and fourprototypical TBMs further confirm the applicability of the method, anddemonstrate that the performance of TBMs in simulating the spatiotemporalpatterns of NEE varies substantially across seasons, with best performanceduring the growing season and more limited skill during transition seasons.This result is consistent with previous work showing that the ability of TBMsto model flux magnitudes is also seasonally-dependent. Overall, the proposedapproach provides a new avenue for evaluating TBM performance based onsub-biome-scale flux patterns, presenting an opportunity for assessing andinforming model development using atmospheric observations.

[学科分类] 地球化学与岩石