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Abstract:
Terrestrial biosphere models are indispensable tools for analyzing the biosphere‐atmosphere exchange of carbon and water. Evaluation of these models using site level observations scrutinizes our current understanding of biospheric responses to meteorological variables. Here we propose a novel model‐data comparison strategy considering that CO2 and H2O exchanges fluctuate on a wide range of timescales. Decomposing simulated and observed time series into subsignals allows to quantify model performance as a function of frequency, and to localize model‐data disagreement in time. This approach is illustrated using site level predictions from two models of different complexity, Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and Lund‐Potsdam‐Jena (LPJ), at four eddy covariance towers in different climates. Frequency‐dependent errors reveal substantial model‐data disagreement in seasonal‐annual and high‐frequency net CO2 fluxes. By localizing these errors in time we can trace these back, for example, to overestimations of seasonal‐annual periodicities of ecosystem respiration during spring greenup and autumn in both models. In the same frequencies, systematic misrepresentations of CO2 uptake severely affect the performance of LPJ, which is a consequence of the parsimonious representation of phenology. ORCHIDEE shows pronounced model‐data disagreements in the high‐frequency fluctuations of evapotranspiration across the four sites. We highlight the advantages that our novel methodology offers for a rigorous model evaluation compared to classical model evaluation approaches. We propose that ongoing model development will benefit from considering model‐data (dis)agreements in the time‐frequency domain.
