Abstract
BackgroundAn increasing number of ecological processes have been incorporated into Earth system models. However, model evaluations usually lag behind the fast development of models, leading to a pervasive simulation uncertainty in key ecological processes, especially the terrestrial carbon (C) cycle. Traceability analysis provides a theoretical basis for tracking and quantifying the structural uncertainty of simulated C storage in models. Thus, a new tool of model evaluation based on the traceability analysis is urgently needed to efficiently diagnose the sources of inter-model variations on the terrestrial C cycle in Earth system models.MethodsA new cloud-based model evaluation platform, i.e., the online traceability analysis system for model evaluation (TraceME v1.0), was established. The TraceME was applied to analyze the uncertainties of seven models from the Coupled Model Intercomparison Project (CMIP6).ResultsThe TraceME can effectively diagnose the key sources of different land C dynamics among CMIIP6 models. For example, the analyses based on TraceME showed that the estimation of global land C storage varied about 2.4 folds across the seven CMIP6 models. Among all models, IPSL-CM6A-LR simulated the lowest land C storage, which mainly resulted from its shortest baseline C residence time. Over the historical period of 1850–2014, gross primary productivity and baseline C residence time were the major uncertainty contributors to the inter-model variation in ecosystem C storage in most land grid cells.ConclusionTraceME can facilitate model evaluation by identifying sources of model uncertainty and provides a new tool for the next generation of model evaluation.
Highlights
Earth system models are an essential tool for understating and predicting the interactions between ecological processes and environmental changes at the global scale (Eyring et al 2016a; Bonan and Doney 2018)
Temporal dynamics of land carbon storage in CMIP6 models Traceability analysis system for Model Evaluation (TraceME) (v1.0) provided an automatic traceability analysis for data of temporal interest, which can be used to evaluate the temporal dynamics of land C storage simulated by models
We used seven models that had submitted results in CMIP6 to analyze the uncertainty of these models in simulating historical land C storage from 1850 to 2014
Summary
Earth system models are an essential tool for understating and predicting the interactions between ecological processes and environmental changes at the global scale (Eyring et al 2016a; Bonan and Doney 2018). The ILAMB system uses a set of statistical methods to construct a data-driven scoring system to benchmark global C cycle models (Collier et al 2018) These new tools have greatly increased the efficiency of model evaluations for Earth system models (Eyring et al 2019). For the terrestrial C cycle, a traceability analysis has been developed to diagnose the inter-model variations in the land C cycle based on its fundamental properties (Xia et al 2013; Luo et al 2017). A new tool of model evaluation based on the traceability analysis is urgently needed to efficiently diagnose the sources of inter-model variations on the terrestrial C cycle in Earth system models
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