Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment

Abstract

Abstract. During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O 2 , NO 3 , Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of modelto-model uncertainty. This requires more attention in future Published by Copernicus Publications on behalf of the European Geosciences Union. R. Séférian et al.: Inconsistent strategies to spin up models in CMIP5model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.

Evaluation of the transport matrix method for simulation of ocean biogeochemical tracers

“…Simulations performed with the TMM are thus orders of magnitude faster making it possible to routinely perform long spin-ups of UVic ESCM biogeochemistry in a few hours rather than weeks. A recent study (Séférian et al, 2016) highlighting the importance of adequate spin-ups suggests that this could be beneficial even for earth system models that are already parallelized, especially with the advent of many-core hardware architectures, such as general purpose graphics processing units (GPGPUs) to which the TMM has been recently ported (Siewertsen et al, 2013). Moreover, the speed-up opens up the possibility of systematically testing different parameterizations in complex, global biogeochemical models, or even optimizing such models against data as has been recently accomplished for a slightly simpler model by Kriest et al (2017).…”

The Carbon Dioxide Removal Model Intercomparison Project (CDRMIP): rationale and experimental protocol for CMIP6

“…Model drift (Gupta et al, 2013;Séférian et al, 2016) is a concern for all CDRMIP experiments because if a model is not at an equilibrium state when the experiment or prerequisite CMIP experiment begins, then the response to any experimental perturbations could be confused by drift. Thus, before beginning any of the experiments a model must be spun up to eliminate long-term drift in carbon reservoirs or fluxes.…”

“…The few natural analogues that exist for some methods (e.g., weathering or reforestation) only provide limited insight into the effectiveness of deliberate large-scale CDR. As such, beyond syntheses of resource requirements and availabilities (e.g., Smith, 2016), there is a lack of observational constraints that can be applied to the assessment of the effectiveness of CDR methods. Lastly, many proposed CDR methods are premature at this point and technology deployment strategies would be required to overcome this barrier (Schäfer et al, 2015), which means that they can only be studied in an idealized manner, i.e., through model simulations.…”

Reviews and syntheses: parameter identification in marine planktonic ecosystem modelling

“…It also depends on the values assigned to the parameters of the biogeochemical model, and it is not necessarily a monotonic function of time, but can exhibit inflection points that reflect the interaction of diverse processes happening on different timescales (Kriest and Oschlies, 2015). For parameter optimization it is meaningful to exclude from a cost function those transient model solutions that involve continuing trends in the redistribution of tracers (see also Séférian et al, 2016). To attain some equilibrated biogeochemical cycling requires considerable computational time, which makes it particularly difficult to employ methods that exploit the parameter-cost function manifold with a large ensemble of model runs like the MCMC method.…”