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Towards a More Objective Evaluation of Modelled Land-Carbon Trends EGU Journal Logos (RGB) Open Access Open Access Open Access Advances in Annales Nonlinear Processes Geosciences Geophysicae in Geophysics Open Access Open Access Natural Hazards Natural Hazards and Earth System and Earth System Sciences Sciences Discussions Open Access Open Access Atmospheric Atmospheric Chemistry Chemistry and Physics and Physics Discussions Open Access Open Access Atmospheric Atmospheric Measurement Measurement Techniques Techniques Discussions Open Access Biogeosciences, 10, 4189–4210, 2013 Open Access www.biogeosciences.net/10/4189/2013/ Biogeosciences doi:10.5194/bg-10-4189-2013 Biogeosciences Discussions © Author(s) 2013. CC Attribution 3.0 License. Open Access Open Access Climate Climate of the Past of the Past Discussions Towards a more objective evaluation of modelled land-carbon Open Access Open Access Earth System trends using atmospheric CO2 and satellite-basedEarth vegetation System activity Dynamics Dynamics observations Discussions D. Dalmonech and S. Zaehle Open Access Max Planck Institute for Biogeochemistry, Biogeochemical Systems Department, Hans-Knoll-Str.¨ Geoscientific 10, 07745 Jena, Germany Geoscientific Open Access Instrumentation Instrumentation Correspondence to: D. Dalmonech ([email protected]) Methods and Methods and Received: 12 September 2012 – Published in Biogeosciences Discuss.: 15 November 2012 Data Systems Data Systems Revised: 23 April 2013 – Accepted: 16 May 2013 – Published: 25 June 2013 Discussions Open Access Open Access Geoscientific Geoscientific Abstract. Terrestrial ecosystem models used for Earth sys- 1 Introduction Model Development tem modelling show a significant divergence in future pat- Model Development terns of ecosystem processes, in particular the net land– The terrestrial and oceanic biospheres currently absorb al- Discussions atmosphere carbon exchanges, despite a seemingly common most half of the fossil-fuel emissions, and thereby buffer Open Access behaviour for the contemporary period. An in-depth evalu- the atmospheric CO2 increase and reduce the rateOpen Access of climate ation of these models is hence of high importance to better change (Cox et al., 2000;Hydrology Raupach et al.,and 2008; Le Quer´ e´ Hydrology and understand the reasons for this disagreement. et al., 2009). Because ofEarth the strong System interactions between the Earth System Here, we develop an extension for existing benchmarking biosphere net carbon (C) uptake and climate in particular on systems by making use of the complementary information land (Cox et al., 2000; FriedlingsteinSciences et al., 2006, Arora et Sciences contained in the observational records of atmospheric CO2 al.2013), projections of future climate changes from Earth Discussions Open Access and remotely sensed vegetation activity to provide a novel set system models (ESMs) need to accurately simulateOpen Access the pro- of diagnostics of ecosystem responses to climate variability cesses that control the evolution of the terrestrial net C bal- Ocean Science in the last 30 yr at different temporal and spatial scales. The ance. However, despiteOcean a seemingly Science common behaviour of selection of observational characteristics (traits) specifically C cycle models for the contemporary period, estimates of Discussions considers the robustness of information given that the un- the future C land balance by different terrestrial biosphere certainty of both data and evaluation methodology is largely models (TBMs) diverge significantly. This divergence con- Open Access unknown or difficult to quantify. tributes strongly to the overall uncertainty in theOpen Access future evo- Based on these considerations, we introduce a baseline lution of the global carbon cycle (Friedlingstein et al., 2006; Solid Earth benchmark – a minimum test that any model has to pass – to Sitch et al., 2008; Arora et al.,Solid 2013). Earth The apparently con- Discussions provide a more objective, quantitative evaluation framework. tradictory behaviour underlines the difficulty of constraining The benchmarking strategy can be used for any land surface future projections of terrestrial models with current obser- model, either driven by observed meteorology or coupled to vations. This calls for an in-depth model evaluation that fo- Open Access Open Access a climate model. cusses on the model’s capacity to simulate key features of C- We apply this framework to evaluate the offline version cycle-related processes rather than simply ensuring that the The Cryosphere easily diagnosed simulatedThe netCryosphere land–atmosphere C exchange of the MPI Earth System Model’s land surface scheme JS- Discussions BACH. We demonstrate that the complementary use of at- agrees with estimates inferred from observations. mospheric CO2 and satellite-based vegetation activity data Several global model evaluation analyses have been pub- allows pinpointing of specific model deficiencies that would lished in the last decades with respect to land model perfor- not be possible by the sole use of atmospheric CO2 observa- mances of the carbon cycle (Anav, et al., 2013; Cadule et al., tions. 2009; Blyth et al., 2009; Randerson et al., 2009; Heimann et al., 1998). However, they differ with respect to reference dataset used, selection of the observational traits as well as Published by Copernicus Publications on behalf of the European Geosciences Union. 4190 D. Dalmonech and S. Zaehle: Towards a more objective evaluation of modelled land-carbon trends their computation, and mathematical formulations used to characteristics of the observations useful for the evaluation quantify the data–model mismatch. These differences cause of ESMs, priority was given to traits and metrics that de- uncertainty when it comes to ranking several land surface scribe the relationship between climate variables and carbon models or to analyse the outcome from different evaluation cycle processes rather than direct comparison of observed works. Recent model benchmarking initiatives (Randerson and modelled time series. et al., 2009; Luo et al., 2012) have therefore underlined the The second innovation of our studies is that we impose need for the development of a standard set of tests and met- a lower acceptable model performance measure (baseline rics applicable to any land surface model at different spatial benchmark) based on the assumption of a null model, i.e. a and temporal scale. model that does not show any trend in the quantity under In addition to a lack of standards, a key challenge in eval- investigation. This lower boundary for each metric helps to uating global biosphere models comes from the uncertainties avoid misleading interpretation of the number returned by the in observations. From a perspective of data–model mismatch scores, and to provide a more informative and intuitively in- quantification, given uncertainties in data and observation, terpretable analysis of the model performance. With respect operators to link model and data exist. However, data error to the atmospheric CO2 traits, the aim is to quantify how and structural errors are often not known or provided quanti- much information the land surface model adds to the signal tatively (e.g. Raupach et al., 2005). of ocean and anthropogenic fossil-fuel emissions and thus to This study is an attempt to move toward a more robust quantify how good the model is relative to the null hypoth- and a more objective evaluation framework by defining novel esis (null model). The working line is thus as follows: the tests/diagnostics and quantitative model performance mea- analyses were performed on a seasonal and a de-seasonalized sures that are robust against these mentioned unquantifiable signal to better identify C-cycle patterns and the relation- uncertainties. We first selected a parsimonious number of ref- ship between C-cycle-related processes and climate variabil- erence datasets that are as much as possible direct observa- ity. As detailed in Sect. 2, we selected several characteris- tions. In first instance, upscaled products such as that from tics (traits) of the observational data that are relevant to the Beer et al. (2009) were not used as the fraction of gap-filled biosphere’s response to climate variability in terms of ter- information is not quantified. Atmospheric CO2 and remote restrial C cycling patterns. We focussed on the the last three sensing data of vegetation activity were selected to take ad- decades (1980–2010) since this is the period with the best vantage of their spatial and temporal coverage and the com- data availability (Tables 2 and 3). For the selected tests, a plementarity of their information content. list of comprehensive metrics was selected to quantify model Atmospheric CO2 measurements and transport modelling performances according to the information content of iden- that links surface fluxes to these measurements are a valu- tified traits. We then compared this metric to the reference able approach to evaluate TBMs since the atmospheric CO2 value of the metric obtained according to the baseline bench- retains the signature of terrestrial ecosystem response to cli- mark to arrive at a final score for the model. mate variability (Heimann et al., 1998; Randerson et al., In Sect. 3 we discuss the potential strengths and limita- 2009; Cadule et al., 2010). However, atmospheric CO2 ob- tions of the evaluation framework at the example of the the servations alone do not allow inference of the contribution JSBACH land surface model of the MPI-ESM (Raddatz et of vegetation and soil components to the observed
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