Environmental conditions such as temperature and water availability are strongly interlinked with terrestrial carbon fluxes. Overall, the terrestrial biosphere is currently providing a negative feedback to a warming world [Friedlingstein et al., 2006]. However, the nature and magnitude of most feedback mechanisms between the atmosphere and biosphere are still uncertain. Warmer temperatures, for instance, often increase terrestrial gross carbon uptake [Beer et al., 2010] but also soil respiration [Mahecha et al., 2010], resulting in a largely uncertain net carbon-cycle response to climate change. The last generation of coupled climate-carbon models largely disagreed as to whether the terrestrial biosphere will act as a sink or a source of carbon to the atmosphere in future [Friedlingstein et al., 2006]. This uncertainty still holds for the more recent model runs collected in the Coupled Model Intercomparison Project Phase 5 (CMIP5) [Ahlström et al., 2012; Jones et al., 2013].
Climate extremes such as droughts, heat waves, or intense precipitation events can significantly affect carbon fluxes [Reichstein et al., 2013]. Their impacts might, in some cases, temporarily reverse the effect of years of carbon sequestration [Ciais et al., 2005]. However, fast recovery can partly offset instantaneous impacts of climate extremes and disturbance events [Amiro et al., 2010]. Identifying extremes directly in variables describing the state of the biosphere such as fraction of absorbed photosynthetically active radiation or enhanced vegetation index can lead to new insights about the relationship between extreme climate drivers on the one hand and extreme responses on the other [Zscheischler et al., 2013; Reichstein et al., 2013]. It has recently been shown that extremes in gross primary production (GPP) are the main driver of GPP's interannual variability at the global [Zscheischler et al., 2014a] and the continental scale [Zscheischler et al., 2014b], with water scarcity driving most of the negative extreme events. While droughts often significantly influence carbon uptake, higher water availability can also mitigate the impacts of heat waves [Bauweraerts et al., 2014]. In a warming climate, the intensity and frequency of climate extremes and their geographical distribution will change substantially [Seneviratne et al., 2012; Sillmann et al., 2013; Fischer et al., 2013], suggesting concurrent changes in carbon cycle variability.
So far little attention has been given to model performance during extreme events. Keenan et al.  discuss model performance and lagged impacts in response to one extreme event within a model-data intercomparison study. Zscheischler et al. [2014a, 2014b] analyze GPP extreme events on four different GPP data sets and find that droughts are the main driver for extreme decreases on the global and continental scale. In a model environment, it can be analyzed whether GPP extremes translate into changes in the net carbon uptake. Hence, in this study, we investigate how extremes in climate and the carbon cycle are related in current Terrestrial Biosphere Models (TBMs). In particular, we work with a suite of 10 state-of-the-art TBMs from the North American Carbon Program (NACP) Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP) described in Huntzinger et al.  and Wei et al. .
While simulated outputs are not direct observations of the carbon cycle, they integrate our current understanding of carbon exchanges between terrestrial ecosystems and the atmosphere, and therefore are a useful tool for several reasons. First, simple plausibility checks of the relationships found in the models can confirm model performance or foster reevaluation of specific model mechanisms. Second, analyzing model agreement can identify individual models that stand out against the rest. This can be useful if one can trace back the specific mechanisms that make a model an outlier in a particular situation, especially because some models that participated in MsTMIP are also used in coupled and/or offline projections of future carbon uptake. Third, due to the framework of MsTMIP [Huntzinger et al., 2013], specific differences in the model output can be attributed to differences in intrinsic model structural characteristics, parameters, and initial states. Finally, model results can yield novel hypotheses based on our current understanding of the processes at work. While we cannot address each of the above points in full detail in this study, we provide first results about how MsMTIP models behave during large-scale extreme events. Results from this study can then later be evaluated against observations, e.g., from carbon flux data obtained by eddy-covariance flux towers (compiled in FLUXNET) [Baldocchi et al., 2001; Baldocchi, 2008].
In this contribution, we analyze how current carbon cycle models translate extreme events in climate variables into (possibly extreme) responses in carbon fluxes. We address this question by looking from both driver and impact perspectives [Smith, 2011]. More specifically, we first identify temperature (T) and precipitation (P) extremes and estimate their immediate impact on the terrestrial carbon fluxes. Some extremes in temperature and precipitation can be strongly coupled, for instance, heat extremes and droughts [Mueller and Seneviratne, 2012]. We will therefore discuss whether the impact of a compound event (T and P simultaneously extreme) exceeds the expected additive impact (sum of impacts when either T or P is extreme). Besides their immediate impact, climate extremes can have strong lagged impacts on terrestrial carbon fluxes [Reichstein et al., 2013]. Warm seasons can enhance heterotrophic respiration in grasslands a year later, soil frost can increase sensitivity of heterotrophic respiration of forests to summer drought and tree mortality can increase after severe droughts [Reichstein et al., 2013]. Such lagged and legacy effects of extreme climate events, however, are still poorly understood [McDowell, 2011] and thus rarely correctly implemented in current carbon cycle models. Thus, we also analyze whether climate extremes cause large-scale lagged impacts.
Droughts and heat waves, as well as wind throw, fires, and insect infestation can trigger strong alterations in GPP and/or TR [Reichstein et al., 2013], but not all extreme changes in terrestrial carbon fluxes need to be driven by extreme drivers [Handmer et al., 2012]. Hence, in a second assessment, we identify extremes in C fluxes and analyze the concurrent climate conditions. More specifically, using driver data of MsTMIP, we investigate the concurrent state of T and P during C flux extremes.
Ecosystems in different regions are limited by different environmental factors. Cold temperatures often limit growth in boreal and temperate regions, whereas in tropical areas it is often warm enough but growth can be limited by water availability or cloud cover [Nemani et al., 2003]. Tropical forests also operate close to their optimal photosynthesis temperature, however, and could be impacted by hot temperatures [Clark, 2004; Corlett, 2011]. In fact, the interannual correlation between (tropical) CO2 anomalies and temperature anomalies is larger than with precipitation anomalies [see, e.g., Wang et al., 2013]. To investigate whether different ecosystems react differently to extreme climate conditions, we compare C flux responses to extreme conditions of T and P between tropical, temperate, and boreal forests.