2016, Sippel, S., Otto, F.E.L., Forkel, M., Allen, M.R., Guillod, B.P., Heimann, M., Reichstein, M., Seneviratne, S.I., Thonicke, K., Mahecha, M.D.

Understanding, quantifying and attributing the impacts of extreme weather and climate events in the terrestrial biosphere is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit biases in their output that hinder any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies, most of which have been criticized for physical inconsistency and the nonpreservation of the multivariate correlation structure. In this study, we introduce a novel, resampling-based bias correction scheme that fully preserves the physical consistency and multivariate correlation structure of the model output. This procedure strongly improves the representation of climatic extremes and variability in a large regional climate model ensemble (HadRM3P, climateprediction.net/weatherathome), which is illustrated for summer extremes in temperature and rainfall over Central Europe. Moreover, we simulate biosphere–atmosphere fluxes of carbon and water using a terrestrial ecosystem model (LPJmL) driven by the bias-corrected climate forcing. The resampling-based bias correction yields strongly improved statistical distributions of carbon and water fluxes, including the extremes. Our results thus highlight the importance of carefully considering statistical moments beyond the mean for climate impact simulations. In conclusion, the present study introduces an approach to alleviate climate model biases in a physically consistent way and demonstrates that this yields strongly improved simulations of climate extremes and associated impacts in the terrestrial biosphere. A wider uptake of our methodology by the climate and impact modelling community therefore seems desirable for accurately quantifying changes in past, current and future extremes.

2018, García Cantú, Anselmo, Frieler, Katja, Reyer, Christopher P O, Ciais, Philippe, Chang, Jinfeng, Ito, Akihiko, Nishina, Kazuya, François, Louis, Henrot, Alexandra-Jane, Hickler, Thomas, Steinkamp, Jörg, Rafique, Rashid, Zhao, Fang, Ostberg, Sebastian, Schaphoff, Sibyll, Tian, Hanqin, Pan, Shufen, Yang, Jia, Morfopoulos, Catherine, Betts, Richard

This paper evaluates the ability of eight global vegetation models to reproduce recent trends and inter-annual variability of biomass in natural terrestrial ecosystems. For the purpose of this evaluation, the simulated trajectories of biomass are expressed in terms of the relative rate of change in biomass (RRB), defined as the deviation of the actual rate of biomass turnover from its equilibrium counterpart. Cumulative changes in RRB explain long-term changes in biomass pools. RRB simulated by the global vegetation models is compared with its observational equivalent, derived from vegetation optical depth reconstructions of above-ground biomass (AGB) over the period 1993–2010. According to the RRB analysis, the rate of global biomass growth described by the ensemble of simulations substantially exceeds the observation. The observed fluctuations of global RRB are significantly correlated with El Niño Southern Oscillation events (ENSO), but only some of the simulations reproduce this correlation. However, the ENSO sensitivity of RRB in the tropics is not significant in the observation, while it is in some of the simulations. This mismatch points to an important limitation of the observed AGB reconstruction to capture biomass variations in tropical forests. Important discrepancies in RRB were also identified at the regional scale, in the tropical forests of Amazonia and Central Africa, as well as in the boreal forests of north-western America, western and central Siberia. In each of these regions, the RRBs derived from the simulations were analyzed in connection with underlying differences in net primary productivity and biomass turnover rate ̶as a basis for exploring in how far differences in simulated changes in biomass are attributed to the response of the carbon uptake to CO2 increments, as well as to the model representation of factors affecting the rates of mortality and turnover of foliage and roots. Overall, our findings stress the usefulness of using RRB to evaluate complex vegetation models and highlight the importance of conducting further evaluations of both the actual rate of biomass turnover and its equilibrium counterpart, with special focus on their background values and sources of variation. In turn, this task would require the availability of more accurate multi-year observational data of biomass and net primary productivity for natural ecosystems, as well as detailed and updated information on land-cover classification.

2013, Ostberg, S., Lucht, W., Schaphoff, S., Gerten, D.

Globally increasing temperatures are likely to have impacts on terrestrial, aquatic and marine ecosystems that are difficult to manage. Quantifying impacts worldwide and systematically as a function of global warming is fundamental to substantiating the discussion on climate mitigation targets and adaptation planning. Here we present a macro-scale analysis of climate change impacts on terrestrial ecosystems based on newly developed sets of climate scenarios featuring a step-wise sampling of global mean temperature increase between 1.5 and 5 K by 2100. These are processed by a biogeochemical model (LPJmL) to derive an aggregated metric of simultaneous biogeochemical and structural shifts in land surface properties which we interpret as a proxy for the risk of shifts and possibly disruptions in ecosystems. Our results show a substantial risk of climate change to transform terrestrial ecosystems profoundly. Nearly no area of the world is free from such risk, unless strong mitigation limits global warming to around 2 degrees above preindustrial level. Even then, our simulations for most climate models agree that up to one-fifth of the land surface may experience at least moderate ecosystem change, primarily at high latitudes and high altitudes. If countries fulfil their current emissions reduction pledges, resulting in roughly 3.5 K of warming, this area expands to cover half the land surface, including the majority of tropical forests and savannas and the boreal zone. Due to differences in regional patterns of climate change, the area potentially at risk of major ecosystem change considering all climate models is up to 2.5 times as large as for a single model.

2016, Rafique, R., Zhao, F., De Jong, R., Zeng, N., Asrar, G.R.

2015, Ciuraru, Raluca, Fine, Ludovic, van Pinxteren, Manuela, D’Anna, Barbara, Herrmann, Hartmut, George, Christian

Isoprene is an important reactive gas that is produced mainly in terrestrial ecosystems but is also produced in marine ecosystems. In the marine environment, isoprene is produced in the seawater by various biological processes. Here, we show that photosensitized reactions involving the sea-surface microlayer lead to the production of significant amounts of isoprene. It is suggested that H-abstraction processes are initiated by photochemically excited dissolved organic matter which will the degrade fatty acids acting as surfactants. This chemical interfacial processing may represent a significant abiotic source of isoprene in the marine boundary layer.