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    ATTRICI v1.1 – counterfactual climate for impact attribution
    (Katlenburg-Lindau : Copernicus, 2021) Mengel, Matthias; Treu, Simon; Lange, Stefan; Frieler, Katja
    Attribution in its general definition aims to quantify drivers of change in a system. According to IPCC Working Group II (WGII) a change in a natural, human or managed system is attributed to climate change by quantifying the difference between the observed state of the system and a counterfactual baseline that characterizes the system's behavior in the absence of climate change, where “climate change refers to any long-term trend in climate, irrespective of its cause” (IPCC, 2014). Impact attribution following this definition remains a challenge because the counterfactual baseline, which characterizes the system behavior in the hypothetical absence of climate change, cannot be observed. Process-based and empirical impact models can fill this gap as they allow us to simulate the counterfactual climate impact baseline. In those simulations, the models are forced by observed direct (human) drivers such as land use changes, changes in water or agricultural management but a counterfactual climate without long-term changes. We here present ATTRICI (ATTRIbuting Climate Impacts), an approach to construct the required counterfactual stationary climate data from observational (factual) climate data. Our method identifies the long-term shifts in the considered daily climate variables that are correlated to global mean temperature change assuming a smooth annual cycle of the associated scaling coefficients for each day of the year. The produced counterfactual climate datasets are used as forcing data within the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). Our method preserves the internal variability of the observed data in the sense that factual and counterfactual data for a given day have the same rank in their respective statistical distributions. The associated impact model simulations allow for quantifying the contribution of climate change to observed long-term changes in impact indicators and for quantifying the contribution of the observed trend in climate to the magnitude of individual impact events. Attribution of climate impacts to anthropogenic forcing would need an additional step separating anthropogenic climate forcing from other sources of climate trends, which is not covered by our method.
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    initMIP-Antarctica: an ice sheet model initialization experiment of ISMIP6
    (Katlenburg-Lindau : Copernicus, 2019) Seroussi, Hélène; Nowicki, Sophie; Simon, Erika; Abe-Ouchi, Ayako; Albrecht, Torsten; Brondex, Julien; Cornford, Stephen; Dumas, Christophe; Gillet-Chaulet, Fabien; Goelzer, Heiko; Golledge, Nicholas R.; Gregory, Jonathan M.; Greve, Ralf; Hoffman, Matthew J.; Humbert, Angelika; Huybrechts, Philippe; Kleiner, Thomas; Larour, Eric; Leguy, Gunter; Lipscomb, William H.; Lowry, Daniel; Mengel, Matthias; Morlighem, Mathieu; Pattyn, Frank; Payne, Anthony J.; Pollard, David; Price, Stephen F.; Quiquet, Aurélien; Reerink, Thomas J.; Reese, Ronja; Rodehacke, Christian B.; Schlegel, Nicole-Jeanne; Shepherd, Andrew; Sun, Sainan; Sutter, Johannes; Van Breedam, Jonas; van de Wal, Roderik S. W.; Winkelmann, Ricarda; Zhang, Tong
    Ice sheet numerical modeling is an important tool to estimate the dynamic contribution of the Antarctic ice sheet to sea level rise over the coming centuries. The influence of initial conditions on ice sheet model simulations, however, is still unclear. To better understand this influence, an initial state intercomparison exercise (initMIP) has been developed to compare, evaluate, and improve initialization procedures and estimate their impact on century-scale simulations. initMIP is the first set of experiments of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6), which is the primary Coupled Model Intercomparison Project Phase 6 (CMIP6) activity focusing on the Greenland and Antarctic ice sheets. Following initMIP-Greenland, initMIP-Antarctica has been designed to explore uncertainties associated with model initialization and spin-up and to evaluate the impact of changes in external forcings. Starting from the state of the Antarctic ice sheet at the end of the initialization procedure, three forward experiments are each run for 100 years: a control run, a run with a surface mass balance anomaly, and a run with a basal melting anomaly beneath floating ice. This study presents the results of initMIP-Antarctica from 25 simulations performed by 16 international modeling groups. The submitted results use different initial conditions and initialization methods, as well as ice flow model parameters and reference external forcings. We find a good agreement among model responses to the surface mass balance anomaly but large variations in responses to the basal melting anomaly. These variations can be attributed to differences in the extent of ice shelves and their upstream tributaries, the numerical treatment of grounding line, and the initial ocean conditions applied, suggesting that ongoing efforts to better represent ice shelves in continental-scale models should continue.