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End date: 2020 × Start date: 2020 × End date: 2017 × Type: Text × Publisher: Göttingen : Copernicus × WGL Institute: PIK ×

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Now showing 1 - 4 of 4
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    Joint Editorial "on the future of journal publications in hydrology"
    (Göttingen : Copernicus, 2014) Blöschl, G.; Bárdossy, A.; Koutsoyiannis, D.; Kundzewicz, Z.W.; Littlewood, I.; Montanari, A.; Savenije, H.
    [No abstract available]
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    The HadGEM2-ES implementation of CMIP5 centennial simulations
    (Göttingen : Copernicus, 2011) Jones, C.D.; Hughes, J.K.; Bellouin, N.; Hardiman, S.C.; Jones, G.S.; Knight, J.; Liddicoat, S.; O'Connor, F.M.; Andres, R.J.; Bell, C.; Boo, K.-O.; Bozzo, A.; Butchart, N.; Cadule, P.; Corbin, K.D.; Doutriaux-Boucher, M.; Friedlingstein, P.; Gornall, J.; Gray, L.; Halloran, P.R.; Hurtt, G.; Ingram, W.J.; Lamarque, J.-F.; Law, R.M.; Meinshausen, M.; Osprey, S.; Palin, E.J.; Parsons, Chini, L.; Raddatz, T.; Sanderson, M.G.; Sellar, A.A.; Schurer, A.; Valdes, P.; Wood, N.; Woodward, S.; Yoshioka, M.; Zerroukat, M.
    The scientific understanding of the Earth's climate system, including thecentral question of how the climate system is likely to respond tohuman-induced perturbations, is comprehensively captured in GCMs and EarthSystem Models (ESM). Diagnosing the simulated climate response, andcomparing responses across different models, is crucially dependent ontransparent assumptions of how the GCM/ESM has been driven - especiallybecause the implementation can involve subjective decisions and may differbetween modelling groups performing the same experiment. This paper outlinesthe climate forcings and setup of the Met Office Hadley Centre ESM, HadGEM2-ES for the CMIP5 set of centennial experiments. We document theprescribed greenhouse gas concentrations, aerosol precursors, stratosphericand tropospheric ozone assumptions, as well as implementation of land-usechange and natural forcings for the HadGEM2-ES historical and futureexperiments following the Representative Concentration Pathways. Inaddition, we provide details of how HadGEM2-ES ensemble members wereinitialised from the control run and how the palaeoclimate and AMIPexperiments, as well as the "emission-driven" RCP experiments wereperformed.
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    Statistical characteristics of surrogate data based on geophysical measurements
    (Göttingen : Copernicus, 2006) Venema, V.; Bachner, S.; Rust, H.W.; Simmer, C.
    In this study, the statistical properties of a range of measurements are compared with those of their surrogate time series. Seven different records are studied, amongst others, historical time series of mean daily temperature, daily rain sums and runoff from two rivers, and cloud measurements. Seven different algorithms are used to generate the surrogate time series. The best-known method is the iterative amplitude adjusted Fourier transform (IAAFT) algorithm, which is able to reproduce the measured distribution as well as the power spectrum. Using this setup, the measurements and their surrogates are compared with respect to their power spectrum, increment distribution, structure functions, annual percentiles and return values. It is found that the surrogates that reproduce the power spectrum and the distribution of the measurements are able to closely match the increment distributions and the structure functions of the measurements, but this often does not hold for surrogates that only mimic the power spectrum of the measurement. However, even the best performing surrogates do not have asymmetric increment distributions, i.e., they cannot reproduce nonlinear dynamical processes that are asymmetric in time. Furthermore, we have found deviations of the structure functions on small scales.
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    Testing the detectability of spatio-temporal climate transitions from paleoclimate networks with the start model
    (Göttingen : Copernicus, 2014) Rehfeld, K.; Molkenthin, N.; Kurths, J.
    A critical challenge in paleoclimate data analysis is the fact that the proxy data are heterogeneously distributed in space, which affects statistical methods that rely on spatial embedding of data. In the paleoclimate network approach nodes represent paleoclimate proxy time series, and links in the network are given by statistically significant similarities between them. Their location in space, proxy and archive type is coded in the node attributes. We develop a semi-empirical model for Spatio- Temporally AutocoRrelated Time series, inspired by the interplay of different Asian Summer Monsoon (ASM) systems. We use an ensemble of transition runs of this START model to test whether and how spatio-temporal climate transitions could be detectable from (paleo)climate networks. We sample model time series both on a grid and at locations at which paleoclimate data are available to investigate the effect of the spatially heterogeneous availability of data. Node betweenness centrality, averaged over the transition region, does not respond to the transition displayed by the START model, neither in the grid-based nor in the scattered sampling arrangement. The regionally defined measures of regional node degree and cross link ratio, however, are indicative of the changes in both scenarios, although the magnitude of the changes differs according to the sampling. We find that the START model is particularly suitable for pseudo-proxy experiments to test the technical reconstruction limits of paleoclimate data based on their location, and we conclude that (paleo)climate networks are suitable for investigating spatio-temporal transitions in the dependence structure of underlying climatic fields.