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    Similarity estimators for irregular and age-uncertain time series
    (München : European Geopyhsical Union, 2014) Rehfeld, K.; Kurths, J.
    Paleoclimate time series are often irregularly sampled and age uncertain, which is an important technical challenge to overcome for successful reconstruction of past climate variability and dynamics. Visual comparison and interpolation-based linear correlation approaches have been used to infer dependencies from such proxy time series. While the first is subjective, not measurable and not suitable for the comparison of many data sets at a time, the latter introduces interpolation bias, and both face difficulties if the underlying dependencies are nonlinear. In this paper we investigate similarity estimators that could be suitable for the quantitative investigation of dependencies in irregular and age-uncertain time series. We compare the Gaussian-kernel-based cross-correlation (gXCF, Rehfeld et al., 2011) and mutual information (gMI, Rehfeld et al., 2013) against their interpolation-based counterparts and the new event synchronization function (ESF). We test the efficiency of the methods in estimating coupling strength and coupling lag numerically, using ensembles of synthetic stalagmites with short, autocorrelated, linear and nonlinearly coupled proxy time series, and in the application to real stalagmite time series. In the linear test case, coupling strength increases are identified consistently for all estimators, while in the nonlinear test case the correlation-based approaches fail. The lag at which the time series are coupled is identified correctly as the maximum of the similarity functions in around 60–55% (in the linear case) to 53–42% (for the nonlinear processes) of the cases when the dating of the synthetic stalagmite is perfectly precise. If the age uncertainty increases beyond 5% of the time series length, however, the true coupling lag is not identified more often than the others for which the similarity function was estimated. Age uncertainty contributes up to half of the uncertainty in the similarity estimation process. Time series irregularity contributes less, particularly for the adapted Gaussian-kernel-based estimators and the event synchronization function. The introduced link strength concept summarizes the hypothesis test results and balances the individual strengths of the estimators: while gXCF is particularly suitable for short and irregular time series, gMI and the ESF can identify nonlinear dependencies. ESF could, in particular, be suitable to study extreme event dynamics in paleoclimate records. Programs to analyze paleoclimatic time series for significant dependencies are included in a freely available software toolbox.
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    Scheme for calculation of multi-layer cloudiness and precipitation for climate models of intermediate complexity
    (München : European Geopyhsical Union, 2013) Eliseev, A.V.; Coumou, D.; Chernokulsky, A.V.; Petoukhov, V.; Petri, S.
    In this study we present a scheme for calculating the characteristics of multi-layer cloudiness and precipitation for Earth system models of intermediate complexity (EMICs). This scheme considers three-layer stratiform cloudiness and single-column convective clouds. It distinguishes between ice and droplet clouds as well. Precipitation is calculated by using cloud lifetime, which depends on cloud type and phase as well as on statistics of synoptic and convective disturbances. The scheme is tuned to observations by using an ensemble simulation forced by the ERA-40-derived climatology for 1979–2001. Upon calibration, the scheme realistically reproduces basic features of fields of cloud fractions, cloud water path, and precipitation. The simulated globally and annually averaged total cloud fraction is 0.59, and the simulated globally averaged annual precipitation is 100 cm yr−1. Both values agree with empirically derived values. The simulated cloud water path is too small, probably because the simulated vertical extent of stratiform clouds is too small. Geographical distribution and seasonal changes of calculated cloud fraction and precipitation are broadly realistic as well. However, some important regional biases still remain in the scheme, e.g. too little precipitation in the tropics. We discuss possibilities for future improvements in the scheme.
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    Parameterization for subgrid-scale motion of ice-shelf calving fronts
    (München : European Geopyhsical Union, 2011) Albrecht, T.; Martin, M.; Haseloff, M.; Winkelmann, R.; Levermann, A.
    In order to explore the response of the Greenland ice sheet (GIS) to climate change on long (centennial to multi-millennial) time scales, a regional energy-moisture balance model has been developed. This model simulates seasonal variations of temperature and precipitation over Greenland and explicitly accounts for elevation and albedo feedbacks. From these fields, the annual mean surface temperature and surface mass balance can be determined and used to force an ice sheet model. The melt component of the surface mass balance is computed here using both a positive degree day approach and a more physically-based alternative that includes insolation and albedo explicitly. As a validation of the climate model, we first simulated temperature and precipitation over Greenland for the prescribed, present-day topography. Our simulated climatology compares well to observations and does not differ significantly from that of a simple parameterization used in many previous simulations. Furthermore, the calculated surface mass balance using both melt schemes falls within the range of recent regional climate model results. For a prescribed, ice-free state, the differences in simulated climatology between the regional energy-moisture balance model and the simple parameterization become significant, with our model showing much stronger summer warming. When coupled to a three-dimensional ice sheet model and initialized with present-day conditions, the two melt schemes both allow realistic simulations of the present-day GIS.