Description: This paper investigates the long-term variability of specific weather types that are associated with damaging hailstorms in Germany for past (1971–2000) and future (2011–2050) time periods. Forty large-scale weather types are determined by the objective weather type classification scheme of German Weather Service. This scheme is applied to both reanalyses (ERA-40) and eight different regional climate model (RCM) simulations. It is shown that the RCMs are able to approximately reproduce the distribution of weather type occurrences obtained from the reference of ERA-40. Using additional insurance loss data, the weather types are further identified as hail-related or hail-unrelated. Hailstorms are neither captured comprehensively by existing observation systems nor can they be modeled reliably and the large-scale weather types are here considered as proxies for hail occurrence. Four weather types that are most likely associated with damaging hailstorms show a slight increase both during the past and future period according to the RCM simulations. A novel statistical model is developed for the probabilistic prediction of the fraction of hail damage days conditional on the weather types. The model is Bayesian and uses a Markov Chain Monte Carlo approach. For the ERA-40 reanalysis the model prediction agrees well with fraction of hail damage days observed in the insurance data. For most of the RCM projections, the statistical model predicts a slight increase in the number of hail days in the future (2031–2045), with relative changes between 7 and 15% compared to the period 1971–2000.

Description: We study the interactions of ice sheets with the other components of the climate system in a new modeling system that encompasses a wide range of interactions between ice sheets, their mass balance, the solid Earth and the climate. Forcing the model with increasing greenhouse gas concentrations allows us to study the full interactions of the different climate system components and thus deepen our understanding of the processes relevant during deglaciation. The system consists of the modified Parallel Ice Sheet Model (mPISM), the VIscoelastic Lithosphere and MAntle model (VILMA), and the Max Planck Institute Earth System Model (MPI-ESM). The surface mass balance of the ice sheets is computed with an energy balance model, shelf basal melt from temperature and salinity of the adjacent ocean. By applying VILMA, sea-level change due to ice loads is calculated considering surface deformation, eustasy and geoid change. In MPI-ESM, glaciers, topography, rivers, coastlines and bathymetry adapt to changes in ice sheets and topography. The model system is forced only with transient orbital parameters and greenhouse gas concentrations. In our experiments, the retreating ice sheets leave behind vast periglacial lakes and marginal seas. Gigantic ice sheet surges into these basins lead to the formation of large ice shelves with low surface elevations causing strong melt. Where the basins are connected to the open ocean, basal melt and calving increase the ice loss at the shelves. Over time, the retarded sea-level response shrinks the periglacial basins again. This study presents first experiments that include the full range of interactions between ice sheets, solid Earth, atmosphere and ocean circulation.

Description: The projected increases in Earth’s mean temperature entail substantial changes in the climate’s variability. Appropriate mitigation and adaptation measures require understanding of these changes since they impact for example the occurrence of extreme events. While projections of the global mean temperature are relatively well constrained based on the employed forcing scenario, they are highly uncertain with respect to the hydrological cycle and local temperature variability. Thus, examining how periods of past warming can help constrain these changes is of vital importance.To this end, we examine how the variability of surface temperature and precipitation changes in simulations of past and future warming from climate models of varying complexity and compare these with changes in proxy-based reconstructions. Based on the simulations, we analyze the moments of the distributions of temperature and precipitation (variance, skewness and kurtosis), as well as the power spectra with a focus on societally-relevant annual to centennial timescales. The analysis contrasts the projected changes under future warming scenarios with those found in transient simulations of the Last Deglaciation from models ranging from an energy balance model to Earth System Models. Changes observed in the simulations of the Last Deglaciation often highly depend on timescale and forcings, in particular changing volcanic activity, meltwater release and ice distributions alter patterns of variability. Based on this, we examine how the faster rate of future change impacts, and potentially limits, the conclusions to be drawn about future climatic changes based on past periods of warming.