ALBERT

Description: Central Asia is one of the largest arid regions in the world, however, multiple lakes have existed here since the Neogene. These lakes were able to sustain themselves despite the aridification trend in Asia through the PlioPleistocene. For example, long-term geological multiproxy records, including carbonate δ18O, from lake sediments of the Qaidam, Gaxun Nur, and Orog Nuur Basins indicate multiple changes in the hydrological cycle of the region with alternate phases of prevailing evaporation and precipitation. These changes are attributed either to Neogene global climate change or regional tectonic events. In this study, we use the isotope-equipped atmospheric general circulation model ECHAM5-wiso for modeling of Asia climate evolution and associated changes in precipitation δ18O during key periods of the Neogene. High-resolution simulations (T159L31, ca. 0.8°x0.8° and 31 vertical levels, 6 hour output frequency) with Mid-Holocene, Pleistocene, Pliocene and Miocene boundary conditions allow us to estimate the contributions of global climate change into the hydrological budget over the Central Asia. We complement this work with a Lagrangian Trajectory analysis (wind back-trajectories) applied to the ECHAM5-wiso outputs to trace changes in the origin of precipitation-producing air masses. We show that in addition to precipitation amount variations associated with changes in large-scale atmosphere dynamics, considerable changes in moisture sources between the time slices considered contribute to the isotopic signature of precipitation within the Qaidam, Gaxun Nur, and Orog Nuur Basins. Finally, comparison of simulated δ18O results to wind backtrajectory analysis suggests that local process, such as moisture recycling, exert an increasing control for more recent time periods.

Description: Understanding the dynamics of warm climate states has gained increasing importance in the face of anthropogenic climate change. During the Last Interglacial (LIG, ∼128 to 116 ka), greenhouse gas concentrations and high latitude insolation were higher than pre-industrial levels, causing a high-latitude warming (Turney and Jones, 2010; Pfeiffer and Lohmann, 2016). We present a suite of climate model results (COSMOS, MPI-ESM, AWI-CM, EC-Earth) to evaluate the patterns and compare the simulations with the above-mentioned surface temperature reconstructions, seasonal archives (Felis et al., 2015; Brocas et al., 2017), and sea ice reconstructions (Stein et al., 2017). As a result of this modestly warmer climate, polar ice sheets were smaller and estimates report that the global mean sea level was 6-9 meters higher than today (Dutton et al., 2015). The sensitivity of the Antarctic Ice sheet is related to the local temperature around the West Antarctic Ice Sheet (WAIS) (Sutter et al., 2016). Our ice sheet model experiments indicate that a 2-3°C local warming causes already a partially collapsed, irreversible WAIS. A pronounced subsurface oceanic warming can destabilize the WAIS, resulting in an oceanic gateway between the Ross and Weddell Seas. A sensitivity study using the new oceanic gateway between the Atlantic and Pacific Oceans as a bathymetrical boundary condition indicates that this region would be covered by sea ice. Mixing due to sea-ice formation prevents a pronounced warming around the WAIS and would stabilize the WAIS. Thus, the disintegration of the WAIS is probably related to non-local influences like in Hellmer et al. (2017) where the shelves of West Antarctica are warmed from below by Circumpolar Deep Water.

Description: In this manuscript we describe the experimental procedure employed at the Alfred Wegener Institute in Germany in the preparation of the simulations for the Pliocene Model Intercomparison Project (PlioMIP). We present a description of the utilized Community Earth System Models (COSMOS, version: COSMOS-landveg r2413, 2009) and document the procedures that we applied to transfer the Pliocene Research, Interpretation and Synoptic Mapping (PRISM) Project mid-Pliocene reconstruction into model forcing fields. The model setup and spin-up procedure are described for both the paleo- and preindustrial (PI) time slices of PlioMIP experiments 1 and 2, and general results that depict the performance of our model setup for mid-Pliocene conditions are presented. The mid-Pliocene, as simulated with our COSMOS setup and PRISM boundary conditions, is both warmer and wetter in the global mean than the PI. The globally averaged annual mean surface air temperature in the mid-Pliocene standalone atmosphere (fully coupled atmosphere-ocean) simulation is 17.35 °C (17.82 °C), which implies a warming of 2.23 °C (3.40 °C) relative to the respective PI control simulation.

Description: Climate and environments of the mid-Pliocene warm period (3.264 to 3.025 Ma) have been extensively studied. Whilst numerical models have shed light on the nature of climate at the time, uncertainties in their predictions have not been systematically examined. The Pliocene Model Intercomparison Project quantifies uncertainties in model outputs through a coordinated multi-model and multi-model/data intercomparison. Whilst commonalities in model outputs for the Pliocene are clearly evident, we show substantial variation in the sensitivity of models to the implementation of Pliocene boundary conditions. Models appear able to reproduce many regional changes in temperature reconstructed from geological proxies. However, data/model comparison highlights that models potentially underestimate polar amplification. To assert this conclusion with greater confidence, limitations in the time-averaged proxy data currently available must be addressed. Furthermore, sensitivity tests exploring the known unknowns in modelling Pliocene climate specifically relevant to the high latitudes are essential (e.g. palaeogeography, gateways, orbital forcing and trace gasses). Estimates of longer-term sensitivity to CO2 (also known as Earth System Sensitivity; ESS), support previous work suggesting that ESS is greater than Climate Sensitivity (CS), and suggest that the ratio of ESS to CS is between 1 and 2, with a "best" estimate of 1.5.