Abstract. Rising global sea levels are one of many impacts, the current anthropogenic global warming poses to humanity. The Antarctic Ice Sheet (AIS) has the potential to contribute several meters of sea level rise over the next few centuries. To predict future sea level rise contributions from ice sheets, both global and regional climate model (RCM) outputs are used as forcing in ice sheet model simulations. While the impact of different global models on future projections is well-studied, the impact of different regional models on the evolution of the AIS is not well-constrained. In our study, we investigated the impact of the choice of present-day reference RCM forcing on the evolution of the AIS. We used the Parallel Ice Sheet Model (PISM) to study the AIS in a constant forcing quasi-equilibrium state and under future projections, combining present-day RCM output with global climate model projections. Our study shows that the choice of RCM reference forcing results in uncertainties of future sea level rise predictions of 8.7 (7.3–9.5) cm in the year 2100 and 24.3 (16.3–46.5) cm in 2300 under the RCP8.5 scenario. Those uncertainties are of the same order of magnitude as the choice of the underlying ice sheet model parameterization and global climate model. Additionally, our study shows that the choice of RCM reference affects the extent of grounding line retreat in West Antarctica in future projections and can result in the potential long-term collapse of the West Antarctic Ice Sheet in quasi-equilibrium simulations. Our study therefore highlights the importance, of a careful choice of RCM reference forcing for simulations of the AIS.
Abstract Solar radiation modification (SRM) is increasingly discussed as a tool to reduce or avert global warming and concomitantly the risk of ice-sheet collapse, as is considered possible for the West Antarctic Ice Sheet (WAIS). Here we analyse the impact of stratospheric aerosol injections on the centennial-to-millennial Antarctic sea-level contribution using an ice-sheet model. We find that mid-twenty-first-century large-scale SRM could delay but ultimately not prevent WAIS collapse in a high-emissions scenario. On intermediate-emissions pathways, SRM could be an effective tool to delay or even prevent an instability of WAIS if deployed by mid-century. However, SRM interventions may be associated with substantial risks, commitments and unintended side effects; therefore, emissions reductions to prevent WAIS collapse seem to be the more practical and sensible approach at the current stage.
Abstract. Proxy-based reconstructions and climate model simulations of surface temperature trends during the Holocene disagree: While reconstructions show a cooling during the mid- and late Holocene, climate models show a continuous warming – a contradiction known as the Holocene temperature conundrum. Despite extensive research, the reason for the disagreement remains unclear. Both, missing processes in the models as well as biases in the proxies and the resulting reconstructions are possible sources of the conundrum. Here we compare our TransEBM v1.2 climate simulation as well as additional climate models of different complexity and Holocene temperature trends from the Temperature12k dataset (Kaufman et al., 2020b), with regards to model-data and model-model agreement. We show that models of all complexities disagree with mid-Holocene temperature trends in reconstructions and that this disagreement is almost independent of proxy and archive type. While, models show the highest agreement with summer temperature trends in reconstructions, our study shows that a trivial summer bias in proxies is not sufficient to explain the conundrum. Further effort to disentangle seasonal biases in proxies and the testing of potential misrepresentations in climate models, like anthropogenic land-use, in form of sensitivity experiments are needed to resolve the Holocene conundrum.
Abstract. Proxy-based reconstructions and climate model simulations of surface temperature trends during the Holocene disagree: While reconstructions show a cooling during the mid- and late Holocene, climate models show a continuous warming – a contradiction known as the Holocene temperature conundrum. Despite extensive research, the reason for the disagreement remains unclear. Both, missing processes in the models as well as biases in the proxies and the resulting reconstructions are possible sources of the conundrum. Here we compare our TransEBM v1.2 climate simulation as well as additional climate models of different complexity and Holocene temperature trends from the Temperature12k dataset (Kaufman et al., 2020b), with regards to model-data and model-model agreement. We show that models of all complexities disagree with mid-Holocene temperature trends in reconstructions and that this disagreement is almost independent of proxy and archive type. While, models show the highest agreement with summer temperature trends in reconstructions, our study shows that a trivial summer bias in proxies is not sufficient to explain the conundrum. Further effort to disentangle seasonal biases in proxies and the testing of potential misrepresentations in climate models, like anthropogenic land-use, in form of sensitivity experiments are needed to resolve the Holocene conundrum.
Climate variability is crucial to our understanding of future climate change and its impacts on societies and the natural world. However, the climate records of the observational era are too short to explore long-term variability. Conversely, an exploration of long transient simulations from state-of-the-art Earth System Models (ESMs) poses high computational demands. It is therefore pertinent to identify the level of complexity sufficient to simulate the variability of surface climate from annual to centennial and longer timescales. To this end, we use an ensemble of transient simulations of the Last Deglaciation, the last period of significant global warming. The ensemble covers an energy balance model (EBM), models of intermediate complexity (EMICs), general circulation models (GCMs) and ESMs. This constitutes a hierarchy that we categorize based on employed atmosphere and ocean components and their resolution, as well as implemented radiation, land hydrology, vegetation and aerosol schemes. To investigate the simulated variability of surface temperature and precipitation, we analyze changes in the shapes of their distributions as characterized by their higher order moments – variance, skewness, kurtosis – with warming. These higher order moments relate the tails to the extremes of the distributions. We identify spatial and temporal patterns and how they depend on model complexity. The EMICs can generally match the global and latitudinal changes in temperature variability found in more complex models. However, they lack in precipitation variability. We further find that the EMICs fail to simulate the tails of the precipitation distributions. We observe dependency of variability on the background state, generally increasing with model complexity. However, there is still a large spread between models of similar complexity, some of which can be related to differences in forcings. Furthermore, questions remain on the abilities of models of any complexity to simulate a magnitude of long-term variability similar to that found regionally in proxy reconstructions. Our analysis offers implications as to the complexity needed and sufficient for capturing the full picture of climate change and we offer some first insights into how the findings translate to future projections of climate change.
<div> <p>Much about the response of temperature variability to a change in the climate's mean state, as the one projected for the current century, remains uncertain. These uncertainties include spatiotemporal patterns, the magnitude, and, in some cases, even the sign. For the last Deglaciation, - the last change in global mean temperature of a similar degree to that expected in projections - variability analyses of climate model simulations and temperature proxies produce conflicting results.&#160;</p> </div><div> <p>Here, we build a hierarchy of transient simulations covering the period since the Last Glacial Maximum about 26k years ago. We include a range of climate models, from conceptual to complex Earth System Models. The simulations cover a variety of temporal and spatial resolutions, parameterizations, and modeled processes. For annual to multi-millennial temporal as well as regional to global spatial scales, we compare variability patterns and power spectra and analyze how they relate to model properties and the background state of Earth's climate. This allows for the examination of regional temperature differences between low, middle, and high latitudes and at locations of available paleoclimate proxy records. For sets of sensitivity experiments, we investigate effects of changes to ice sheets, sea ice, and in volcanic, solar, greenhouse, and orbital forcing on modeled climate variability.&#160;&#160;</p> </div><div> <p>Thus, our analysis provides insights into when and how models disagree with each other and with proxies, and what differences arise due to specific models, simulation setups, and boundary conditions. Based on these results, we can then gauge the degree of complexity which is required to reproduce past temperature variability and predict its changes in the future.&#160;</p> </div>
Abstract. Rising global sea levels are one of many impacts, the current anthropogenic global warming poses to humanity. The Antarctic Ice Sheet (AIS) has the potential to contribute several meters of sea level rise over the next few centuries. To predict future sea level rise contributions from ice sheets, both global and regional climate model (RCM) outputs are used as forcing in ice sheet model simulations. While the impact of different global models on future projections is well-studied, the impact of different regional models on the evolution of the AIS is not well-constrained. In our study, we investigated the impact of the choice of present-day reference RCM forcing on the evolution of the AIS. We used the Parallel Ice Sheet Model (PISM) to study the AIS in a constant forcing quasi-equilibrium state and under future projections, combining present-day RCM output with global climate model projections. Our study shows that the choice of RCM reference forcing results in uncertainties of future sea level rise predictions of 8.7 (7.3–9.5) cm in the year 2100 and 24.3 (16.3–46.5) cm in 2300 under the RCP8.5 scenario. Those uncertainties are of the same order of magnitude as the choice of the underlying ice sheet model parameterization and global climate model. Additionally, our study shows that the choice of RCM reference affects the extent of grounding line retreat in West Antarctica in future projections and can result in the potential long-term collapse of the West Antarctic Ice Sheet in quasi-equilibrium simulations. Our study therefore highlights the importance, of a careful choice of RCM reference forcing for simulations of the AIS.
<div> <p>Projections of anthropogenic climate change suggest possible surface temperature increases similar to those during past major shifts of the mean climate like the Last Deglaciation. Such shifts do not only affect the mean but rather the full probability distributions of climatic variables such as temperature and precipitation. Changes to their distributions can thus be expected for the future as well and need to be constrained. <span>&#160;</span></p> </div><div> <p>To this end, we examine transient simulations of the Last Deglaciation from a hierarchy of climate models, ranging from an energy balance model to state-of-the-art Earth System Models. Besides the mean, we use the higher moments of variability &#8211; variance, skewness, and kurtosis &#8211; to characterize changes of the distribution. The analysis covers annual to millennial timescales and examines how patterns vary with timescale and region in response to warming. Furthermore, we evaluate how the changes of the distributions affect the occurrence of extremes.&#160;<span>&#160;</span></p> </div><div> <p>To analyze the influence of forcings on the distributions, we compare the patterns of the fully-forced simulations to those in sensitivity experiments that isolate the effects of individual forcings. In particular, the effect of volcanism is examined across the hierarchy, as well as changes in ice cover, freshwater input, CO<sub><span>2</span></sub>, and orbit. While large-scale global patterns can be found, there are significant regional differences as well as differences between simulations, relating for example to differences in the modelling of ice cover changes and freshwater input. Finally, we investigate whether climate model projections show the same trends with respect to the change in moments as those found in the deglacial simulations and thus whether the patterns found might hold for future climate.<span>&#160;</span></p> </div>
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