Search

It has long been hypothesized that climate can modify both the pattern and magnitude of erosion in mountainous landscapes, thereby controlling morphology, rates of deformation, and potentially modulating global carbon and nutrient cycles through weathering feedbacks. Although conceptually appealing, geologic evidence for a direct climatic control on erosion has remained ambiguous owing to a lack of high-resolution, long-term terrestrial records and suitable field sites. Here we provide direct terrestrial field evidence for long-term synchrony between erosion rates and Milankovitch-driven, 400-kyr eccentricity cycles using a Plio-Pleistocene cosmogenic radionuclide paleo-erosion rate record from the southern Central Andes. The observed climate-erosion coupling across multiple orbital cycles, when combined with results from the intermediate complexity climate model CLIMBER-2, are consistent with the hypothesis that relatively modest fluctuations in precipitation can cause synchronous and nonlinear responses in erosion rates as landscapes adjust to ever-evolving hydrologic boundary conditions imposed by oscillating climate regimes.

Over the last decade, our understanding of climate sensitivity has improved considerably. The climate system shows variability on many timescales, is subject to non-stationary forcing and it is most likely out of equilibrium with the changes in the radiative forcing. Slow and fast feedbacks complicate the interpretation of geological records as feedback strengths vary over time. In the geological past, the forcing timescales were different than at present, suggesting that the response may have behaved differently. Do these insights constrain the climate sensitivity relevant for the present day? In this paper, we review the progress made in theoretical understanding of climate sensitivity and on the estimation of climate sensitivity from proxy records. Particular focus lies on the background state dependence of feedback processes and on the impact of tipping points on the climate system. We suggest how to further use palaeo data to advance our understanding of the currently ongoing climate change.

The strongly varying benthic δ18 O levels of the early and mid-Miocene (23 to 14 Myr ago) are primarily caused by a combination of changes in Antarctic Ice Sheet (AIS) volume and deep-ocean temperatures. These factors are coupled since AIS changes affect deep-ocean temperatures. It has recently been argued that this is due to changes in ice sheet area rather than volume because area changes affect the surface albedo. This finding would be important when the transient AIS grows relatively faster in extent than in thickness, which we test here. We analyse simulations of Miocene AIS variability carried out using the three-dimensional ice sheet model IMAU-ICE forced by warm (high CO 2 , no ice) and cold (low CO 2 , large East AIS) climate snapshots. These simulations comprise equilibrium and idealized quasi-orbital transient runs with strongly varying CO 2 levels (280 to 840 ppm). Our simulations show a limited direct effect of East AIS changes on Miocene orbital-timescale benthic δ18 O variability because of the slow build-up of volume. However, we find that relative to the equilibrium ice sheet size, the AIS area adapts significantly faster and more strongly than volume to the applied forcing variability. Consequently, during certain intervals the ice sheet is receding at the margins, while ice is still building up in the interior. That means the AIS does not adapt to a changing equilibrium size at the same rate or with the same sign everywhere. Our results indicate that the Miocene Antarctic Ice Sheet affects deep-ocean temperatures more than its volume suggests. [ABSTRACT FROM AUTHOR]

The strongly varying benthic δ18O levels of the early and mid-Miocene (23 to 14 Myr ago) are primarily caused by a combination of changes in Antarctic ice sheet (AIS) volume and deep ocean temperatures. These factors are coupled since AIS changes affect deep ocean temperatures. It has recently been argued that this is due to changes in ice sheet area rather than volume, because area changes affect the surface albedo. This would be important when the transient AIS grows relatively faster in extent than in thickness, which we test here. We analyse simulations of Miocene AIS variability carried out using the three-dimensional ice-sheet model IMAU-ICE forced by warm (high CO2, no ice) and cold (low CO2, large East-AIS) climate snapshots. These simulations comprise equilibrium and idealised quasi-orbital transient runs with strongly varying CO2 levels (280 to 840 ppm). Our simulations show limited direct effect of East-AIS changes on Miocene orbital timescale benthic δ18O variability, because of the slow build-up of volume. However, we find that AIS area responds significantly faster and more strongly than volume to the applied forcing variability. Consequently, during certain intervals the ice sheet is receding at the margins, while ice is still building up in the interior. That means the AIS does not adapt to a changing equilibrium size at the same rate or with the same sign everywhere. Our results indicate that the Miocene Antarctic ice sheet affects deep ocean temperatures more than its volume suggests. [ABSTRACT FROM AUTHOR]

During the last glacial cycle (LGC), ice sheets covered large parts of Eurasia and North America, which resulted in ∼120 m of sea level change. Ice sheet–climate interactions have considerable influence on temperature and precipitation patterns and therefore need to be included when simulating this time period. Ideally, ice sheet–climate interactions are simulated by a high-resolution Earth system model. While these models are capable of simulating climates at a certain point in time, such as the pre-industrial (PI) or the Last Glacial Maximum (LGM; 21 000 years ago), a full transient glacial cycle is currently computationally unfeasible as it requires a too-large amount of computation time. Nevertheless, ice sheet models require forcing that captures the gradual change in climate over time to calculate the accumulation and melt of ice and its effect on ice sheet extent and volume changes. Here we simulate the LGC using an ice sheet model forced by LGM and PI climates. The gradual change in climate is modelled by transiently interpolating between pre-calculated results from a climate model for the LGM and the PI. To assess the influence of ice sheet–climate interactions, we use two different interpolation methods: the climate matrix method, which includes a temperature–albedo and precipitation–topography feedback, and the glacial index method, which does not. To investigate the sensitivity of the results to the prescribed climate forcing, we use the output of several models that are part of the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3). In these simulations, ice volume is prescribed, and the climate is reconstructed with a general circulation model (GCM). Here we test those models by using their climate to drive an ice sheet model over the LGC. We find that the ice volume differences caused by the climate forcing exceed the differences caused by the interpolation method. Some GCMs produced unrealistic LGM volumes, and only four resulted in reasonable ice sheets, with LGM Northern Hemisphere sea level contribution ranging between 74–113 m with respect to the present day. The glacial index and climate matrix methods result in similar ice volumes at the LGM but yield a different ice evolution with different ice domes during the inception phase of the glacial cycle and different sea level rates during the deglaciation phase. The temperature–albedo feedback is the main cause of differences between the glacial index and climate matrix methods. [ABSTRACT FROM AUTHOR]

During the Last Glacial Cycle (LGC), ice sheets covered large parts of Eurasia and North America which resulted in ~120 meters of sea level change. Ice sheet - climate interactions have considerable influence on temperature and precipitation patterns, and therefore need to be included when simulating this time period. Ideally, ice sheet - climate interactions are simulated by a high-resolution earth system model. While these models are capable of simulating climates at a certain point in time, such as the Pre-Industrial (PI) or the Last Glacial Maximum (LGM; 21,000 years ago), a full glacial cycle is currently unfeasible as it requires a too large amount of computation time. Nevertheless, ice-sheet models require forcing that captures the gradual change in climate over time to calculate the accumulation and melt of ice and its effect on ice sheet extent and volume changes. Here we simulate the LGC using an ice sheet model forced by LGM and PI climates. The gradual change in climate is modelled by transiently interpolating between pre-calculated results from a climate model for the LGM and the PI. To assess the influence of ice sheet - climate interactions, we use two different interpolation methods: The climate matrix method, which includes these interactions, and the glacial index method, which does not. To investigate the sensitivity of the results to the prescribed climate forcing, we use the output of several models that are part of the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3). In these simulations, ice volume is prescribed and the climate is reconstructed. Here we test those models by using their climate to drive an ice sheet model over the LGC. We find that the differences caused by the climate forcing exceeds the differences caused by the interpolation method. Some General Circulation Models (GCMs) produced unrealistic LGM volumes and only four resulted in reasonable ice sheets with LGM Northern Hemisphere sea level contribution ranging between 74 - 113 meters with respect to the present day. The glacial index and climate matrix methods result in similar ice volumes at LGM but yield a different ice evolution with different ice domes during the inception phase of the glacial cycle, and different sea-level rates during the deglaciation phase. The temperature-albedo feedback is the main cause of differences between the glacial index and climate matrix methods. [ABSTRACT FROM AUTHOR]

The influence of long-term processes in the climate system, such as land ice changes, has to be compensated for when comparing climate sensitivity derived from paleodata with equilibrium climate sensitivity (ECS) calculated by climate models, which is only generated by a CO2 change. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI], that relates the impact of land ice changes on global temperature to that of CO2 changes, in our calculation of climate sensitivity from paleodata. We apply our new approach to a proxy-inferred paleoclimate dataset, and find an equivalent ECS of 5.6 ± 1.3 K per CO2 doubling. The substantial uncertainty herein is generated by the range in ε[LI] we use, which is based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum (LGM) temperature anomaly (46 ± 14%). The low end of our ECS estimate, which concurs with estimates from other approaches, tallies with a large influence for land ice changes. To separately assess this influence, we analyse output of the PMIP3 climate model intercomparison project. From this data, we infer a functional intermodel relation between global and high-latitude temperature changes at the LGM with respect to the pre-industrial climate, and the temperature anomaly caused by a CO2 change. Applying this relation to our dataset, we find a considerable 64% influence for land ice changes on the LGM temperature anomaly. This is even higher than the range used before, and leads to an equivalent ECS of 3.8 K per CO2 doubling. Together, our results suggest that land ice changes play a key role in the variability of Late Pleistocene temperatures. [ABSTRACT FROM AUTHOR]

Since the inception of the Antarctic ice sheet at the Eocene-Oligocene Transition (~ 34 Myr ago), land ice has played a crucial role in Earth's climate. Through the ice-albedo and surface-height-temperature feedbacks, land ice variability strengthens atmospheric temperature changes induced by orbital and CO2 variations. Quantification of these feedbacks on long time scales has hitherto scarcely been undertaken. In this study, we use a zonally averaged energy balance climate model bi-directionally coupled to a one-dimensional ice sheet model. The relative simplicity of these models allows us to perform integrations over the past 38 Myr in a fully transient fashion, using a benthic oxygen isotope record as forcing to inversely simulate CO2. Output of the model are mutually consistent records of CO2, temperature, ice volume-equivalent sea level and benthic δ18O. Firstly, we investigate the relation between global temperature and CO2, which changes once the model run has experienced high CO2 concentrations. Secondly, we study the influence of ice sheets on the evolution of global temperature and polar amplification by comparing runs with ice sheet-climate interaction switched on and off. We find that ice volume variability has a strong enhancing effect on atmospheric temperature changes, particularly in the regions where the ice sheets are located. As a result, polar amplification in the Northern Hemisphere decreases towards warmer climates as there is little land ice left to melt. Conversely, decay of the Antarctic ice sheet increases polar amplification in the Southern Hemisphere in the high-CO2 regime. Our results also show that in cooler climates than the pre-industrial, the ice-albedo feedback predominates the surface-height-temperature feedback, while in warmer climates they are more equal in strength. [ABSTRACT FROM AUTHOR]