Patrick J. Applegate

Comment on “Absence of Cooling in New Zealand and the Adjacent Ocean During the Younger Dryas Chronozone”

Barrows et al. (Reports, 5 October 2007, p. 86) presented cosmogenic exposure dates and data from an ocean sediment core that challenge evidence for glacier advance in New Zealand during the Younger Dryas event. We use modeling of geomorphic processes to argue that their cosmogenic exposure dates are inconclusive.

Late Holocene fluctuations of Qori Kalis outlet glacier, Quelccaya Ice Cap, Peruvian Andes

Geology v. 42, p. [347–350][1], doi:10.1130/G35245.1 There was an error in determining the number of 10Be atoms per gram of quartz for samples JS-09-20, -24, -14, and -15 and, thus, the calculated 10Be ages. All usage of these samples and their ages has been corrected in the GSA Data Repository (

How effective is albedo modification (solar radiation management geoengineering) in preventing sea-level rise from the Greenland Ice Sheet?

Albedo modification (AM) is sometimes characterized as a potential means of avoiding climate threshold responses, including large-scale ice sheet mass loss. Previous work has investigated the effects of AM on total sea-level rise over the present century, as well as AMs ability to reduce long-term (103 yr) contributions to sea-level rise from the Greenland Ice Sheet (GIS). These studies have broken new ground, but neglect important feedbacks in the GIS system, or are silent on AMs effectiveness over the short time scales that may be most relevant for decision-making (<103 yr). Here, we assess AMs ability to reduce GIS sea-level contributions over decades to centuries, using a simplified ice sheet model. We drive this model using a business-as-usual base temperature forcing scenario, as well as scenarios that reflect AM-induced temperature stabilization or temperature drawdown. Our model results suggest that (i) AM produces substantial near-term reductions in the rate of GIS-driven sea-level rise. However, (ii) sea-level rise contributions from the GIS continue after AM begins. These continued sea level rise contributions persist for decades to centuries after temperature stabilization and temperature drawdown begin, unless AM begins in the next few decades. Moreover, (iii) any regrowth of the GIS is delayed by decades or centuries after temperature drawdown begins, and is slow compared to pre-AM rates of mass loss. Combined with recent work that suggests AM would not prevent mass loss from the West Antarctic Ice Sheet, our results provide a nuanced picture of AMs possible effects on future sea-level rise.

Increasing temperature forcing reduces the Greenland Ice Sheet’s response time scale

Damages from sea level rise, as well as strategies to manage the associated risk, hinge critically on the time scale and eventual magnitude of sea level rise. Satellite observations and paleo-data suggest that the Greenland Ice Sheet (GIS) loses mass in response to increased temperatures, and may thus contribute substantially to sea level rise as anthropogenic climate change progresses. The time scale of GIS mass loss and sea level rise are deeply uncertain, and are often assumed to be constant. However, previous ice sheet modeling studies have shown that the time scale of GIS response likely decreases strongly with increasing temperature anomaly. Here, we map the relationship between temperature anomaly and the time scale of GIS response, by perturbing a calibrated, three-dimensional model of GIS behavior. Additional simulations with a profile, higher-order, ice sheet model yield time scales that are broadly consistent with those obtained using the three-dimensional model, and shed light on the feedbacks in the ice sheet system that cause the time scale shortening. Semi-empirical modeling studies that assume a constant time scale of sea level adjustment, and are calibrated to small preanthropogenic temperature and sea level changes, may underestimate future sea level rise. Our analysis suggests that the benefits of reducing greenhouse gas emissions, in terms of avoided sea level rise from the GIS, may be greatest if emissions reductions begin before large temperature increases have been realized. Reducing anthropogenic climate change may also allow more time for design and deployment of risk management strategies by slowing sea level contributions from the GIS.

Calibrating an Ice Sheet Model Using High-Dimensional Binary Spatial Data

Rapid retreat of ice in the Amundsen Sea sector of West Antarctica may cause drastic sea level rise, posing significant risks to populations in low-lying coastal regions. Calibration of computer models representing the behavior of the West Antarctic Ice Sheet is key for informative projections of future sea level rise. However, both the relevant observations and the model output are high-dimensional binary spatial data; existing computer model calibration methods are unable to handle such data. Here we present a novel calibration method for computer models whose output is in the form of binary spatial data. To mitigate the computational and inferential challenges posed by our approach, we apply a generalized principal component based dimension reduction method. To demonstrate the utility of our method, we calibrate the PSU3D-ICE model by comparing the output from a 499-member perturbed-parameter ensemble with observations from the Amundsen Sea sector of the ice sheet. Our methods help rigorously characterize the parameter uncertainty even in the presence of systematic data-model discrepancies and dependence in the errors. Our method also helps inform environmental risk analyses by contributing to improved projections of sea level rise from the ice sheets. Supplementary materials for this article are available online.

A simple, physically motivated model of sea-level contributions from the Greenland ice sheet in response to temperature changes

Sea level could rise by several meters over the next centuries. The Greenland ice sheet could be an important contributor to future sea-level rise, because of its large volume and its high sensitivity to surface air temperature increases. Frameworks for the integrated climate risk management often require fast, simplified treatments of sea-level rise, in particular for estimating the risks associated with low probabilities but potentially high impacts. State-of-the-art ice sheet models provide important insights, but are often computationally too demanding to evaluate tail-area risks. Here we present SIMPLE, a physically motivated model of the Greenland ice sheet in response to temperature changes. SIMPLE can skillfully reproduce the results from a three-dimensional ice sheet model and outperforms existing simple models, after similar calibration. We anticipate that SIMPLE will be calibrated to other ice sheet models and can provide a fast approximation (emulator) for such models in studies that require many model evaluations. SIMPLE is a fast physically motivated model of the Greenland ice sheet.It provides fast approximations in studies that require many model evaluations.It skillfully reproduces 3D ice sheet model simulations over a wide range of forcings.SIMPLE outperforms existing simplified representations, after similar calibration.

Improving ice sheet model calibration using paleoclimate and modern data

Human-induced climate change may cause significant ice volume loss from the West Antarctic Ice Sheet (WAIS). Projections of ice volume change from ice-sheet models and corresponding future sea-level rise have large uncertainties due to poorly constrained input parameters. In most future applications to date, model calibration has utilized only modern or recent (decadal) observations, leaving input parameters that control the long-term behavior of WAIS largely unconstrained. Many paleo-observations are in the form of localized time series, while modern observations are non-Gaussian spatial data; combining information across these types poses non-trivial statistical challenges. Here we introduce a computationally efficient calibration approach that utilizes both modern and paleo-observations to generate better-constrained ice volume projections. Using fast emulators built upon principal component analysis and a reduced dimension calibration model, we can efficiently handle high-dimensional and non-Gaussian data. We apply our calibration approach to the PSU3D-ICE model which can realistically simulate long-term behavior of WAIS. Our results show that using paleo observations in calibration significantly reduces parametric uncertainty, resulting in sharper projections about the future state of WAIS. One benefit of using paleo observations is found to be that unrealistic simulations with overshoots in past ice retreat and projected future regrowth are eliminated.

Challenges in the Use of Cosmogenic Exposure Dating of Moraine Boulders to Trace the Geographic Extents of Abrupt Climate Changes : The Younger Dryas Example

Cosmogenic exposure dating has sometimes been used to identify moraines associated with short-lived climatic events, such as the Younger Dryas (12.9-11.7 ka). Here we point out two remaining challe ...