On the Reconstruction of Palaeo-Ice Sheets: Recent Advances and Future Challenges

Reconstructing the growth and decay of palaeo-ice sheets is critical to understanding mechanisms of global climate change and associated sea-level fluctuations in the past, present and future. The significance of palaeo-ice sheets is further underlined by the broad range of disciplines concerned with reconstructing their behaviour, many of which have undergone a rapid expansion since the 1980s. In particular, there has been a major increase in the size and qualitative diversity of empirical data used to reconstruct and date ice sheets, and major improvements in our ability to simulate their dynamics in numerical ice sheet models. These developments have made it increasingly necessary to forge interdisciplinary links between sub-disciplines and to link numerical modelling with observations and dating of proxy records. The aim of this paper is to evaluate recent developments in the methods used to reconstruct ice sheets and outline some key challenges that remain, with an emphasis on how future work might integrate terrestrial and marine evidence together with numerical modelling. Our focus is on pan-ice sheet reconstructions of the last deglaciation, but regional case studies are used to illustrate methodological achievements, challenges and opportunities. Whilst various disciplines have made important progress in our understanding of ice-sheet dynamics, it is clear that data-model integration remains under-used, and that uncertainties remain poorly quantified in both empirically-based and numerical ice-sheet reconstructions. The representation of past climate will continue to be the largest source of uncertainty for numerical modelling. As such, palaeo-observations are critical to constrain and validate modelling. State-of-the-art numerical models will continue to improve both in model resolution and in the breadth of inclusion of relevant processes, thereby enabling more accurate and more direct comparison with the increasing range of palaeo-observations. Thus, the capability is developing to use all relevant palaeo-records to more strongly constrain deglacial (and to a lesser extent pre-LGM) ice sheet evolution. In working towards that goal, the accurate representation of uncertainties is required for both constraint data and model outputs. Close cooperation between modelling and data-gathering communities is essential to ensure this capability is realised and continues to progress

A comparison of two spectral approaches for computing the Earth response to surface loads

When predicting the deformation of the Earth under surface loads, most models follow the same methodology, consisting of producing a unit response that is then con-volved with the appropriate surface forcing. These models take into account the whole Earth, and are generally spherical, computing a unit response in terms of its spherical harmonic representation through the use of load Love numbers. From these Love numbers, the spatial pattern of the bedrock response to any particular scenario can be obtained. Two different methods are discussed here. The first, which is related to the convolution in the classical sense, appears to be very sensitive to the total number of degrees used when summing these Love numbers in the harmonic series in order to obtain the corresponding Green’s function. We will see from the spectral properties of these Love numbers how to compute these series correctly and how consequently to eliminate in practice the sensitivity to the number of degrees (Gibbs Phenomena). The second method relies on a preliminary harmonic decomposition of the load, which reduces the convolution to a simple product within Fourier space. The convergence properties of the resulting Fourier series make this approach less sensitive to any harmonic cut-off. However, this method can be more or less computationally expensive depending on the loading characteristics. This paper describes these two methods, how to eliminate Gibbs phenomena in the Green’s function method, and shows how the load characteristics as well as the available computational resources can be determining factors in selecting one approach

Measurement and simulation of rotationally-resolved chemiluminescence spectra in flames

Brockhinke A, Krüger J, Heusing M, Letzgus M. Measurement and simulation of rotationally-resolved chemiluminescence spectra in flames. APPLIED PHYSICS B. 2012;107(3):539-549