2 NERC Standard Grants Awards to EARTH Researchers
12 Sep 2012
2 NERC standard grants were awarded to Cardiff researchers Dr. T.C. Hales and Dr. Stephen Barker to begin in December 2012. Details of their awards can be found below.
Assessing the role of millennial-scale variability in glacial-interglacial climate change
Stephen Barker (Cardiff University, UK), Gregor Knorr (Alfred Wegener Institute, Germany), Andy Ridgwell (University of Bristol, UK)
Funded by NERC (UK): Total project cost: ~£433k
During the Pleistocene epoch (or at least the last 800,000 years), Earth’s climate has been dominated by variations both on orbital (tens to hundreds of thousands of years) and millennial timescales. Each of these modes of variability has received significant enquiry and yet each remains enigmatic in its underlying mechanisms. Recently however, progress has been made in understanding the potential interplay between millennial-scale climate variability (involving abrupt changes in ocean circulation and the so-called bipolar seesaw) and the mechanism of deglaciation (the transition from glacial to interglacial conditions). This project aims to provide quantitative information about this link in order to learn more about the mechanism of glacial termination. Specifically, we aim to quantitatively differentiate between those millennial-scale oscillations that coincide with glacial terminations and those that do not and to determine the precise temporal relationship between seesaw oscillations, glacial terminations and changes in orbital configuration. In so doing we aim to make progress on the following outstanding questions: Are bipolar seesaw oscillations a necessary feature of glacial terminations or merely a complicating factor? Are seesaw oscillations themselves sufficient to drive glacial termination or are there particular characteristics of terminal oscillations that promote deglaciation? What are the connections between varying boundary conditions (insolation, ice volume, atmospheric CO2 concentration) and the nature of seesaw oscillations? Is there an underlying orbital parameter that ultimately controls the occurrence of glacial terminations? The project will involve a combination of quantitative data analysis and the application of state-of-the-art computer models of the climate system.
Climate History Controls Future Landslide Hazard
T.C. Hales (Cardiff University, UK), Simon Mudd (University of Edinburgh, UK)
Funded by NERC (UK): Total project cost: ~£350k
The intense precipitation associated with large storms can initiate thousands of landslides and debris flows, endangering lives and cause significant damage to infrastructure. Changes to the frequency and/or intensity of storms is a predicted consequence of anthropogenically-driven climate change, thus predictive models of landsliding are essential for mitigating these effects. Shallow landslides that initiate in soil are particularly destructive as they often initiate rapidly moving debris flows. Physically-based shallow landslide hazard models usually estimate landsliding a function of modern hydrologic, ecologic, and soil mechanical properties. The flaw in this approach is that it does not account for the "memory" of previous landslides in a catchment, where landslides are unlikely to occur twice in the same location within the short window of time (<1000 years). When landslide "memory" is considered, we hypothesise two possible effects on future landsliding: (1) the likelihood that extreme rainfall will create a large landslide event is dependent on the number of large storms that have recently occurred in a catchment, and (2) storms that initiate a 1000's of landslides may have a resonance within a landscape that causes landslides to cluster in time. Accounting for the combined role of precipitation and landscape resonance is of immediate concern as we begin to make predict hazards associated with climate change. The proposed research will quantify whether landslides are clustered in time, through the collection of a novel, large, millennial-scale dataset of landslide frequency. We will analyse landslide frequency using radiocarbon found at the base of 75 hollows (local depocentres located 10's of metres above channel heads) where shallow landslides initiate. These data, in conjunction with high resolution LiDAR topographic data, will drive the creation of a unique, probabilistic, landslide hazard model that estimates landslide hazard based on both recent precipitation and the potential resonance imparted by previous storms. Our novel landslide dataset and landslide hazard model will significantly improve our ability to predict the risks posed by landslides in current and future climate scenarios.
