This article is edited and drawn from:
Davies, B.J., 2022. Dating Glacial Landforms II: Radiometric Techniques, in: Haritashya, U. (Ed.), Treatise in Geomorphology (Second edition). Cryospheric Geomorphology. Elsevier, pp. 249-280. (link)
What is cosmogenic nuclide dating?
Cosmogenic nuclide dating has been widely applied worldwide over the last 20 years (Balco, 2011). It relies on the accumulation of cosmogenic nuclides in materials on the Earth’s surface. As cosmic rays have a short attenuation length, and cannot pass through substantial thicknesses of rock, water, ice and sediment, glacially transported rocks and ice-scoured bedrock are shielded from cosmic rays until they are exposed by recession of ice to the atmosphere at the Earth’s surface.
Upon deposition and recession of the ice, cosmogenic isotopes begin to accumulate in the upper faces of minerals in rocks. These can be measured, and if the production rate is known, the ‘exposure age’ can be calculated. If the rock is then buried, the divergence between two isotopes with different half-lives (commonly 10Be and 26Al) allows a ‘burial age’ to be determined.
The six key isotopes
There are six key isotopes that are useful for cosmogenic nuclide dating in the Earth’s surface (10Be, 26Al, 3He, 21Ne, 36Cl, 14C). 10Be is applied most commonly for exposure-age and burial dating of glacial landforms. These isotopes allow exposure or burial age dating over a range of timescales, from hundreds to several million years.
Length of time applicable
In practice, the key limiting factor on using exposure age dating on glacial landforms is the tendency for landforms such as moraines to degrade and rocks to weather away over time, producing scatted ages (Heyman et al., 2011; Ivy-Ochs and Briner, 2014). This means that over longer timescales dating back past the Mid-Pleistocene in exposed locations, exposure-age dating is less applicable than cosmogenic burial dating.
The principals, methods and numerical theories and equations for cosmogenic nuclide dating have been thoroughly reviewed elsewhere (Balco, 2011; Cockburn and Summerfield, 2004; Darvill, 2013; Dunai and Lifton, 2014; Gosse and Phillips, 2001; Granger et al., 2013; Heyman et al., 2016; Ivy-Ochs and Briner, 2014; Ivy-Ochs and Kober, 2007; Jones et al., 2019). The key principles and applications are summarized briefly here, and then sampling methodologies and data analysis protocols are discussed.