1. What do glacial moraine chronologies really tell us about climate? Martin P. Kirkbride Geography School of the Environment School of the Environment University of Dundee Dundee DD1 4HN Scotland UK. European Geophysical Union General Assembly 2011 Session GM9.1/9.2

2. 1. Introduction: moraine dating, and the principles of correlation Principles of correlation physical similarity (classic stratigraphic correlation) texture, structure, provenance, fossil assemblage spatial continuity tephra layers, Heinrich layers etc. statistical matching measures of central tendency and dispersion Moraine are physically similar and lack spatial continuity, so we depend on statistical properties of proxy age samples

3. Five steps to linking climate records and moraines Climate variations (various amplitudes, frequencies, and phenomena)  Glacier responses (variable reaction and response times re. glacier size and form)  Moraine deposition (variable debris supply)  Erosion censoring  Moraine dating  Correlation (local, regional. interhemispheric scales, “lumping/splitting” decisions)

4. Climate variations (various amplitudes, frequencies, and phenomena)  Glacier responses (variable reaction and response times re. glacier size and form)  Moraine deposition (variable debris supply)  Erosion censoring  Moraine dating  Correlation (local, regional. interhemispheric scales, “lumping/splitting” decisions) Five steps to linking climate records and moraines

5. Timescales of glacier reaction and response Cirque glacier = annual variation Potentially 6 moraines Small valley glacier = decadal variation Potentially 3 moraines Compound valley glacier = century scale variation 0 moraines Different glaciers respond to different frequencies of climatic fluctuation Larger glaciers filter and smooth complex high-frequency fluctuations (Haeberli and Hoelzle)

6. 2. Relations between spatial correlation and temporal resolution How do different ranges of uncertainty in dating affect out ability to correlate distant moraine sequences? Mt Cook, NZ: Schaefer et al (2009) Science Uncertainty is c. 20% of individual 10 Be age (ie. ± 10%)

7. Chronological resolution (uncertainty) and correlation Our ability to correlate depends on the range of uncertainty (“error bars”) of the dated moraines. “Error”CorrelationInterpretation ± 500M1 = M2  M3 1 glacier advance “event” ± 250M1 = M2  M3 2 glacier advance “events” ± 75M1  M2  M3 3 glacier advance “events”

8. “Lumping” is the tendency to correlate across wide areas because the temporal resolution of individual chronologies is too coarse to distinguish separate events “Splitting” is the tendency to distinguish between closely-spaced events which are dated to high resolution. The “Lumping/Splitting” Rule: The spatial resolution of correlation is in inverse relation to the temporal resolution of the component chronologies.

9. The “Lumping/Splitting” Rule: The spatial resolution of correlation is in inverse relation to the temporal resolution of the component chronologies. “Lumped” chronologies may be appropriate for interhemispheric correlation where millenial- scale glacial fluctuations (eg LIA) are due to global climate changes. “Split” chronologies may be appropriate for local to regional correlation where decadal scale glacial fluctuations (eg LIA maximum) are due to regional atmospheric circulation changes.

10. Response scale, chronological resolution, and correlation error Type I error False rejection of null hypothesis False correlation of different climatic events. Null hypothesis: “there is no temporal or climatic association between moraines in different places” Type II error False acceptance of null hypothesis False differentiation of the same climatic event.

11. Kaplan et al. (2010) Nature Kaplan et al (2010) Nature 467 Response scale, chronological resolution, and correlation error Ages spread over 2,500 years produce a statistical uncertainty of only 100 years (weighted mean). Which is the most realistic estimate of uncertainty? This affects our ability to correlate with confidence and risks errors of false differentiation. Risk of a Type 2 error = false acceptance of null hypothesis: more likely if chronologies are unrealistically resolved.

12. Kirkbride & Brazier (1998) Quaternary Proceedings. Age structure of moraine sequences Age-difference curves : Graphs of moraine age against age-difference from next youngest moraine. An increase in age difference with age is common – but is it due to:  Shift in recorded climate signal?  Loss of evidence?  “Correlation shift”? Age difference Age 3. Completeness of the moraine record: erosion censoring How do we know how complete our moraine records are?

13. Kirkbride & Brazier (1998 ) Quaternary Proceedings 6 Climate varies with frequencies of 2000, 200 and 20 years. Age-difference line shows both the climate frequency recorded by the moraine field, and the degree of erosion censoring. Erosion censoring of moraine assemblages

14. Little Ice Age chronologies Mt Cook: Schaefer et al (2009) Blåbreen: Bickerton & Matthews (1992) If the age differences between moraines increase with age, older deposits may have been censored by erosion or aggradation. Mt Cook: possible erosion censoring Blåbreen: no erosion censoring

15. Erosion censoring of moraine assemblages Holocene chronologies Decreasing quality of proxy evidence Iceland (Kirkbride & Dugmore 2008 Quatern. Res.)

16. 4. Conclusions and recommendations. 1. We require a theoretical and practical basis for correlation. We have no systematic criteria at the moment. 2. Correlation decisions need to be informed by chronological resolution, timescale of glacier response, and presumed frequency of climatic variability. 3.We need better integration of modelling of glacier sensitivity into chronological investigations. 4. We need some way of assessing the completeness of moraine records as part of correlation attempts. Thank you