Depth and seasonal biases in organic temperature proxies: a modelling study

For more than a decade TEX₈₆ and U^K’₃₇, derived from ratios of biomarker lipids have widely been used as organic paleotemperature proxies. Yet, these proxies, especially TEX₈₆, have several uncertainties associated with factors such as depth and seasonal biases which are complicating its application as an annual mean sea-surface temperature (SST) proxy. To constrain this impact, we performed a relatively simple modelling exercise where we use instrumental temperature and nutrient data from 40 locations across the globe to predict theoretical proxy values and compare them with measured core-top proxy values.

The model first uses instrumental nutrient and temperature data, and probability density functions to predict the theoretical depth occurrence of the source organisms of the two proxies. Additionally, seasonal bias was introduced by predicting seasonal occurrences using instrumental nutrient and chlorophyll data. This was used to calculate the depth- and season weighed temperature signal annually deposited in the sediment, which in turn was converted to theoretical proxy values using culture or mesocosm calibrations. This showed, as expected, that depth and seasonal biases introduced scatter in the correlation between theoretical proxy values and annual mean SST but still highly significant for both U^K’₃₇ (r²= 0.96), and TEX₈₆ (r²= 0.77). We find that the theoretical proxy values are much lower than measured proxy value for TEX₈₆, which tentatively suggests that TEX₈₆ might in fact be coming from shallower depths or that the mesocosm calibration is incorrect. Our model for U^K’₃₇ results in theoretical values similar to measured values except for low temperature locations. This might suggest an influence of seasonal bias towards more warmer summer seasons which is more pronounced in high latitudes than in tropics.