Abstract
Paleoclimate proxy data are playing an increasingly central role in contemporary climate science. First, proxy data about key paleoclimates in Earth’s history can be used to benchmark the performance of state-of-the-art climate models by providing crucial “out of sample” tests. Paleoclimates provide data about the response of the Earth to climate states and forcing scenarios that are very different from those provided by the limited historical (i.e., instrument) record (which has hitherto provided the basis for building, tuning, and testing current climate models). These tests, which have most recently been undertaken by the Paleoclimate Model Intercomparison Project 4 (PMIP4) in coordination with CMIP6, will be increasingly important for developing climate models that can reliably forecast a future where anthropogenic forcing has perturbed the Earth out of the climate state represented by the historical record (Kageyama et al. 2018). Second, paleoclimate proxy data can also be used more directly to provide an estimate for quantities such as equilibrium climate sensitivity (ECS). Although ECS used to be estimated on the basis of the values provided by climate models, since the fourth assessment report (AR4) both paleoclimate proxy data and (instrument) data from historical warming have provided additional observational constraints on ECS values. In the most recent AR6, which was published last year, model-based estimates of ECS from the CMIP6 models were for the first time excluded from the evidential base for estimating climate sensitivity. Instead, the current official estimate for ECS was derived only on the basis of the following three independent lines of evidence: process understanding about feedbacks, the historical climate record, and the paleoclimate record (Sherwood et al. 2020; IPCC AR6, Chapter 7). Given their increasing importance for climate research, paleoclimate proxy data are ripe for philosophical analysis. Despite their role as data for testing climate models and as observational evidence for a value of climate sensitivity, it must be emphasized that paleoclimate data are themselves a complex, model-laden data product, involving many layers of data processing, data conversion, and data correction (Bokulich 2020). Hence, there are many sources of uncertainty in paleoclimate data that arise along the path from local proxy measurements of traces left in geologic record to global paleoclimate reconstructions of Earth’s deep past. To realize their potential, questions about how to validate paleoclimate data must be confronted. In this talk I develop a multi-procedure framework for validating (or evaluating) proxy data, analogous to the frameworks used for model evaluation. I further argue that paleoclimate data must be evaluated as adequate or inadequate for particular purposes (Bokulich and Parker 2021). Finally, I highlight the importance of data pluralism in the form of multiple data ensembles derived from different possible ways of processing the data. Although developed in the context of paleoclimate proxy data, the data-validation framework I provide here can be generalized to apply to data evaluation in other scientific contexts.
