A new global climate reconstruction for the mid-Pliocene Warm Period.

We present a new reconstruction of global climatological temperature fields for the mid-Pliocene Warm Period.

The method combines globally complete modelled temperature fields, with sparse proxy-based estimates of local temperature anomalies. We use the full set of PlioMIP and PlioMIP2 model simulations, and the proxy-based SST estimates of of Haywood et al 2020 (time slice at MIS KM5c, 3.2Ma) to ensure the best possible global coverage. 

We perform some initial filtering of the model simulations to remove duplicates and closely related models. We then de-bias the ensemble (relative to the proxy data) and show via sensitivity tests that this can be an essential step in the process. Specifically, any bias in the prior ensemble leads to a significant bias (which may take roughly 70-80% of its initial magnitude) in the posterior estimate. Thus we recommend that this step is taken in similar reconstructions unless the researcher is confident that the bias in the prior ensemble is low relative to likely bias in interpretation of proxy data.

The assimilation method is a localised Ensemble Kalman Filter, which ensures spatially coherent fields that both respect the physical principles embodied in the models, and are also tied closely to observational estimates. This method takes the processed ensemble of models to represent our prior uncertainty, and updates it with observational estimates arising from the proxy data. Thus, in areas where proxy data are sparse and/or highly uncertain, our result is still described by the spread of model results. However, accurate proxy data can improve the estimate over a local region. Our reconstruction has a global mean surface air temperature anomaly of + 4.7 +- 1C relative to the pre-industrial climate.