Reply on CC1

James Annan

doi:10.5194/cp-2022-12-ac1

Abstract

We present a new reconstruction of surface air temperature and sea surface temperature for the Last Glacial Maximum. The method blends model fields and sparse proxy-based point estimates through a data assimilation approach. Our reconstruction updates that of Annan and Hargreaves (2013), using improved models, data and methodology and our reconstruction has a global annual mean surface air temperature anomaly of −4.5 ± 0.9 °C relative to the pre-industrial climate. This is slightly colder than our previous estimate, with an upwards revision on its uncertainty due to methodological assumptions. It is, however, substantially less cold than the recent reconstruction of Tierney et al. (2020). We discuss the reasons for this discrepancy.

Highlights

There is a significant demand for reconstructions of the large spatial patterns of paleoclimatic states, in order to understand 10 past climate changes and how these may relate to expected future changes
We use the diverse ensemble of model simulations of past climate states which were generated by the GCMs which participated in various community model intercomparison projects, together with comprehensive data sets over land and ocean, in order to generate spatially complete and physically coherent maps of surface air temperature (SAT) and sea surface temperature (SST) for both periods
Our new method is less susceptible to sampling noise in the model climatologies and the result is noticeably smoother than our previous analysis

Summary

Introduction

There is a significant demand for reconstructions of the large spatial patterns of paleoclimatic states, in order to understand 10 past climate changes and how these may relate to expected future changes. Estimating these states is far from trivial, as climate proxy data are very limited in time and space, and contain substantial uncertainties and potentially systematic biases. We use the diverse ensemble of model simulations of past climate states which were generated by the GCMs which participated in various community model intercomparison projects, together with comprehensive data sets over land and ocean, in order to generate spatially complete and physically coherent maps of surface air temperature (SAT) and sea surface temperature (SST) for both periods. Our approach has some 20 similarities to the methods of Annan and Hargreaves (2013) and Tierney et al (2020) but differs in several important ways and the resulting LGM reconstruction is substantially different from both of these previous analyses

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Conclusion