An “offline” approach to DA is used, where static ensemble samples are drawn from existing CMIP climate-model simulations to serve as the prior estimate of climate variables. We use linear, univariate forward models (“proxy system models (PSMs)") that map climate variables to proxy measurements by fitting proxy data to 2 m air temperature from gridded instrumental temperature data; the linear PSMs are then used to predict proxy values from the prior estimate. Results for the LMR are compared against six gridded instrumental temperature data sets and 25% of the proxy records are withheld from assimilation for independent verification. Results show broad agreement with previous reconstructions of Northern Hemisphere mean 2 m air temperature, with millennial-scale cooling, a multicentennial warm period around 1000 C.E., and a cold period coincident with the Little Ice Age (circa 1450-1800 C.E.). Verification against gridded instrumental data sets during 1880-2000 C.E. reveals greatest skill in the tropics and lowest skill over Northern Hemisphere land areas. Verification against independent proxy records indicates substantial improvement relative to the model (prior) data without proxy assimilation. As an illustrative example, we present multivariate reconstructed fields for a singular event, the 1808/1809 “mystery” volcanic eruption, which reveal global cooling that is strongly enhanced locally due to the presence of the Pacific-North America wave pattern in the 500 hPa geopotential height field.
Bibliographical noteFunding Information:
This research was supported by grants from the National Science Foundation (grant AGS-1304263 to the University of Washington) and the National Oceanic and Atmospheric Administration (grant NA14OAR4310176). Climate simulations were generated as part of the Paleoclimate Model Intercomparison (PMIP3) project. We acknowledge the World Climate Research Programme's Working Group on Coupled Modelling, which is responsible for CMIP. For CMIP the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. CMIP data used in this paper may be obtained from the Earth System Grid Federation at http://esgf.llnl.gov/. Access to data and software related to research in this paper are published at the doi: 10.17911/S9WC7N. Comments and suggestions from two anonymous referees were helpful in revision and are gratefully acknowledged. We also thank the LMR advisory panel, Kim Cobb, Kevin Anchukaitis, Gil Compo, Michael N. Evans, and Thorsten Kiefer, for their guidance and suggestions.
© 2016. The Authors.