Published August 30, 2019 | Version v1.0
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Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models'

  • 1. Luke
  • 2. Greg

Description

Abstract from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models':

Despite the importance of interdecadal climate variability, we have a limited understanding of which geographic regions are associated with global temperature variability at these timescales. The instrumental record tends to be too short to develop sample statistics to study interdecadal climate variability, and Coupled Model Intercomparison Project, Phase 5 (CMIP5) climate models tend to disagree about which locations most strongly influence global mean interdecadal temperature variability. Here we use a new paleoclimate data assimilation product, the Last Millennium Reanalysis (LMR), to examine where local variability is associated with global mean temperature variability at interdecadal timescales. The LMR framework uses an ensemble Kalman filter data assimilation approach to combine the latest paleoclimate data and state-of-the-art model data to generate annually resolved field reconstructions of surface temperature, which allow us to explore the timing and dynamics of preinstrumental climate variability in new ways. The LMR consistently shows that the middle- to high-latitude north Pacific and the high-latitude North Atlantic tend to lead global temperature variability on interdecadal timescales. These findings have important implications for understanding the dynamics of low-frequency climate variability in the preindustrial era.

Notes

Surface air temperature output, saved as netcdf files, from paleoclimate data assimilation experiments run using the Last Millennium Reanalysis for Parsons and Hakim, 2019, JGRA (10.1029/2019JD030426). All files starting with 'air_MCruns_ensemble_mean_' include the 11-Monte Carlo iteration (100 ensemble members each) mean of the air temperature reconstructions, each using a different CMIP5 past1000 model prior in the data assimilation procedure (CMIP5 past1000 data can be downloaded from: https://esgf-node.llnl.gov/search/cmip5/). Here annual mean surface air temperature for years 850-2000 Common Era (CE) are saved as part of the experiments for the main text. Further details can be found in Parsons and Hakim, 2019 JGRA (10.1029/2019JD030426). Files starting with the name 'SUPPLEMENT' were output as part of the sensitivity testing when conducting the analysis for the manuscript. Results from these sensitivity tests are reported in Figure S4 (all used the CCSM4 past1000 prior) and include (note some file names indicate the output was saved for the 1500-2000 CE time period only) the following changes in experimental setup: setup using 1 MC iteration (0% LMRdbv1 proxies withheld in 1 MC iteration); setup using only the PAGES2k Phase 2 proxy records (25% proxies withheld in each of 11 MC iterations); setup excluding all tree ring records on every continent (25% LMRdbv1 proxies withheld in each of 11 MC iterations); setup excluding tree ring records on the North American continent (0% LMRdbv1 proxies withheld in 1 MC iteration); setup using 50% proxies (50% LMRdbv1 proxies withheld in each of 11 MC iterations); setup using 25% proxies (75% LMRdbv1 proxies withheld in each of 11 MC iterations); setup using a fixed proxy network limited to proxies that span the 850-2000CE time period (25% proxies LMRdbv1 proxies withheld in each of 11 MC iterations); setup using a fixed proxy network limited to proxies that span the 1500-1850CE time period (25% LMRdbv1 proxies withheld in each of 11 MC iterations); setup using a limited, fixed proxy network that only had data coverage that spanned 1500-1850CE time period (50% LMRdbv1 proxies withheld in each of 11 MC iterations).

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Additional details

Related works

Is compiled by
Journal article: 10.1029/2019JD030426 (DOI)

References

  • 10.1029/2019JD030426
  • 10.1002/2016JD024751
  • 10.5194/cp-15-1251-2019