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

• Main Authors: Parsons, Hakim
• Format: Dataset
• Language: English
• Published: 2019
• Subjects: paleoclimate; data assimilation; cmip5; last millennium; Pacific; North Atlantic
• Online Access: https://zenodo.org/record/5636999; https://doi.org/10.5281/zenodo.5636999

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. 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 ...