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

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...

Full description

Bibliographic Details
Main Authors: , Parsons, , Hakim
Format: Dataset
Language:English
Published: Zenodo 2019
Subjects:
Online Access:https://dx.doi.org/10.5281/zenodo.5636999
https://zenodo.org/record/5636999
id ftdatacite:10.5281/zenodo.5636999
record_format openpolar
institution Open Polar
collection DataCite Metadata Store (German National Library of Science and Technology)
op_collection_id ftdatacite
language English
topic paleoclimate, data assimilation, cmip5, last millennium
spellingShingle paleoclimate, data assimilation, cmip5, last millennium
, Parsons
, Hakim
Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models'
topic_facet paleoclimate, data assimilation, cmip5, last millennium
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. : 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). : {"references": ["10.1029/2019JD030426", "10.1002/2016JD024751", "10.5194/cp-15-1251-2019"]}
format Dataset
author , Parsons
, Hakim
author_facet , Parsons
, Hakim
author_sort , Parsons
title Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models'
title_short Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models'
title_full Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models'
title_fullStr Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models'
title_full_unstemmed Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models'
title_sort data from 'local regions associated with interdecadal global temperature variability in the last millennium reanalysis and cmip5 models'
publisher Zenodo
publishDate 2019
url https://dx.doi.org/10.5281/zenodo.5636999
https://zenodo.org/record/5636999
geographic Pacific
geographic_facet Pacific
genre North Atlantic
genre_facet North Atlantic
op_relation https://dx.doi.org/10.1029/2019jd030426
https://dx.doi.org/10.5281/zenodo.5636998
op_rights Open Access
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
cc-by-4.0
info:eu-repo/semantics/openAccess
op_rightsnorm CC-BY
op_doi https://doi.org/10.5281/zenodo.5636999
https://doi.org/10.1029/2019jd030426
https://doi.org/10.5281/zenodo.5636998
_version_ 1766137354367533056
spelling ftdatacite:10.5281/zenodo.5636999 2023-05-15T17:37:25+02:00 Data from 'Local Regions Associated With Interdecadal Global Temperature Variability in the Last Millennium Reanalysis and CMIP5 Models' , Parsons , Hakim 2019 https://dx.doi.org/10.5281/zenodo.5636999 https://zenodo.org/record/5636999 en eng Zenodo https://dx.doi.org/10.1029/2019jd030426 https://dx.doi.org/10.5281/zenodo.5636998 Open Access Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 info:eu-repo/semantics/openAccess CC-BY paleoclimate, data assimilation, cmip5, last millennium dataset Dataset 2019 ftdatacite https://doi.org/10.5281/zenodo.5636999 https://doi.org/10.1029/2019jd030426 https://doi.org/10.5281/zenodo.5636998 2022-02-08T12:23:07Z 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 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). : {"references": ["10.1029/2019JD030426", "10.1002/2016JD024751", "10.5194/cp-15-1251-2019"]} Dataset North Atlantic DataCite Metadata Store (German National Library of Science and Technology) Pacific