# Last Millennium Reanalysis (LMR) Project Global Climate Reconstructions Version 2 #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # Template Version 3.0 # Encoding: UTF-8 # NOTE: Please cite original publication, online resource and date accessed when using this data. # If there is no publication information, please cite Investigator, title, online resource and date accessed. # # Description/Documentation lines begin with # # Data lines have no # # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/27850 # Description: NOAA Landing Page # Online_Resource: http://www1.ncdc.noaa.gov/pub/data/paleo/reconstructions/tardif2019lmr/tardif2019_lmr.txt # Description: NOAA location of the template # # Data_Type: Climate Reconstructions # # Dataset_DOI: # # Parameter_Keywords: air temperature, sea surface temperature, precipitation, atmospheric circulation #--------------------------------------- # Contribution_Date # Date: 2019-10-07 #--------------------------------------- # File_Last_Modified_Date # Date: 2019-10-07 #--------------------------------------- # Title # Study_Name: Last Millennium Reanalysis (LMR) Project Global Climate Reconstructions Version 2 #--------------------------------------- # Investigators # Investigators: Tardif, R.; Hakim, G.J.; Perkins, W.A.; Horlick, K.A.; Erb, M.P.; Emile-Geay, J.; Anderson, D.M.; Steig, E.J.; Noone, D. #--------------------------------------- # Description_Notes_and_Keywords # Description: The data provided are for the LMR version 2 reconstructions in netcdf format. Data from two versions are provided, both described in Tardif et al. (2019). # Common aspects are: # CCSM4 Last Millennium simulation as the source of prior, with states from 100 randomly drawn years as the prior ensemble in each Monte-Carlo realization # Regression-based Proxy System Models, formulated using the seasonal responses of individual records, with bivariate models w.r.t. temperature and precipitation for tree-ring width proxies, and univariate w.r.t. temperature for all other proxy archives. # Covariance localization applied with a cut-off length scale of 25000 km # Reconstructions generated at an annual resolution, on a 2ox2o grid. # Differences are related to the set of assimilated proxies: # LMR v2.1: Proxies from the PAGES2k (2017) data set*. Corresponds to results presented in Tardif et al. (2019), section 3, figures 2-5. # LMR v2.0: Proxies from PAGES2k (2017) + Anderson et al. (2019) [see figure 8 from Tardif et al. (2019)]. Reconstruction results are discussed in Tardif et al. (2019), section 4.3, and shown in figures 9-10, (e) and (f), and in figure 11. # * with the exception of the Palmyra coral record: we used the more recent version from Emile-Geay et al (2013), instead of the version from Cobb et al. (2003) as in PAGES2k (2017); and the Kiritimati coral record: the longer record from the Anderson et al (2019) dataset, taken from Cobb et al (2013), replaces a slightly shorter record included in PAGES2k (2017). # # Data Notes # File and variable naming conventions follow as closely as possible those for the NOAA 20th Century Reanalysis. # Gridded fields have the format: (time, MCrun, lat, lon) where time is the year, lat is the latitude index, lon is the longitude index, and MCrun indicate the Monte Carlo iteration index. There are in fact 20 LMR reconstructions contained in these arrays. They differ in the climate model ensemble prior to assimilation (random draws from the CCSM4 Last Millennium simulation) and the proxies that were drawn randomly for the reconstruction (75% of all available proxies). You probably want to start with the "grand mean," which is an average over the MCrun dimension. NOTE: the variance on the MCrun index does NOT represent the uncertainty (error) in the reconstructions! It only represents the piece from the prior and proxies. The major portion of the error is in the full ensemble, which is summarized by the spread field for each iteration. # All fields are anomalies from the 1951-1980 time-mean. # # netCDF Filelist # # Global and hemispheric-mean two-meter air temperature [format: (time, MCrun, members); this has all ensemble members]: # global-mean temperature # v2.0: gmt_MCruns_ensemble_full_LMRv2.0.nc; v2.1: gmt_MCruns_ensemble_full_LMRv2.1.nc # NH-mean temperature # v2.0: nhmt_MCruns_ensemble_full_LMRv2.0.nc ; v2.1: nhmt_MCruns_ensemble_full_LMRv2.1.nc # SH-mean temperature: # v2.0: shmt_MCruns_ensemble_full_LMRv2.0.nc ; v2.1: shmt_MCruns_ensemble_full_LMRv2.1.nc # # Two-meter air temperature: # full grid ensemble mean # v2.0: air_MCruns_ensemble_mean_LMRv2.0.nc ; v2.1: air_MCruns_ensemble_mean_LMRv2.1.nc # full grid ensemble spread # v2.0: air_MCruns_ensemble_spread_LMRv2.0.nc ; v2.1: air_MCruns_ensemble_spread_LMRv2.1.nc # # Sea-surface temperature: # full grid ensemble mean # v2.0: sst_MCruns_ensemble_mean_LMRv2.0.nc ; v2.1: sst_MCruns_ensemble_mean_LMRv2.1.nc # full grid ensemble spread # v2.0: sst_MCruns_ensemble_spread_LMRv2.0.nc ; v2.1: sst_MCruns_ensemble_spread_LMRv2.1.nc # # 500 hPa geopotential height: # full grid ensemble mean # v2.0: hgt500_MCruns_ensemble_mean_LMRv2.0.nc ; v2.1: hgt500_MCruns_ensemble_mean_LMRv2.1.nc # full grid ensemble spread # v2.0: hgt500_MCruns_ensemble_spread_LMRv2.0.nc ; v2.1: hgt500_MCruns_ensemble_spread_LMRv2.1.nc # # Mean-sea-level pressure: # full grid ensemble mean # v2.0: prmsl_MCruns_ensemble_mean_LMRv2.0.nc ; v2.1: prmsl_MCruns_ensemble_mean_LMRv2.1.nc # full grid ensemble spread # v2.0: prmsl_MCruns_ensemble_spread_LMRv2.0.nc ; v2.1: prmsl_MCruns_ensemble_spread_LMRv2.1.nc # # Precipitation: # full grid ensemble mean # v2.0: prate_MCruns_ensemble_mean_LMRv2.0.nc ; v2.1: prate_MCruns_ensemble_mean_LMRv2.1.nc # full grid ensemble spread # v2.0: prate_MCruns_ensemble_spread_LMRv2.0.nc ; v2.1: prate_MCruns_ensemble_spread_LMRv2.1.nc # # Precipitable water: # full grid ensemble mean # v2.0: pr_wtr_MCruns_ensemble_mean_LMRv2.0.nc ; v2.1: pr_wtr_MCruns_ensemble_mean_LMRv2.1.nc # full grid ensemble spread # v2.0: pr_wtr_MCruns_ensemble_spread_LMRv2.0.nc ; v2.1: pr_wtr_MCruns_ensemble_spread_LMRv2.1.nc # # Palmer drought severity index (PDSI): # full grid ensemble mean # v2.0: pdsi_MCruns_ensemble_mean_LMRv2.0.nc ; v2.1: pdsi_MCruns_ensemble_mean_LMRv2.1.nc # full grid ensemble spread # v2.0: pdsi_MCruns_ensemble_spread_LMRv2.0.nc ; v2.1: pdsi_MCruns_ensemble_spread_LMRv2.1.nc # # Climate indices (Nino3.4, PDO, AMO etc.) [format: (time, MCrun, members); this has all ensemble members]: # climate indices # v2.0: posterior_climate_indices_MCruns_ensemble_full_LMRv2.0.nc ; v2.1: posterior_climate_indices_MCruns_ensemble_full_LMRv2.1.nc # #--------------------------------------- # Publication # Authors: Tardif, R., G.J. Hakim, W.A. Perkins, K.A. Horlick, M.P. Erb, J. Emile-Geay, D.M. Anderson, E.J. Steig, and D. Noone # Published_Date_or_Year: 2019 # Published_Title: Last Millennium Reanalysis with an expanded proxy database and seasonal proxy modeling # Journal_Name: Climate of the Past # Volume: 15 # Edition: # Issue: # Pages: 1251-1273 # Report_Number: # DOI: 10.5194/cp-15-1251-2019 # Online_Resource: # Full_Citation: # Abstract: The Last Millennium Reanalysis (LMR) utilizes an ensemble methodology to assimilate paleoclimate data for the production of annually resolved climate field reconstructions of the Common Era. Two key elements are the focus of this work: the set of assimilated proxy records and the forward models that map climate variables to proxy measurements. Results based on an updated proxy database and seasonal regression-based forward models are compared to the LMR prototype, which was based on a smaller set of proxy records and simpler proxy models formulated as univariate linear regressions against annual temperature. Validation against various instrumental-era gridded analyses shows that the new reconstructions of surface air temperature and 500?hPa geopotential height are significantly improved (from 10% to more than 100%), while improvements in reconstruction of the Palmer Drought Severity Index are more modest. Additional experiments designed to isolate the sources of improvement reveal the importance of the updated proxy records, including coral records for improving tropical reconstructions, and tree-ring density records for temperature reconstructions, particularly in high northern latitudes. Proxy forward models that account for seasonal responses, and dependence on both temperature and moisture for tree-ring width, also contribute to improvements in reconstructed thermodynamic and hydroclimate variables in midlatitudes. The variability of temperature at multidecadal to centennial scales is also shown to be sensitive to the set of assimilated proxies, especially to the inclusion of primarily moisture-sensitive tree-ring-width records. #--------------------------------------- # Publication # Authors: Anderson, D.M., R. Tardif, K. Horlick, M.P. Erb, G.J. Hakim, D. Noone, W.A. Perkins, E.J. Steig # Published_Date_or_Year: 2019 # Published_Title: Additions to the Last Millennium Reanalysis multi-proxy database # Journal_Name: Data Science Journal # Volume: 18 # Edition: # Issue: 1 # Pages: # Report_Number: # DOI: 10.5334/dsj-2019-002 # Online_Resource: # Full_Citation: # Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR). The 2290 additional series include 2152 tree ring chronologies and 138 other series. They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation. A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project. The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables. Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods. #--------------------------------------- # Publication # Authors: Hakim, G.J., J. Emile-Geay, E.J. Steig, D. Noone, D.M. Anderson, R. Tardif, N.J. Steiger, and W.A. Perkins # Published_Date_or_Year: 2016 # Published_Title: The Last Millennium Climate Reanalysis Project: Framework and first results # Journal_Name: Journal of Geophysical Research: Atmospheres # Volume: 121 # Edition: # Issue: # Pages: 6745-6764 # Report_Number: # DOI: 10.1002/2016JD024751 # Online_Resource: # Full_Citation: # Abstract: 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. #--------------------------------------- # Funding_Agency # Funding_Agency_Name: # Grant: #--------------------------------------- # Site_Information # Site_Name: Global # Location: # Country: # Northernmost_Latitude: 90 # Southernmost_Latitude: -90 # Easternmost_Longitude: 180 # Westernmost_Longitude: -180 # Elevation: #--------------------------------------- # Data_Collection # Collection_Name: LMR Reconstructions 2019 # First_Year: 0 # Last_Year: 2000 # Time_Unit: AD # Core_Length: # Notes: #--------------------------------------- # Chronology_Information # Chronology: #--------------------------------------- # Variables # Data variables follow that are preceded by "##" in columns one and two. # Variables list, one per line, shortname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) ## time age,,,year Common Era,,climate reconstructions,,,N, ## air air temperature,,,kelvin,,climate reconstructions,,,N,2m air temperature ## sst sea surface temperature,,,kelvin,,climate reconstructions,,,N, ## hgt500 geopotential height,,,meter,,climate reconstructions,,,N,500 hPa height ## prmsl sea level pressure,,,pascal,,climate reconstructions,,,N, ## prate precipitation,,,kilogram per square meter per second,,climate reconstructions,,,N,precipitation rate at surface ## pr_wtr precipitation,,,kilogram per square meter,,climate reconstructions,,,N,precipitable water ## pdo Pacific Decadal Oscillation Index,,,dimensionless,,climate reconstructions,,,N, ## amo Atlantic Multidecadal Oscillation Index,,,dimensionless,,climate reconstructions,,,N, ## nino34 El Nino Southern Oscillation Index,,,dimensionless,,climate reconstructions,,,N,Nino3.4 Index ## ao Arctic Oscillation Index,,,dimensionless,,climate reconstructions,,,N, ## nao North Atlantic Oscillation Index,,,dimensionless,,climate reconstructions,,,N, ## soi Southern Oscillation Index,,,dimensionless,,climate reconstructions,,,N, ## sam Southern Annular Mode,,,dimensionless,,climate reconstructions,,,N,Southern Annular Mode Index #------------------------ # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing_Values: NA All data is in netCDF files organized by variable type version 2.0 data is in https://www1.ncdc.noaa.gov/pub/data/paleo/reconstructions/tardif2019lmr/v2_0 NA NA NA NA NA NA NA NA NA NA NA NA NA NA version 2.1 data is in https://www1.ncdc.noaa.gov/pub/data/paleo/reconstructions/tardif2019lmr/v2_1 NA NA NA NA NA NA NA NA NA NA NA NA NA NA