# Global 2,000 Year Paleo Hydrodynamics Data Assimilation (PHYDA) Product #----------------------------------------------------------------------- # World Data Service for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program # National Centers for Environmental Information (NCEI) #----------------------------------------------------------------------- # Template Version 3.0 # Encoding: UTF-8 # NOTE: Please cite Publication, and Online_Resource and date accessed when using these data. # If there is no publication information, please cite Investigators, Title, and Online_Resource and date accessed. # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24230 # Description: NOAA Landing Page # Online_Resource: https://www1.ncdc.noaa.gov/pub/data/paleo/reconstructions/steiger2018/readme-steiger2018.txt # Description: NOAA location of the template # # Original_Source_URL: # Description: # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstructions # # Dataset DOI: # # Parameter_Keywords: air temperature, precipitation, atmospheric circulation #-------------------- # Contribution_Date # Date: 2018-05-25 #-------------------- # File_Last_Modified_Date # Date: 2018-05-25 #-------------------- # Title # Study_Name: Global 2,000 Year Paleo Hydrodynamics Data Assimilation (PHYDA) Product #-------------------- # Investigators # Investigators: Steiger, N.J.; Smerdon, J.E.; Cook, E.R.; Cook, B.I. #-------------------- # Description_Notes_and_Keywords # Description: Paleohydrodynamic proxy data set and global hydroclimate reconstructions for the past 2,000 years. # Included are reconstructions of three global variables gridded at ~2 degree resolution: surface temperature at 2m, # the Palmer drought severity index (PDSI), and the standardized precipitation evapotranspiration index (SPEI). # Also reconstructed are climate indices at annual, JJA, and DJF temporal resolutions: # the global mean temperature, the North Atlantic sea surface temperature index (which is the non-detrended and # non-smoothed version of the Atlantic multidecadal oscillation index (AMO), and the location of the intertropical # convergence zone (ITCZ) in 11 longitudinal zones. Also reconstructed are the monthly Nino sea surface temperature # (SST) indices (Nino 1+2, 3, 3.4, 4) and the monthly equatorial Pacific zonal SST gradient. # # The reconstructions are stored in three (4.1 GB) NetCDF4 data files. # Filenames and md5 checksums are as follows: # da_hydro_AprMar_r.1-2000_d.05-Jan-2018.nc md5:bc6f42f7f0cd444f43e1e41d351093e5 # da_hydro_DecFeb_r.1-2000_d.05-Jan-2018.nc md5:ba4a5b6821d0385de5fcf2e0c357013f # da_hydro_JunAug_r.1-2000_d.05-Jan-2018.nc md5:69f9acaf54208273ca74632c2325b8bb # # This database provides the first truly global reconstructions of hydroclimate along with associated climate # dynamical variables over the past two thousand years. The reconstructions were made with an improved data # assimilation reconstruction approach that optimally combines 2,978 paleoclimate proxy-data time series with # the physical constraints of an atmosphere-ocean climate model. Three separate global reconstructions were # created from the years 1 to 2000 CE, targeting annual means (defined as April to the next calendar year March), # the boreal growing season of June, July, and August (JJA), and the austral growing season of December, # January, and February (DJF); each of these reconstructions is contained in a separate NetCDF file. # The reconstructions include three global variables gridded at about 2 degree resolution: # surface temperature at 2 m, the Palmer drought severity index (PDSI), and the standardized precipitation # evapotranspiration index (SPEI). Dynamical variables also included for each reconstruction: the global mean # temperature, the North Atlantic sea surface temperature index which is the non-detrended and non-smoothed # version of the Atlantic multidecadal oscillation (AMO), the monthly Nino SST indices (Nino 1+2, 3, 3.4, 4), # the monthly equatorial Pacific zonal SST gradient, and the location of the intertropical convergence zone (ITCZ) # in 11 longitudinal zones. # # The proxy data is contained in a single Matlab file: # proxydata_aprmar_lmr_v0.2.0_pages2k_v2.mat md5:2d20435760a5e12bbc29501e7cd02b3d # # This collection of paleoclimate proxy data currently includes 2591 tree ring chronologies, 197 coral and # sclerosponge records, 153 ice core isotope records, 26 speleothem isotope records, 10 lake sediment records, # and 1 marine sediment record, for a total of 2,978 records. The proxy records have been collected with # a focus on the past 2000 years. # # This dataset has been collated through collaborative efforts with the Last Millennium Reanalysis project # (Hakim et al. 2016) and provides the basis for the reconstructions presented in Steiger et al. (2018). # Though the majority of data records are culled from PAGES2k Consortium (2017) and Breitenmoser et al. (2014), # some data was taken from the NOAA NCEI's World Data Center for Paleoclimatology archive. Additionally, data was # solicited from multiple investigators such as Eric Steig, Stephanie Hayman, Sylke Draschba, Henning Kuhnert, # Andy Baker, and others amounting to approximately 60 coral, ice core, speleothem, and lake sediment datasets, # though all files in this archive can be freely shared. Datasets were selected whose resolution was at least # 25 years, temporal duration was greater than 40 years, and consisted of proxies that had established proxy # system models (forward models). # # The data files are in Matlab format and the variables here include the proxy names ('lmr2k_names'), # the proxy data ('lmr2k_data'), the proxy type ('archive), the proxy measurement ('msrmt'), the proxy latitudes # and longitudes ('p_lat' and 'p_lon'), and the years of the proxies ('year'). Seasonally resolved proxies # have been averaged from April to the following calendar year March. # # Provided Keywords: Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI) # #-------------------- # Publication # Authors: Nathan J. Steiger, Jason E. Smerdon, Edward R. Cook, Benjamin I. Cook # Published_Date_or_Year: 2018-05-22 # Published_Title: A reconstruction of global hydroclimate and dynamical variables over the Common Era # Journal_Name: Scientific Data # Volume: 5 # Edition: 180086 # Issue: # Pages: # Report_Number: # DOI: 10.1038/sdata.2018.86 # Online_Resource: https://www.nature.com/articles/sdata201886 # Full_Citation: # Abstract: Hydroclimate extremes critically affect human and natural systems, but there remain many unanswered questions about their causes and how to interpret their dynamics in the past and in climate change projections. These uncertainties are due, in part, to the lack of long-term, spatially resolved hydroclimate reconstructions and information on the underlying physical drivers for many regions. Here we present the first global reconstructions of hydroclimate and associated climate dynamical variables over the past two thousand years. We use a data assimilation approach tailored to reconstruct hydroclimate that optimally combines 2,978 paleoclimate proxy-data time series with the physical constraints of an atmosphere-ocean climate model. The global reconstructions are annually or seasonally resolved and include two spatiotemporal drought indices, near-surface air temperature, an index of North Atlantic variability, the location of the intertropical convergence zone, and monthly Nino indices. This database, called the Paleo Hydrodynamics Data Assimilation product (PHYDA), will provide a critical new platform for investigating the causes of past climate variability and extremes, while informing interpretations of future hydroclimate projections. #------------------ # Funding_Agency # Funding_Agency_Name: US National Oceanic and Atmospheric Administration # Grant: Climate and Global Change Postdoctoral Fellowship Program #------------------ # Funding_Agency # Funding_Agency_Name: US National Science Foundation # Grant: AGS-1243204, AGS-1401400, AGS-1602581, AGS-1602920, OISE-1743738 #------------------ # Site_Information # Site_Name: Global # Location: Global # Country: # Northernmost_Latitude: 90 # Southernmost_Latitude: -90 # Easternmost_Longitude: 180 # Westernmost_Longitude: -180 # Elevation: #------------------ # Data_Collection # Collection_Name: Steiger2018hydro # Earliest_Year: 0 # Most_Recent_Year: 2000 # Time_Unit: CE # Core_Length: # Notes: #------------------ # Chronology_Information # Chronology: # #---------------- # Variables # # Data variables follow are preceded by "##" in columns one and two. # Data line variables format: one per line, shortname-tab-variable components (what, material, error, units, seasonality, data type,detail, method, C or N for Character or Numeric data, free text) # ## age_CE age, , , years common era, , , , ,N, ## temp surface air temperature, , , degrees c, ,climate reconstructions,,,N, ## PDSI Palmer Drought Severity Index, , , , ,climate reconstructions,,,N, ## SPEI standardized precipitation evapotranspiration index, , , , ,climate reconstructions,,,N, ## NASSTI North Atlantic sea surface temperature index, , , , ,climate reconstructions,,,N, ## ITCZ location of the intertropical convergence zone, , , , ,climate reconstructions,,,N, ## Nino1+2 Nino 1+2 sea surface temperature index, , , , ,climate reconstructions,,,N, ## Nino3 Nino 3 sea surface temperature index, , , , ,climate reconstructions,,,N, ## Nino3.4 Nino 3.4 sea surface temperature index, , , , ,climate reconstructions,,,N, ## Nino4 Nino 4 sea surface temperature index, , , , ,climate reconstructions,,,N, # #----------------