# North America Last 2ka Decadal Temperature Reconstructions #----------------------------------------------------------------------- # World Data Center for Paleoclimatology, Boulder # and # NOAA Paleoclimatology Program #----------------------------------------------------------------------- # 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: http://hurricane.ncdc.noaa.gov/pls/paleox/f?p=519:1:::::P1_STUDY_ID:16257 # # Original_Source_URL: ftp://ftp.ncdc.noaa.gov/pub/data/paleo/pages2k/trouet2013nam1200tr-ann.txt # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Climate Reconstructions #-------------------- # Contribution_Date # Date: 2014-03-30 #-------------------- # Title # Study_Name: North America Last 2ka Decadal Temperature Reconstructions #-------------------- # Investigators # Investigators: Trouet, V.; Diaz, H., Wahl, E.; Viau, A.; Graham, R.; Graham, N.; Cook, E. #-------------------- # Description_and_Notes # Description: PAGES North America 2k Temperature Reconstructions, including tree-ring based reconstructions # at annual and decadal resolution (1200-1980 CE), plus a pollen-based reconstruction at 30 year resolution (480-1950 CE). #-------------------- # Publication # Authors: V Trouet, H F Diaz, E R Wahl, A E Viau, R Graham, N Graham and E R Cook # Published_Date_or_Year: 2013-04-13 # Published_Title: A 1500-year reconstruction of annual mean temperature for temperate North America on decadal-to-multidecadal time scales # Journal_Name: Environmental Research Letters # Volume: 8 # Edition: # Issue: 2 # Pages: # DOI: 10.1088/1748-9326/8/2/024008 # Online_Resource: http://iopscience.iop.org/1748-9326/8/2/024008/article # Full_Citation: # Abstract: We present two reconstructions of annual average temperature over temperate North America: a tree-ring based reconstruction at decadal resolution (1200-1980 CE) and a pollen-based reconstruction at 30 year resolution that extends back to 480 CE. We maximized reconstruction length by using long but low-resolution pollen records and applied a three-tier calibration scheme for this purpose. The tree-ring-based reconstruction was calibrated against instrumental annual average temperatures on annual and decadal scale, it was then reduced to a lower resolution, and was used as a calibration target for the pollen-based reconstruction. Before the late-19th to the early-21st century, there are three prominent low-frequency periods in our extended reconstruction starting at 480 CE, notably the Dark Ages cool period (about 500-700 CE) and Little Ice Age (about 1200-1900 CE), and the warmer medieval climate anomaly (MCA; about 750-1100 CE). The 9th and the 11th century are the warmest centuries and they constitute the core of the MCA in our reconstruction, a period characterized by centennial-scale aridity in the North American West. These two warm peaks are slightly warmer than the baseline period (1904-1980), but nevertheless much cooler than temperate North American temperatures during the early-21st century. #------------------ # Publication # Authors: PAGES 2k Consortium # Published_Date_or_Year: 2013-04-21 # Published_Title: Continental-scale temperature variability during the past two millennia # Journal_Name: Nature Geoscience # Volume: 6 # Edition: # Issue: # Pages: 339-346 # DOI: 10.1038/ngeo1797 # Online_Resource: http://www.nature.com/ngeo/journal/v6/n5/full/ngeo1797.html # Full_Citation: # Abstract: Past global climate changes had strong regional expression. To elucidate their spatio-temporal pattern, we reconstructed past temperatures for seven continental-scale regions during the past one to two millennia. The most coherent feature in nearly all of the regional temperature reconstructions is a long-term cooling trend, which ended late in the nineteenth century. At multi-decadal to centennial scales, temperature variability shows distinctly different regional patterns, with more similarity within each hemisphere than between them. There were no globally synchronous multi-decadal warm or cold intervals that define a worldwide Medieval Warm Period or Little Ice Age, but all reconstructions show generally cold conditions between ad 1580 and 1880, punctuated in some regions by warm decades during the eighteenth century. The transition to these colder conditions occurred earlier in the Arctic, Europe and Asia than in North America or the Southern Hemisphere regions. Recent warming reversed the long-term cooling; during the period ad 1971-2000, the area-weighted average reconstructed temperature was higher than any other time in nearly 1,400 years. #------------------ # Funding_Agency # Funding_Agency_Name: IGBP PAGES # Grant: #------------------ # Site_Information # Site_Name: Temperate North America # Location: North America # Country: # Northernmost_Latitude: 55.0 # Southernmost_Latitude: 30.0 # Easternmost_Longitude: -75.0 # Westernmost_Longitude: -130.0 # Elevation: m #------------------ # Data_Collection # Collection_Name: Trouet2013NAM1200TRann # Earliest_Year: 1200 # Most_Recent_Year: 1987 # Time_Unit: AD # Core_Length: m # Notes: #------------------ # Chronology: # # # #---------------- # Variables # # Data variables follow are preceded by "##" in columns one and two. # Data line variables format: Variables list, one per line, shortname-tab-longname-tab-longname components (9 components: what, material, error, units, seasonality, archive, detail, method, C or N for Character or Numeric data) # # ##age_AD age, , , AD, , , , ,N ##temp2m-ann 2m air temperature, ring width, , deg C, annual, tree rings, wrt 1904-1980, PC spatial regression,N ##temp2m-ann2.5 2m air temperature, ring width, 2.5 percentile, deg C, annual, tree rings, wrt 1904-1980, PC spatial regression,N ##temp2m-ann97.5 2m air temperature, ring width, 97.5 percentile, deg C, annual, tree rings, wrt 1904-1980, PC spatial regression,N # # #---------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: # age_AD temp2m-ann temp2m-ann2.5 temp2m-ann97.5 1200 0.127390187 -0.416577058 0.6077138 1201 0.227425215 -0.302225678 0.6907226 1202 -0.179981775 -0.467719517 0.06406086 1203 -0.258996636 -0.677642401 0.1865496 1204 -0.288868094 -0.770368072 0.1505203 1205 -0.6952619 -0.992402364 -0.3742265 1206 -0.483791596 -0.91194555 -0.0495955 1207 -0.108589147 -0.662872019 0.3787706 1208 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