# northamerica_canada_cana233 - Galloping Mountain - Breitenmoser Tree Ring Chronology Data #----------------------------------------------------------------------- # 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: # # Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611 # # Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/5513 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: northamerica_canada_cana233 - Galloping Mountain - Breitenmoser Tree Ring Chronology Data #-------------------- # Investigators # Investigators: Breitenmoser, P.; Bronnimann, S.; Frank, D. #-------------------- # Description_and_Notes # Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details #-------------------- # Publication # Authors: Breitenmoser, P.; Bronnimann, S.; Frank, D. # Published_Date_or_Year: 2014-03-11 # Published_Title: Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies # Journal_Name: Climate of the Past # Volume: 10 # Edition: # Issue: # Pages: 437-449 # DOI: 10.5194/cp-10-437-2014 # Online_Resource: www.clim-past.net/10/437/2014/ # Full_Citation: # Abstract: We investigate relationships between climate and tree-ring data on a global scale using the process-based Vaganov–Shashkin Lite (VSL) forward model of tree-ring width formation. The VSL model requires as inputs only latitude, monthly mean temperature, and monthly accumulated precipitation. Hence, this simple, process-based model enables ring-width simulation at any location where monthly climate records exist. In this study, we analyse the growth response of simulated tree rings to monthly climate conditions obtained from the CRU TS3.1 data set back to 1901. Our key aims are (a) to assess the VSL model performance by examining the relations between simulated and observed growth at 2287 globally distributed sites, (b) indentify optimal growth parameters found during the model calibration, and (c) to evaluate the potential of the VSL model as an observation operator for data-assimilation-based reconstructions of climate from tree-ring width. The assessment of the growth-onset threshold temperature of approximately 4–6 C for most sites and species using a Bayesian estimation approach complements other studies on the lower temperature limits where plant growth may be sustained. Our results suggest that the VSL model skilfully simulates site level treering series in response to climate forcing for a wide range of environmental conditions and species. Spatial aggregation of the tree-ring chronologies to reduce non-climatic noise at the site level yielded notable improvements in the coherence between modelled and actual growth. The resulting distinct and coherent patterns of significant relationships between the aggregated and simulated series further demonstrate the VSL model’s ability to skilfully capture the climatic signal contained in tree-ring series. Finally, we propose that the VSL model can be used as an observation operator in data assimilation approaches to reconstruct past climate. #-------------------- # Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig # Published_Date_or_Year: 2018 # Published_Title: Additions to the last millennium reanalysis multi-proxy database # Journal_Name: Data Science Journal # Volume: # Edition: # Issue: # Pages: # Report_Number: # DOI: # Online_Resource: # Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal. # 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. #------------------ # Funding_Agency # Funding_Agency_Name: Swiss National Science Foundation # Grant: #-------------------- # Funding_Agency_Name: National Science Foundation # Grant:AGS-1304263 # Funding_Agency_Name: National Oceanic and Atmospheric Administration # Grant:NA14OAR4310176 #------------------ # Site_Information # Site_Name: Galloping Mountain # Location: # Country: Canada # Northernmost_Latitude: 49.9 # Southernmost_Latitude: 49.9 # Easternmost_Longitude: -118.37 # Westernmost_Longitude: -118.37 # Elevation: 2050 m #-------------------- # Data_Collection # Collection_Name: northamerica_canada_cana233B # Earliest_Year: 1842 # Most_Recent_Year: 1997 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.75121164285","T2":"18.5760409219","M1":"0.0227194474233","M2":"0.354266552124"}} #-------------------- # Species # Species_Name: Engelmann spruce # Species_Code: PCEN #-------------------- # Chronology: # # # #-------------------- # Variables # # Data variables follow that 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 age, , ,years AD, , , , ,N ##trsgi tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N # #-------------------- # Data: # Data lines follow (have no #) # Data line format - tab-delimited text, variable short name as header # Missing Values: nan # age trsgi 1842 0.908 1843 1.127 1844 0.776 1845 0.91 1846 0.843 1847 0.695 1848 0.948 1849 0.656 1850 0.678 1851 0.794 1852 0.828 1853 0.793 1854 0.594 1855 0.842 1856 0.689 1857 0.761 1858 0.861 1859 0.957 1860 1.003 1861 0.935 1862 0.956 1863 1.246 1864 0.759 1865 1.095 1866 1.14 1867 0.872 1868 1.05 1869 1.131 1870 0.848 1871 0.943 1872 0.956 1873 0.963 1874 0.942 1875 0.939 1876 0.724 1877 0.83 1878 0.896 1879 0.937 1880 0.67 1881 0.813 1882 0.958 1883 0.801 1884 0.7 1885 0.965 1886 0.984 1887 0.838 1888 0.854 1889 0.923 1890 0.958 1891 0.996 1892 0.951 1893 1.004 1894 0.964 1895 1.004 1896 1.098 1897 1.104 1898 1.235 1899 0.822 1900 0.936 1901 1.181 1902 1.096 1903 1.094 1904 1.223 1905 1.06 1906 0.928 1907 0.973 1908 1.23 1909 1.118 1910 1.119 1911 1.074 1912 1.041 1913 1.063 1914 1.18 1915 0.827 1916 0.919 1917 1.035 1918 1.336 1919 1.378 1920 1.184 1921 0.769 1922 0.877 1923 0.791 1924 0.866 1925 1.097 1926 1.057 1927 0.999 1928 1.0 1929 0.988 1930 1.022 1931 1.265 1932 1.275 1933 1.319 1934 1.211 1935 1.2 1936 1.632 1937 1.353 1938 1.666 1939 1.318 1940 1.547 1941 1.33 1942 1.025 1943 1.134 1944 1.283 1945 1.396 1946 1.09 1947 1.306 1948 1.294 1949 1.295 1950 1.442 1951 1.213 1952 1.186 1953 1.262 1954 1.216 1955 1.121 1956 0.972 1957 1.009 1958 1.386 1959 0.895 1960 1.077 1961 1.315 1962 1.02 1963 1.129 1964 0.955 1965 1.152 1966 1.095 1967 1.317 1968 0.823 1969 0.729 1970 1.0 1971 0.785 1972 0.653 1973 0.869 1974 0.724 1975 0.79 1976 0.711 1977 0.926 1978 0.859 1979 0.871 1980 0.784 1981 0.787 1982 0.664 1983 0.66 1984 0.755 1985 0.681 1986 0.575 1987 0.79 1988 0.773 1989 0.808 1990 0.8 1991 0.584 1992 0.745 1993 0.525 1994 0.921 1995 0.686 1996 0.566 1997 0.514