# europe_germ033 - Arber - 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/5263 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_germ033 - Arber - 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: Arber # Location: # Country: Germany # Northernmost_Latitude: 49.12 # Southernmost_Latitude: 49.12 # Easternmost_Longitude: 13.13 # Westernmost_Longitude: 13.13 # Elevation: 1420 m #-------------------- # Data_Collection # Collection_Name: europe_germ033B # Earliest_Year: 1850 # 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":"3.92100501967","T2":"19.3624691557","M1":"0.0226152603756","M2":"0.27562210193"}} #-------------------- # Species # Species_Name: Norway spruce # Species_Code: PCAB #-------------------- # 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 1850 0.907 1851 0.662 1852 0.836 1853 0.983 1854 0.95 1855 0.885 1856 0.888 1857 1.285 1858 1.267 1859 1.06 1860 0.796 1861 0.815 1862 0.951 1863 1.476 1864 1.126 1865 1.038 1866 1.019 1867 1.028 1868 0.915 1869 1.083 1870 1.1 1871 1.07 1872 1.038 1873 1.291 1874 1.312 1875 1.442 1876 1.258 1877 1.093 1878 1.236 1879 1.015 1880 1.081 1881 1.336 1882 1.011 1883 0.878 1884 1.15 1885 1.027 1886 0.871 1887 1.01 1888 0.987 1889 1.044 1890 0.828 1891 0.764 1892 0.861 1893 0.91 1894 0.999 1895 1.058 1896 0.765 1897 0.898 1898 0.987 1899 1.089 1900 0.957 1901 1.205 1902 1.037 1903 1.182 1904 1.11 1905 0.844 1906 0.808 1907 1.083 1908 1.224 1909 1.19 1910 1.16 1911 1.307 1912 1.144 1913 0.91 1914 0.863 1915 0.682 1916 0.916 1917 0.867 1918 0.672 1919 0.77 1920 0.669 1921 0.641 1922 0.578 1923 0.589 1924 0.72 1925 0.809 1926 0.692 1927 0.897 1928 0.807 1929 0.935 1930 0.958 1931 1.198 1932 1.038 1933 0.968 1934 1.253 1935 1.172 1936 1.103 1937 0.962 1938 0.886 1939 1.079 1940 1.141 1941 0.96 1942 0.887 1943 1.017 1944 1.111 1945 1.236 1946 1.24 1947 1.167 1948 0.777 1949 0.795 1950 0.864 1951 0.852 1952 1.083 1953 1.102 1954 0.864 1955 1.005 1956 0.866 1957 1.11 1958 1.042 1959 1.533 1960 1.499 1961 1.42 1962 1.441 1963 1.752 1964 1.256 1965 0.896 1966 1.246 1967 1.188 1968 1.047 1969 1.274 1970 1.158 1971 1.187 1972 0.993 1973 1.136 1974 0.753 1975 0.926 1976 0.639 1977 1.044 1978 0.616 1979 0.932 1980 0.395 1981 0.788 1982 0.562 1983 0.708 1984 0.683 1985 0.716 1986 0.918 1987 0.566 1988 0.777 1989 0.803 1990 0.846 1991 0.823 1992 1.102 1993 1.011 1994 1.105 1995 0.805 1996 0.792 1997 1.051