# europe_germ009 - Schaumburg - 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/4291 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_germ009 - Schaumburg - 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: Schaumburg # Location: # Country: Germany # Northernmost_Latitude: 52.32 # Southernmost_Latitude: 52.32 # Easternmost_Longitude: 9.03 # Westernmost_Longitude: 9.03 # Elevation: 50 m #-------------------- # Data_Collection # Collection_Name: europe_germ009B # Earliest_Year: 1839 # Most_Recent_Year: 1971 # Time_Unit: y_ad # Core_Length: # Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.65495291697","T2":"16.1821040084","M1":"0.0228171769279","M2":"0.552715862814"}} #-------------------- # Species # Species_Name: English oak # Species_Code: QURO #-------------------- # 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 1839 0.761 1840 0.664 1841 0.631 1842 0.773 1843 1.079 1844 0.81 1845 0.745 1846 0.723 1847 0.812 1848 0.77 1849 0.724 1850 0.9 1851 0.955 1852 0.939 1853 1.016 1854 1.119 1855 1.12 1856 1.182 1857 0.781 1858 0.837 1859 0.839 1860 0.946 1861 1.476 1862 1.296 1863 1.06 1864 1.067 1865 0.699 1866 1.046 1867 1.2 1868 0.93 1869 0.652 1870 1.161 1871 0.923 1872 0.523 1873 0.696 1874 0.87 1875 1.305 1876 1.361 1877 1.48 1878 1.752 1879 1.304 1880 1.312 1881 0.85 1882 0.862 1883 0.824 1884 1.356 1885 1.112 1886 0.963 1887 0.815 1888 0.988 1889 0.915 1890 1.01 1891 1.039 1892 1.107 1893 0.694 1894 0.904 1895 1.097 1896 1.139 1897 1.059 1898 1.282 1899 1.179 1900 1.245 1901 0.933 1902 1.055 1903 1.407 1904 1.093 1905 1.142 1906 1.209 1907 1.146 1908 1.214 1909 0.65 1910 0.763 1911 0.668 1912 0.957 1913 1.125 1914 1.249 1915 0.877 1916 0.632 1917 1.049 1918 0.981 1919 0.765 1920 0.855 1921 0.609 1922 0.882 1923 0.866 1924 1.212 1925 0.776 1926 0.889 1927 1.103 1928 0.783 1929 0.683 1930 0.6 1931 1.025 1932 1.053 1933 0.986 1934 0.62 1935 0.855 1936 1.012 1937 0.916 1938 0.939 1939 0.921 1940 0.779 1941 0.72 1942 0.958 1943 0.972 1944 0.754 1945 0.92 1946 0.871 1947 0.638 1948 0.904 1949 1.207 1950 1.326 1951 0.937 1952 0.879 1953 0.902 1954 0.778 1955 1.07 1956 0.884 1957 0.851 1958 0.924 1959 0.517 1960 0.758 1961 1.156 1962 0.902 1963 0.885 1964 0.871 1965 1.19 1966 1.49 1967 1.304 1968 1.051 1969 1.228 1970 1.212 1971 1.3