# europe_czec002 - Krkonose Mountains Upper Labe Valley Southern Slope - 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/4284 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_czec002 - Krkonose Mountains Upper Labe Valley Southern Slope - 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: Krkonose Mountains Upper Labe Valley Southern Slope # Location: # Country: Czech Republic # Northernmost_Latitude: 50.75 # Southernmost_Latitude: 50.75 # Easternmost_Longitude: 15.55 # Westernmost_Longitude: 15.55 # Elevation: 1150 m #-------------------- # Data_Collection # Collection_Name: europe_czec002B # Earliest_Year: 1807 # Most_Recent_Year: 1990 # 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":"5.42222135933","T2":"19.8982391961","M1":"0.0221392193203","M2":"0.350823325815"}} #-------------------- # 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 1807 1.267 1808 1.124 1809 1.09 1810 0.924 1811 1.024 1812 1.03 1813 0.956 1814 0.951 1815 0.94 1816 0.864 1817 0.882 1818 0.797 1819 0.864 1820 0.818 1821 0.713 1822 0.652 1823 0.761 1824 0.923 1825 0.956 1826 1.101 1827 0.924 1828 0.975 1829 0.987 1830 0.918 1831 1.172 1832 0.982 1833 1.28 1834 1.041 1835 0.889 1836 0.925 1837 0.879 1838 0.787 1839 1.17 1840 1.035 1841 0.942 1842 1.205 1843 0.817 1844 0.807 1845 0.9 1846 1.112 1847 1.106 1848 1.127 1849 1.072 1850 1.12 1851 0.942 1852 1.146 1853 1.182 1854 1.119 1855 1.053 1856 1.0 1857 1.262 1858 1.117 1859 1.146 1860 1.069 1861 1.111 1862 0.995 1863 1.297 1864 1.15 1865 0.934 1866 0.989 1867 0.933 1868 1.021 1869 0.823 1870 1.008 1871 0.897 1872 0.857 1873 1.005 1874 1.022 1875 1.029 1876 0.977 1877 0.935 1878 0.96 1879 0.957 1880 1.168 1881 1.283 1882 1.2 1883 1.001 1884 1.094 1885 1.041 1886 0.991 1887 1.005 1888 0.878 1889 0.943 1890 0.823 1891 0.744 1892 1.007 1893 0.991 1894 0.972 1895 1.065 1896 0.899 1897 0.931 1898 1.009 1899 0.988 1900 0.953 1901 1.002 1902 0.87 1903 0.893 1904 0.873 1905 0.878 1906 0.694 1907 0.868 1908 1.036 1909 0.863 1910 0.988 1911 1.107 1912 0.934 1913 0.818 1914 0.942 1915 0.928 1916 0.847 1917 1.092 1918 0.815 1919 0.978 1920 0.754 1921 0.886 1922 0.978 1923 0.706 1924 0.982 1925 0.895 1926 0.92 1927 1.124 1928 1.068 1929 1.105 1930 0.995 1931 1.294 1932 1.002 1933 1.008 1934 1.23 1935 1.322 1936 1.233 1937 1.061 1938 1.031 1939 1.112 1940 1.012 1941 0.989 1942 0.689 1943 0.749 1944 0.986 1945 1.042 1946 1.311 1947 1.35 1948 0.975 1949 1.02 1950 1.285 1951 1.055 1952 1.246 1953 1.193 1954 0.967 1955 1.102 1956 0.741 1957 1.029 1958 1.084 1959 1.192 1960 1.212 1961 1.212 1962 1.242 1963 1.47 1964 1.079 1965 0.892 1966 1.234 1967 1.253 1968 1.155 1969 1.12 1970 1.047 1971 0.773 1972 0.999 1973 1.11 1974 0.562 1975 0.89 1976 0.842 1977 0.878 1978 0.78 1979 0.925 1980 0.493 1981 0.587 1982 0.478 1983 0.55 1984 0.394 1985 0.517 1986 0.726 1987 0.741 1988 0.779 1989 0.844 1990 0.94