# europe_swit192 - Vals GR Riefawald - 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/8498 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit192 - Vals GR Riefawald - 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: Vals GR Riefawald # Location: # Country: Switzerland # Northernmost_Latitude: 46.62 # Southernmost_Latitude: 46.62 # Easternmost_Longitude: 9.2 # Westernmost_Longitude: 9.2 # Elevation: 1900 m #-------------------- # Data_Collection # Collection_Name: europe_swit192B # Earliest_Year: 1770 # Most_Recent_Year: 2008 # 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":"5.05522143534","T2":"17.2961249939","M1":"0.0230139874066","M2":"0.399769682243"}} #-------------------- # Species # Species_Name: European larch # Species_Code: LADE #-------------------- # 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 1770 0.657 1771 0.805 1772 0.918 1773 0.893 1774 1.049 1775 1.236 1776 1.2 1777 0.675 1778 0.771 1779 0.39 1780 1.352 1781 1.374 1782 1.417 1783 1.136 1784 2.027 1785 1.421 1786 1.736 1787 1.11 1788 2.032 1789 1.613 1790 1.191 1791 1.331 1792 1.25 1793 1.068 1794 0.964 1795 0.633 1796 0.895 1797 1.123 1798 1.263 1799 0.918 1800 0.691 1801 0.6 1802 0.916 1803 1.039 1804 0.811 1805 0.628 1806 0.737 1807 1.096 1808 1.343 1809 0.769 1810 0.628 1811 1.092 1812 0.89 1813 0.383 1814 0.564 1815 0.453 1816 0.293 1817 0.58 1818 0.968 1819 0.913 1820 0.748 1821 0.385 1822 1.655 1823 1.427 1824 1.029 1825 0.887 1826 0.982 1827 1.192 1828 0.969 1829 0.97 1830 0.602 1831 1.043 1832 0.872 1833 1.078 1834 1.262 1835 1.956 1836 1.426 1837 1.332 1838 1.025 1839 1.298 1840 1.278 1841 1.192 1842 2.177 1843 0.715 1844 0.96 1845 0.876 1846 1.05 1847 0.886 1848 0.854 1849 1.313 1850 0.975 1851 0.756 1852 0.788 1853 0.995 1854 0.392 1855 0.883 1856 0.708 1857 0.595 1858 1.048 1859 1.174 1860 1.1 1861 1.232 1862 1.502 1863 1.652 1864 1.01 1865 0.952 1866 0.891 1867 0.541 1868 1.161 1869 0.941 1870 1.398 1871 0.536 1872 0.993 1873 1.102 1874 1.438 1875 1.377 1876 1.489 1877 1.413 1878 0.873 1879 0.773 1880 0.552 1881 0.961 1882 0.557 1883 0.92 1884 0.688 1885 1.094 1886 0.349 1887 1.129 1888 0.549 1889 0.942 1890 0.419 1891 0.603 1892 1.021 1893 0.848 1894 0.965 1895 1.003 1896 1.173 1897 0.952 1898 0.705 1899 1.176 1900 1.229 1901 1.441 1902 1.102 1903 1.248 1904 1.935 1905 1.532 1906 0.937 1907 0.728 1908 1.259 1909 0.381 1910 0.861 1911 0.963 1912 0.766 1913 0.276 1914 0.448 1915 1.019 1916 0.584 1917 1.395 1918 0.518 1919 0.651 1920 0.652 1921 1.04 1922 1.328 1923 0.872 1924 1.139 1925 1.202 1926 0.444 1927 1.005 1928 1.178 1929 0.912 1930 1.135 1931 1.518 1932 0.959 1933 0.876 1934 1.463 1935 1.541 1936 1.003 1937 1.027 1938 0.778 1939 0.814 1940 0.556 1941 1.141 1942 0.844 1943 1.055 1944 1.406 1945 1.223 1946 0.595 1947 1.076 1948 0.701 1949 1.251 1950 1.385 1951 1.145 1952 1.348 1953 0.407 1954 0.591 1955 0.482 1956 0.201 1957 0.295 1958 0.69 1959 0.714 1960 0.799 1961 0.51 1962 0.996 1963 0.362 1964 0.285 1965 0.47 1966 0.516 1967 0.854 1968 0.524 1969 0.626 1970 0.899 1971 0.915 1972 0.784 1973 0.924 1974 0.713 1975 0.397 1976 0.584 1977 0.532 1978 0.457 1979 0.892 1980 0.438 1981 0.355 1982 0.92 1983 1.073 1984 0.951 1985 0.818 1986 1.165 1987 0.936 1988 1.155 1989 1.46 1990 1.162 1991 1.106 1992 0.853 1993 1.127 1994 1.191 1995 1.151 1996 1.105 1997 0.826 1998 1.541 1999 0.848 2000 1.314 2001 1.667 2002 1.455 2003 1.469 2004 1.328 2005 1.821 2006 1.64 2007 1.52 2008 1.655