# europe_spai018 - Andrinal - 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/3283 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_spai018 - Andrinal - 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: Andrinal # Location: # Country: Spain # Northernmost_Latitude: 40.43 # Southernmost_Latitude: 40.43 # Easternmost_Longitude: -4.93 # Westernmost_Longitude: -4.93 # Elevation: 1500 m #-------------------- # Data_Collection # Collection_Name: europe_spai018B # Earliest_Year: 1792 # Most_Recent_Year: 1989 # 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":"4.51323404474","T2":"15.5505135132","M1":"0.0223547","M2":"0.424796264756"}} #-------------------- # Species # Species_Name: Austrian pine # Species_Code: PINI #-------------------- # 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 1792 0.615 1793 0.574 1794 0.947 1795 1.17 1796 1.309 1797 1.325 1798 1.403 1799 1.61 1800 1.743 1801 1.663 1802 1.39 1803 0.834 1804 1.144 1805 1.202 1806 0.857 1807 1.119 1808 0.97 1809 0.897 1810 1.001 1811 1.329 1812 0.923 1813 0.779 1814 0.867 1815 1.073 1816 0.871 1817 1.029 1818 1.111 1819 1.044 1820 0.907 1821 1.184 1822 1.097 1823 1.108 1824 0.978 1825 0.818 1826 0.427 1827 0.401 1828 0.716 1829 0.875 1830 0.782 1831 0.66 1832 0.506 1833 0.679 1834 1.031 1835 1.362 1836 1.255 1837 1.049 1838 0.785 1839 0.819 1840 0.704 1841 0.979 1842 0.932 1843 1.1 1844 1.382 1845 1.257 1846 1.36 1847 1.072 1848 1.011 1849 1.052 1850 1.42 1851 1.115 1852 0.891 1853 0.574 1854 0.791 1855 0.659 1856 0.762 1857 0.886 1858 0.968 1859 0.93 1860 0.726 1861 0.794 1862 0.791 1863 0.838 1864 1.226 1865 1.412 1866 1.255 1867 1.417 1868 1.503 1869 1.51 1870 1.163 1871 0.934 1872 1.046 1873 1.002 1874 0.745 1875 0.611 1876 0.431 1877 0.85 1878 1.114 1879 0.776 1880 1.122 1881 1.523 1882 1.589 1883 1.134 1884 1.191 1885 1.567 1886 1.501 1887 0.983 1888 1.328 1889 1.133 1890 0.879 1891 0.883 1892 1.046 1893 1.233 1894 0.85 1895 0.97 1896 0.955 1897 0.899 1898 1.231 1899 0.873 1900 0.552 1901 0.709 1902 1.019 1903 1.494 1904 1.16 1905 1.046 1906 1.226 1907 1.292 1908 1.029 1909 0.653 1910 1.026 1911 1.242 1912 1.405 1913 1.235 1914 1.465 1915 0.975 1916 0.863 1917 0.734 1918 0.76 1919 0.979 1920 1.193 1921 1.066 1922 0.791 1923 1.082 1924 0.756 1925 0.998 1926 1.284 1927 0.963 1928 0.8 1929 0.84 1930 0.54 1931 0.565 1932 0.972 1933 1.015 1934 0.573 1935 0.713 1936 0.787 1937 1.06 1938 0.835 1939 0.834 1940 1.094 1941 0.663 1942 0.391 1943 0.752 1944 0.689 1945 0.994 1946 0.586 1947 0.697 1948 0.873 1949 0.997 1950 1.287 1951 0.893 1952 0.944 1953 1.033 1954 0.773 1955 0.904 1956 0.827 1957 1.145 1958 1.082 1959 1.031 1960 0.875 1961 0.867 1962 0.596 1963 0.58 1964 1.213 1965 0.904 1966 0.983 1967 0.764 1968 0.698 1969 0.767 1970 0.751 1971 0.691 1972 0.805 1973 1.202 1974 0.904 1975 0.769 1976 1.276 1977 1.465 1978 1.033 1979 0.675 1980 1.252 1981 0.993 1982 1.019 1983 1.298 1984 1.162 1985 1.065 1986 0.654 1987 1.163 1988 0.835 1989 0.765