# europe_swed009 - Arosjak - 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/3464 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swed009 - Arosjak - 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: Arosjak # Location: # Country: Sweden # Northernmost_Latitude: 67.87 # Southernmost_Latitude: 67.87 # Easternmost_Longitude: 19.42 # Westernmost_Longitude: 19.42 # Elevation: 762 m #-------------------- # Data_Collection # Collection_Name: europe_swed009B # Earliest_Year: 1774 # Most_Recent_Year: 1971 # 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":"7.21619702691","T2":"19.4420169725","M1":"0.0225016810414","M2":"0.284933663083"}} #-------------------- # Species # Species_Name: Scots pine # Species_Code: PISY #-------------------- # 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 1774 0.798 1775 0.813 1776 0.899 1777 0.687 1778 0.846 1779 0.732 1780 0.909 1781 0.7 1782 0.835 1783 0.511 1784 0.549 1785 0.752 1786 0.438 1787 0.569 1788 0.514 1789 0.814 1790 0.683 1791 0.729 1792 0.733 1793 0.574 1794 0.687 1795 0.711 1796 0.633 1797 0.762 1798 0.786 1799 0.975 1800 0.786 1801 0.907 1802 0.896 1803 0.563 1804 0.664 1805 0.612 1806 0.408 1807 0.553 1808 0.631 1809 0.663 1810 0.627 1811 0.712 1812 0.497 1813 0.676 1814 0.63 1815 0.776 1816 1.002 1817 1.114 1818 1.238 1819 1.372 1820 1.148 1821 0.953 1822 0.855 1823 1.153 1824 1.11 1825 1.154 1826 1.494 1827 1.486 1828 1.429 1829 1.389 1830 1.331 1831 1.717 1832 1.495 1833 1.326 1834 1.444 1835 1.144 1836 1.084 1837 0.526 1838 0.93 1839 0.949 1840 0.787 1841 0.69 1842 0.837 1843 0.906 1844 0.914 1845 1.234 1846 1.27 1847 1.468 1848 1.074 1849 1.204 1850 1.159 1851 1.243 1852 1.368 1853 1.27 1854 1.614 1855 1.49 1856 1.256 1857 0.886 1858 1.441 1859 1.106 1860 1.096 1861 1.323 1862 1.177 1863 1.096 1864 1.192 1865 1.213 1866 1.172 1867 1.008 1868 0.972 1869 0.972 1870 0.948 1871 0.918 1872 1.04 1873 1.432 1874 1.066 1875 1.364 1876 1.475 1877 1.244 1878 1.025 1879 1.26 1880 0.915 1881 0.663 1882 0.951 1883 1.195 1884 1.143 1885 1.103 1886 0.957 1887 1.035 1888 0.811 1889 0.988 1890 1.222 1891 1.277 1892 0.865 1893 0.959 1894 1.173 1895 1.139 1896 1.198 1897 1.241 1898 1.324 1899 1.062 1900 0.82 1901 1.4 1902 1.065 1903 0.678 1904 0.728 1905 0.849 1906 0.882 1907 0.852 1908 1.027 1909 0.798 1910 0.833 1911 0.823 1912 1.093 1913 0.973 1914 1.093 1915 1.233 1916 1.31 1917 1.117 1918 1.374 1919 1.25 1920 1.178 1921 1.127 1922 1.135 1923 1.0 1924 1.028 1925 1.241 1926 1.08 1927 1.089 1928 0.613 1929 0.601 1930 1.202 1931 0.966 1932 0.857 1933 0.741 1934 1.088 1935 0.731 1936 0.539 1937 1.186 1938 1.148 1939 0.825 1940 0.706 1941 1.086 1942 0.793 1943 0.852 1944 0.958 1945 1.136 1946 0.962 1947 0.982 1948 1.011 1949 0.903 1950 0.946 1951 0.932 1952 0.849 1953 1.04 1954 1.363 1955 1.021 1956 0.808 1957 0.909 1958 0.704 1959 0.815 1960 0.895 1961 0.702 1962 0.702 1963 0.517 1964 0.836 1965 0.599 1966 0.686 1967 0.741 1968 0.724 1969 0.753 1970 0.885 1971 0.646