# europe_swit129 - Balmberg SO Trocken - 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/4329 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit129 - Balmberg SO Trocken - 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: Balmberg SO Trocken # Location: # Country: Switzerland # Northernmost_Latitude: 47.25 # Southernmost_Latitude: 47.25 # Easternmost_Longitude: 7.53 # Westernmost_Longitude: 7.53 # Elevation: 1220 m #-------------------- # Data_Collection # Collection_Name: europe_swit129B # Earliest_Year: 1827 # Most_Recent_Year: 1982 # 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":"4.52637152642","T2":"15.9190062263","M1":"0.0221503649493","M2":"0.600466693958"}} #-------------------- # 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 1827 0.847 1828 1.051 1829 1.026 1830 0.843 1831 1.143 1832 1.052 1833 0.848 1834 0.993 1835 0.915 1836 0.789 1837 0.832 1838 0.782 1839 0.677 1840 0.957 1841 1.026 1842 1.169 1843 1.145 1844 1.134 1845 1.302 1846 1.262 1847 1.171 1848 1.078 1849 1.244 1850 1.169 1851 1.217 1852 1.272 1853 1.338 1854 1.343 1855 1.042 1856 1.119 1857 1.121 1858 0.867 1859 0.975 1860 1.026 1861 1.106 1862 0.893 1863 1.004 1864 1.058 1865 0.707 1866 0.95 1867 0.9 1868 0.783 1869 1.271 1870 0.779 1871 1.165 1872 1.044 1873 0.997 1874 0.945 1875 1.212 1876 1.042 1877 1.023 1878 1.144 1879 1.167 1880 1.351 1881 1.289 1882 1.394 1883 1.198 1884 1.175 1885 1.106 1886 0.91 1887 0.819 1888 0.656 1889 0.977 1890 0.865 1891 0.856 1892 0.875 1893 0.67 1894 0.791 1895 0.83 1896 0.817 1897 0.979 1898 1.163 1899 0.994 1900 1.08 1901 0.92 1902 1.125 1903 1.27 1904 1.182 1905 1.171 1906 0.945 1907 1.116 1908 0.985 1909 0.783 1910 0.657 1911 0.602 1912 0.606 1913 0.687 1914 0.73 1915 0.709 1916 0.735 1917 0.722 1918 0.747 1919 0.763 1920 0.785 1921 0.828 1922 0.67 1923 0.648 1924 0.753 1925 0.978 1926 0.83 1927 0.899 1928 0.877 1929 1.128 1930 1.371 1931 1.083 1932 1.187 1933 0.945 1934 0.679 1935 1.121 1936 0.865 1937 0.733 1938 0.829 1939 0.948 1940 0.609 1941 0.574 1942 0.929 1943 0.855 1944 0.81 1945 0.39 1946 0.757 1947 0.648 1948 0.617 1949 0.64 1950 0.867 1951 1.335 1952 1.134 1953 1.046 1954 1.189 1955 1.356 1956 0.998 1957 1.401 1958 1.688 1959 1.486 1960 1.149 1961 1.054 1962 1.047 1963 1.226 1964 1.216 1965 1.422 1966 1.569 1967 1.129 1968 1.1 1969 1.192 1970 1.333 1971 1.154 1972 1.233 1973 1.083 1974 1.009 1975 0.984 1976 0.608 1977 1.102 1978 0.784 1979 0.964 1980 0.896 1981 1.005 1982 1.002