# europe_swit121 - Mittleri Hellelawald - 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/4531 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit121 - Mittleri Hellelawald - 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: Mittleri Hellelawald # Location: # Country: Switzerland # Northernmost_Latitude: 46.3 # Southernmost_Latitude: 46.3 # Easternmost_Longitude: 7.83 # Westernmost_Longitude: 7.83 # Elevation: 1510 m #-------------------- # Data_Collection # Collection_Name: europe_swit121B # Earliest_Year: 1836 # Most_Recent_Year: 1980 # 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":"5.71333403446","T2":"16.77645167","M1":"0.0223690052909","M2":"0.392644897201"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABAL #-------------------- # 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 1836 0.692 1837 0.767 1838 0.919 1839 0.918 1840 0.777 1841 0.728 1842 0.897 1843 1.133 1844 0.983 1845 1.311 1846 1.264 1847 1.079 1848 1.068 1849 0.997 1850 1.045 1851 1.096 1852 1.138 1853 1.24 1854 1.015 1855 0.999 1856 1.11 1857 0.942 1858 0.815 1859 1.045 1860 0.749 1861 0.877 1862 0.724 1863 0.892 1864 0.932 1865 0.691 1866 0.945 1867 0.947 1868 0.751 1869 0.983 1870 0.789 1871 1.05 1872 0.908 1873 1.117 1874 0.826 1875 0.832 1876 1.084 1877 0.842 1878 0.944 1879 0.931 1880 0.829 1881 1.158 1882 1.26 1883 1.34 1884 1.632 1885 1.521 1886 1.602 1887 1.594 1888 0.979 1889 1.435 1890 1.354 1891 1.122 1892 1.303 1893 1.066 1894 0.886 1895 1.044 1896 1.075 1897 1.031 1898 1.114 1899 1.035 1900 0.917 1901 0.906 1902 1.045 1903 1.098 1904 1.093 1905 1.091 1906 1.061 1907 0.954 1908 1.04 1909 0.824 1910 0.959 1911 1.03 1912 0.911 1913 0.806 1914 1.101 1915 0.895 1916 1.094 1917 0.914 1918 1.147 1919 0.844 1920 0.933 1921 0.64 1922 0.66 1923 0.926 1924 0.821 1925 0.863 1926 1.056 1927 0.902 1928 1.008 1929 0.81 1930 0.822 1931 1.057 1932 1.146 1933 0.906 1934 0.792 1935 0.938 1936 0.953 1937 0.984 1938 1.061 1939 0.961 1940 1.102 1941 1.033 1942 0.831 1943 0.936 1944 0.781 1945 0.867 1946 1.045 1947 0.934 1948 0.89 1949 1.21 1950 0.877 1951 1.044 1952 1.181 1953 0.95 1954 1.065 1955 1.153 1956 0.878 1957 1.097 1958 1.079 1959 1.124 1960 0.844 1961 1.185 1962 1.021 1963 0.846 1964 1.021 1965 0.888 1966 0.968 1967 1.097 1968 0.942 1969 1.084 1970 0.877 1971 0.911 1972 1.012 1973 1.034 1974 0.931 1975 0.836 1976 0.939 1977 0.946 1978 1.085 1979 1.001 1980 0.961