# europe_swit170w - Crete de la Neige, GE - 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/4393 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_swit170w - Crete de la Neige, GE - 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: Crete de la Neige, GE # Location: # Country: Switzerland # Northernmost_Latitude: 46.27 # Southernmost_Latitude: 46.27 # Easternmost_Longitude: 5.93 # Westernmost_Longitude: 5.93 # Elevation: 1700 m #-------------------- # Data_Collection # Collection_Name: europe_swit170wB # Earliest_Year: 1788 # Most_Recent_Year: 1987 # 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":"5.19898935466","T2":"16.678145856","M1":"0.0223448948421","M2":"0.53473097495"}} #-------------------- # Species # Species_Name: krummholz pine # Species_Code: PIMU #-------------------- # 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 1788 1.161 1789 1.101 1790 1.041 1791 1.285 1792 0.984 1793 0.773 1794 1.136 1795 0.994 1796 1.032 1797 0.971 1798 1.248 1799 1.178 1800 1.292 1801 1.038 1802 1.164 1803 0.98 1804 1.004 1805 1.053 1806 1.104 1807 1.293 1808 1.588 1809 1.246 1810 1.123 1811 1.141 1812 1.103 1813 0.768 1814 0.949 1815 0.962 1816 0.728 1817 0.41 1818 0.461 1819 0.581 1820 0.636 1821 0.596 1822 0.896 1823 1.005 1824 0.958 1825 1.116 1826 1.023 1827 0.94 1828 1.178 1829 1.17 1830 0.618 1831 0.976 1832 0.523 1833 0.678 1834 0.954 1835 0.745 1836 0.46 1837 0.714 1838 0.767 1839 0.713 1840 1.069 1841 1.157 1842 1.22 1843 1.048 1844 1.378 1845 1.244 1846 1.265 1847 1.06 1848 1.148 1849 1.097 1850 0.949 1851 0.933 1852 1.12 1853 0.959 1854 0.896 1855 0.747 1856 0.727 1857 0.9 1858 0.896 1859 0.916 1860 0.768 1861 1.047 1862 1.138 1863 0.997 1864 0.911 1865 1.054 1866 1.142 1867 0.954 1868 1.053 1869 1.095 1870 0.718 1871 0.997 1872 1.053 1873 1.067 1874 1.317 1875 1.487 1876 0.963 1877 1.027 1878 0.85 1879 0.898 1880 0.868 1881 1.332 1882 1.286 1883 1.042 1884 1.451 1885 1.331 1886 1.035 1887 1.155 1888 0.758 1889 1.077 1890 0.856 1891 0.837 1892 1.222 1893 1.344 1894 1.089 1895 0.816 1896 1.009 1897 0.918 1898 1.176 1899 1.04 1900 0.845 1901 0.85 1902 0.676 1903 1.257 1904 1.104 1905 1.144 1906 1.051 1907 1.138 1908 1.092 1909 1.073 1910 0.805 1911 0.655 1912 0.708 1913 0.621 1914 0.891 1915 0.857 1916 0.678 1917 0.845 1918 0.731 1919 0.818 1920 0.769 1921 0.948 1922 0.729 1923 0.94 1924 0.816 1925 0.954 1926 0.763 1927 0.751 1928 0.601 1929 0.692 1930 0.827 1931 0.81 1932 0.877 1933 0.858 1934 1.062 1935 0.862 1936 0.883 1937 0.648 1938 0.905 1939 0.902 1940 0.554 1941 0.528 1942 0.853 1943 0.971 1944 1.086 1945 0.483 1946 0.927 1947 0.889 1948 0.737 1949 0.519 1950 0.705 1951 1.079 1952 0.893 1953 0.737 1954 1.108 1955 1.193 1956 0.928 1957 0.851 1958 1.405 1959 1.485 1960 1.182 1961 0.806 1962 0.599 1963 0.702 1964 0.825 1965 1.006 1966 1.097 1967 1.287 1968 1.443 1969 1.556 1970 1.747 1971 1.57 1972 1.404 1973 1.125 1974 1.246 1975 0.984 1976 0.955 1977 1.203 1978 0.97 1979 1.019 1980 0.994 1981 0.967 1982 1.218 1983 1.263 1984 0.931 1985 1.508 1986 1.157 1987 1.389