# europe_germ061 - Laerchenbogen - 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/5270 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_germ061 - Laerchenbogen - 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: Laerchenbogen # Location: # Country: Germany # Northernmost_Latitude: 48.95 # Southernmost_Latitude: 48.95 # Easternmost_Longitude: 11.93 # Westernmost_Longitude: 11.93 # Elevation: 460 m #-------------------- # Data_Collection # Collection_Name: europe_germ061B # Earliest_Year: 1864 # Most_Recent_Year: 1996 # 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":"3.95310205048","T2":"15.5114695486","M1":"0.0229812098175","M2":"0.525948759825"}} #-------------------- # 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 1864 0.885 1865 0.631 1866 0.816 1867 0.843 1868 0.625 1869 0.807 1870 0.625 1871 1.0 1872 0.626 1873 1.053 1874 0.938 1875 0.994 1876 0.929 1877 0.8 1878 0.957 1879 0.949 1880 0.882 1881 1.06 1882 1.07 1883 0.974 1884 0.937 1885 0.825 1886 0.789 1887 0.886 1888 0.99 1889 0.971 1890 1.179 1891 1.166 1892 1.056 1893 0.838 1894 0.826 1895 0.973 1896 0.928 1897 1.118 1898 1.095 1899 0.985 1900 0.958 1901 1.007 1902 0.983 1903 1.048 1904 0.875 1905 0.751 1906 1.067 1907 0.906 1908 0.89 1909 1.014 1910 1.053 1911 0.94 1912 1.068 1913 1.047 1914 1.174 1915 0.914 1916 1.22 1917 0.915 1918 0.929 1919 1.05 1920 1.114 1921 0.684 1922 0.805 1923 0.998 1924 0.968 1925 1.025 1926 1.57 1927 1.584 1928 1.237 1929 0.647 1930 0.904 1931 1.19 1932 1.319 1933 1.285 1934 0.943 1935 1.021 1936 1.123 1937 1.258 1938 1.127 1939 1.127 1940 0.613 1941 0.986 1942 0.856 1943 1.038 1944 1.036 1945 1.093 1946 1.488 1947 1.122 1948 0.876 1949 1.13 1950 0.788 1951 1.004 1952 0.955 1953 1.131 1954 1.247 1955 1.321 1956 0.774 1957 1.117 1958 1.062 1959 1.27 1960 0.765 1961 1.09 1962 0.845 1963 1.027 1964 0.917 1965 0.942 1966 0.823 1967 0.74 1968 0.718 1969 0.816 1970 0.657 1971 0.652 1972 0.6 1973 0.694 1974 0.381 1975 0.444 1976 0.186 1977 0.274 1978 0.45 1979 0.373 1980 0.574 1981 0.511 1982 0.338 1983 0.774 1984 0.843 1985 0.997 1986 0.877 1987 0.921 1988 0.995 1989 1.015 1990 1.301 1991 1.447 1992 1.661 1993 1.421 1994 1.377 1995 1.102 1996 1.055