# europe_lith014 - Visakio Ruda - 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/8597 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_lith014 - Visakio Ruda - 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: Visakio Ruda # Location: # Country: Lithuania # Northernmost_Latitude: 54.82 # Southernmost_Latitude: 54.82 # Easternmost_Longitude: 23.43 # Westernmost_Longitude: 23.43 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: europe_lith014B # Earliest_Year: 1868 # Most_Recent_Year: 2006 # 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":"4.02565657621","T2":"19.5737539145","M1":"0.0222832279715","M2":"0.208901300723"}} #-------------------- # Species # Species_Name: European larch # Species_Code: LADE #-------------------- # 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 1868 0.5 1869 0.943 1870 1.049 1871 1.132 1872 0.973 1873 0.877 1874 0.704 1875 0.836 1876 1.077 1877 1.148 1878 1.291 1879 1.133 1880 1.492 1881 1.395 1882 1.21 1883 0.965 1884 0.8 1885 0.438 1886 0.841 1887 1.117 1888 0.661 1889 0.515 1890 0.585 1891 0.734 1892 0.664 1893 0.766 1894 0.728 1895 1.027 1896 0.871 1897 0.979 1898 0.834 1899 0.75 1900 0.754 1901 1.0 1902 0.956 1903 1.425 1904 1.508 1905 1.671 1906 1.342 1907 1.176 1908 1.262 1909 1.266 1910 1.707 1911 1.506 1912 1.347 1913 1.478 1914 1.188 1915 1.262 1916 1.391 1917 1.081 1918 0.98 1919 0.994 1920 0.379 1921 0.719 1922 0.886 1923 0.843 1924 0.58 1925 0.45 1926 0.528 1927 0.547 1928 0.432 1929 0.629 1930 0.634 1931 0.81 1932 0.886 1933 0.676 1934 0.868 1935 1.015 1936 1.081 1937 0.895 1938 0.857 1939 0.836 1940 0.633 1941 0.563 1942 0.708 1943 0.871 1944 0.995 1945 0.752 1946 1.034 1947 0.945 1948 0.897 1949 0.978 1950 0.908 1951 1.044 1952 0.818 1953 0.853 1954 0.683 1955 0.925 1956 0.662 1957 1.11 1958 0.817 1959 0.848 1960 0.83 1961 1.099 1962 0.903 1963 1.146 1964 0.902 1965 0.931 1966 1.033 1967 0.865 1968 0.879 1969 0.979 1970 1.017 1971 0.917 1972 1.127 1973 1.045 1974 0.866 1975 1.199 1976 0.792 1977 1.055 1978 1.15 1979 1.038 1980 1.082 1981 1.303 1982 1.083 1983 1.283 1984 0.945 1985 1.191 1986 1.498 1987 1.246 1988 1.434 1989 1.062 1990 1.418 1991 1.227 1992 0.798 1993 1.147 1994 0.756 1995 0.742 1996 1.034 1997 1.198 1998 0.956 1999 1.048 2000 0.789 2001 0.915 2002 0.828 2003 0.918 2004 0.775 2005 1.066 2006 0.676