# europe_lith020 - Degsne - 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/8591 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_lith020 - Degsne - 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: Degsne # Location: # Country: Lithuania # Northernmost_Latitude: 54.57 # Southernmost_Latitude: 54.57 # Easternmost_Longitude: 23.87 # Westernmost_Longitude: 23.87 # Elevation: 90 m #-------------------- # Data_Collection # Collection_Name: europe_lith020B # Earliest_Year: 1857 # Most_Recent_Year: 2006 # 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":"4.58193805582","T2":"15.474870721","M1":"0.0221562819573","M2":"0.49445249759"}} #-------------------- # 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 1857 1.045 1858 0.703 1859 0.856 1860 0.95 1861 1.017 1862 1.395 1863 1.25 1864 1.274 1865 1.153 1866 1.192 1867 0.671 1868 0.358 1869 0.342 1870 0.707 1871 0.919 1872 1.253 1873 1.281 1874 0.956 1875 0.993 1876 1.101 1877 1.142 1878 1.201 1879 1.429 1880 1.171 1881 1.029 1882 0.773 1883 0.848 1884 1.031 1885 0.495 1886 0.811 1887 0.873 1888 0.916 1889 0.806 1890 0.867 1891 1.064 1892 1.124 1893 1.175 1894 1.304 1895 1.483 1896 1.071 1897 0.956 1898 1.063 1899 0.901 1900 0.652 1901 0.856 1902 0.788 1903 0.928 1904 1.123 1905 1.298 1906 1.036 1907 1.205 1908 1.071 1909 1.147 1910 1.389 1911 1.125 1912 0.756 1913 1.203 1914 0.921 1915 0.676 1916 1.114 1917 0.944 1918 1.092 1919 1.064 1920 0.53 1921 0.8 1922 1.23 1923 0.989 1924 0.804 1925 0.997 1926 1.054 1927 0.997 1928 1.091 1929 1.297 1930 1.282 1931 1.409 1932 1.348 1933 1.106 1934 1.257 1935 1.175 1936 1.102 1937 0.814 1938 0.981 1939 0.883 1940 0.783 1941 0.677 1942 0.778 1943 1.012 1944 1.352 1945 1.166 1946 1.289 1947 0.988 1948 1.091 1949 1.053 1950 1.089 1951 1.224 1952 0.986 1953 1.254 1954 0.839 1955 0.673 1956 0.572 1957 0.856 1958 0.824 1959 0.383 1960 0.574 1961 0.798 1962 1.114 1963 1.315 1964 0.722 1965 0.79 1966 0.686 1967 0.476 1968 0.594 1969 0.689 1970 0.886 1971 0.551 1972 0.662 1973 0.753 1974 0.66 1975 0.818 1976 0.705 1977 0.891 1978 1.053 1979 1.032 1980 0.792 1981 1.113 1982 0.976 1983 1.284 1984 1.086 1985 1.309 1986 1.392 1987 1.537 1988 1.448 1989 0.883 1990 1.078 1991 1.029 1992 0.482 1993 0.895 1994 0.735 1995 0.674 1996 0.988 1997 1.045 1998 1.114 1999 1.122 2000 1.26 2001 1.243 2002 0.934 2003 1.067 2004 1.214 2005 1.457 2006 0.826