# europe_lith017 - Selema - 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/8595 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_lith017 - Selema - 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: Selema # Location: # Country: Lithuania # Northernmost_Latitude: 54.68 # Southernmost_Latitude: 54.68 # Easternmost_Longitude: 23.5 # Westernmost_Longitude: 23.5 # Elevation: 60 m #-------------------- # Data_Collection # Collection_Name: europe_lith017B # Earliest_Year: 1870 # 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":"6.00376277834","T2":"17.4188819321","M1":"0.0217000221456","M2":"0.481539427533"}} #-------------------- # 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 1870 0.963 1871 1.015 1872 1.323 1873 1.099 1874 0.765 1875 0.892 1876 1.162 1877 1.098 1878 0.965 1879 1.267 1880 1.397 1881 1.001 1882 0.912 1883 1.02 1884 1.138 1885 0.573 1886 1.056 1887 0.795 1888 0.512 1889 0.424 1890 0.591 1891 0.698 1892 0.877 1893 0.873 1894 1.286 1895 1.222 1896 0.905 1897 0.785 1898 1.073 1899 0.941 1900 0.862 1901 1.017 1902 1.101 1903 1.284 1904 1.076 1905 1.328 1906 0.951 1907 1.119 1908 1.069 1909 0.863 1910 0.962 1911 0.904 1912 0.697 1913 1.005 1914 0.789 1915 0.811 1916 1.169 1917 0.8 1918 0.948 1919 1.182 1920 1.139 1921 1.192 1922 1.687 1923 1.173 1924 1.556 1925 1.069 1926 1.398 1927 0.762 1928 0.889 1929 1.228 1930 1.151 1931 1.323 1932 1.241 1933 1.038 1934 1.308 1935 1.226 1936 1.444 1937 0.877 1938 0.952 1939 0.831 1940 0.804 1941 0.76 1942 0.973 1943 1.299 1944 1.472 1945 0.849 1946 1.262 1947 1.059 1948 0.991 1949 1.317 1950 1.551 1951 1.354 1952 0.584 1953 0.818 1954 0.365 1955 0.578 1956 0.504 1957 0.624 1958 0.735 1959 0.745 1960 0.704 1961 1.014 1962 1.159 1963 1.437 1964 0.724 1965 0.859 1966 1.03 1967 0.792 1968 1.191 1969 1.246 1970 1.388 1971 0.96 1972 1.048 1973 0.722 1974 0.622 1975 0.691 1976 0.456 1977 0.762 1978 0.724 1979 0.863 1980 0.677 1981 1.125 1982 0.791 1983 1.052 1984 0.68 1985 1.308 1986 1.608 1987 1.203 1988 1.381 1989 0.669 1990 1.19 1991 1.017 1992 0.492 1993 1.162 1994 0.814 1995 0.328 1996 0.776 1997 0.851 1998 0.518 1999 0.93 2000 0.786 2001 0.96 2002 0.661 2003 1.051 2004 1.037 2005 1.662 2006 0.825