# europe_lith022 - Berzenai - 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/8589 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_lith022 - Berzenai - 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: Berzenai # Location: # Country: Lithuania # Northernmost_Latitude: 55.83 # Southernmost_Latitude: 55.83 # Easternmost_Longitude: 22.82 # Westernmost_Longitude: 22.82 # Elevation: 100 m #-------------------- # Data_Collection # Collection_Name: europe_lith022B # Earliest_Year: 1877 # 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":"4.38597995023","T2":"15.0203553927","M1":"0.0221290447367","M2":"0.286135399982"}} #-------------------- # 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 1877 0.963 1878 0.919 1879 1.163 1880 1.278 1881 0.946 1882 0.845 1883 1.015 1884 1.098 1885 1.003 1886 1.115 1887 0.746 1888 0.94 1889 1.276 1890 1.005 1891 0.879 1892 0.738 1893 0.501 1894 0.636 1895 1.061 1896 0.745 1897 1.063 1898 1.303 1899 0.98 1900 1.055 1901 1.129 1902 1.035 1903 1.221 1904 0.983 1905 0.948 1906 1.006 1907 0.882 1908 1.185 1909 1.123 1910 1.644 1911 1.424 1912 1.121 1913 1.158 1914 0.942 1915 0.828 1916 1.402 1917 1.191 1918 1.381 1919 1.575 1920 0.811 1921 0.802 1922 0.932 1923 0.925 1924 1.219 1925 1.161 1926 0.943 1927 0.516 1928 0.437 1929 0.88 1930 0.804 1931 0.742 1932 0.877 1933 0.595 1934 0.745 1935 0.844 1936 0.887 1937 0.872 1938 0.765 1939 0.696 1940 0.506 1941 0.559 1942 0.773 1943 0.925 1944 1.07 1945 0.793 1946 0.838 1947 0.692 1948 0.476 1949 0.687 1950 0.761 1951 0.983 1952 0.966 1953 1.147 1954 0.749 1955 0.92 1956 0.906 1957 0.854 1958 0.419 1959 0.538 1960 0.687 1961 0.995 1962 1.297 1963 1.799 1964 1.258 1965 1.286 1966 1.449 1967 0.998 1968 0.931 1969 0.653 1970 0.911 1971 0.97 1972 0.944 1973 0.763 1974 0.872 1975 1.155 1976 0.576 1977 0.783 1978 1.059 1979 1.043 1980 1.047 1981 1.243 1982 0.936 1983 1.217 1984 1.247 1985 1.568 1986 1.521 1987 1.355 1988 1.47 1989 0.462 1990 1.044 1991 1.115 1992 0.682 1993 0.75 1994 0.936 1995 0.689 1996 1.233 1997 1.349 1998 0.997 1999 1.35 2000 0.805 2001 1.371 2002 1.054 2003 0.916 2004 0.857 2005 1.217 2006 0.438