# europe_turk015 - Dumali Dag - 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/5128 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: europe_turk015 - Dumali Dag - 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: Dumali Dag # Location: # Country: Turkey # Northernmost_Latitude: 37.4 # Southernmost_Latitude: 37.4 # Easternmost_Longitude: 30.63 # Westernmost_Longitude: 30.63 # Elevation: 1156 m #-------------------- # Data_Collection # Collection_Name: europe_turk015B # Earliest_Year: 1831 # Most_Recent_Year: 2000 # 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":"4.31208378249","T2":"14.9260298327","M1":"0.0221717698438","M2":"0.289404872792"}} #-------------------- # Species # Species_Name: Calabrian pine # Species_Code: PIBR #-------------------- # 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 1831 1.085 1832 1.137 1833 1.126 1834 0.945 1835 1.324 1836 0.843 1837 1.0 1838 1.27 1839 1.008 1840 0.598 1841 1.184 1842 1.029 1843 1.231 1844 0.937 1845 1.074 1846 1.188 1847 1.01 1848 1.524 1849 0.917 1850 1.207 1851 1.007 1852 0.828 1853 0.966 1854 0.756 1855 1.234 1856 0.746 1857 1.155 1858 0.821 1859 1.305 1860 0.808 1861 0.869 1862 0.942 1863 0.704 1864 0.728 1865 0.897 1866 0.929 1867 0.738 1868 1.016 1869 0.776 1870 0.731 1871 0.865 1872 1.209 1873 1.018 1874 0.733 1875 0.809 1876 1.449 1877 1.205 1878 0.947 1879 0.745 1880 0.817 1881 0.907 1882 1.05 1883 1.187 1884 1.219 1885 1.533 1886 1.172 1887 0.826 1888 0.993 1889 1.339 1890 0.878 1891 0.88 1892 0.774 1893 0.59 1894 0.622 1895 0.583 1896 0.801 1897 0.851 1898 0.568 1899 0.541 1900 0.97 1901 1.11 1902 1.06 1903 1.389 1904 1.155 1905 1.04 1906 0.982 1907 0.605 1908 0.569 1909 0.484 1910 0.838 1911 0.718 1912 0.726 1913 1.088 1914 1.368 1915 1.31 1916 0.967 1917 1.005 1918 0.851 1919 1.14 1920 0.814 1921 0.841 1922 1.007 1923 0.859 1924 1.249 1925 1.262 1926 1.228 1927 0.664 1928 0.631 1929 0.839 1930 1.302 1931 1.192 1932 0.734 1933 0.955 1934 1.08 1935 0.68 1936 1.141 1937 0.909 1938 0.814 1939 0.903 1940 1.104 1941 0.768 1942 0.833 1943 1.086 1944 1.072 1945 0.728 1946 0.888 1947 0.812 1948 1.145 1949 0.888 1950 0.879 1951 1.065 1952 1.231 1953 0.774 1954 0.848 1955 1.0 1956 0.818 1957 1.001 1958 1.545 1959 1.142 1960 1.528 1961 0.851 1962 1.02 1963 1.18 1964 0.984 1965 0.916 1966 1.283 1967 0.874 1968 1.239 1969 1.028 1970 1.088 1971 0.951 1972 1.532 1973 0.933 1974 1.11 1975 1.379 1976 1.229 1977 1.113 1978 1.092 1979 1.399 1980 0.838 1981 1.029 1982 1.344 1983 1.08 1984 1.111 1985 0.726 1986 0.958 1987 0.934 1988 0.93 1989 1.005 1990 1.246 1991 1.054 1992 1.231 1993 0.981 1994 0.902 1995 0.995 1996 0.735 1997 0.873 1998 0.808 1999 0.731 2000 0.65