# asia_leba006 - Maaser - 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/5556 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_leba006 - Maaser - 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: Maaser # Location: # Country: Lebanon # Northernmost_Latitude: 33.67 # Southernmost_Latitude: 33.67 # Easternmost_Longitude: 35.68 # Westernmost_Longitude: 35.68 # Elevation: 1720 m #-------------------- # Data_Collection # Collection_Name: asia_leba006B # Earliest_Year: 1837 # Most_Recent_Year: 2002 # 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":"5.39863015773","T2":"16.6459139344","M1":"0.0224062840504","M2":"0.380735374197"}} #-------------------- # Species # Species_Name: cedar of Lebanone # Species_Code: CDLI #-------------------- # 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 1837 1.154 1838 0.827 1839 0.849 1840 0.347 1841 0.447 1842 0.5 1843 0.747 1844 0.849 1845 0.953 1846 1.188 1847 0.978 1848 0.674 1849 0.229 1850 0.21 1851 0.503 1852 0.654 1853 0.973 1854 0.857 1855 1.131 1856 1.059 1857 1.567 1858 1.84 1859 1.38 1860 1.039 1861 1.313 1862 0.832 1863 0.96 1864 1.441 1865 1.355 1866 1.341 1867 1.375 1868 1.106 1869 1.281 1870 1.395 1871 1.298 1872 0.959 1873 0.477 1874 0.655 1875 1.254 1876 1.444 1877 1.294 1878 1.023 1879 0.836 1880 0.62 1881 0.042 1882 0.263 1883 0.625 1884 0.932 1885 1.196 1886 1.021 1887 1.137 1888 1.323 1889 1.208 1890 1.206 1891 1.406 1892 1.624 1893 1.171 1894 1.129 1895 0.923 1896 0.704 1897 0.672 1898 0.635 1899 0.709 1900 1.073 1901 1.262 1902 1.312 1903 1.002 1904 1.299 1905 0.954 1906 0.999 1907 0.646 1908 0.206 1909 0.297 1910 0.774 1911 1.005 1912 1.249 1913 1.242 1914 1.512 1915 0.977 1916 0.564 1917 1.145 1918 1.202 1919 1.562 1920 1.139 1921 1.14 1922 1.225 1923 1.124 1924 1.403 1925 1.405 1926 1.532 1927 1.231 1928 1.256 1929 1.464 1930 0.876 1931 0.501 1932 0.498 1933 0.878 1934 1.132 1935 0.852 1936 1.083 1937 0.904 1938 1.037 1939 1.032 1940 1.012 1941 0.933 1942 1.076 1943 0.97 1944 0.267 1945 0.034 1946 0.421 1947 0.727 1948 0.798 1949 0.729 1950 0.974 1951 0.448 1952 0.051 1953 0.17 1954 0.314 1955 0.703 1956 0.877 1957 1.003 1958 1.31 1959 1.542 1960 1.265 1961 0.943 1962 0.776 1963 0.733 1964 0.912 1965 0.796 1966 1.162 1967 1.31 1968 1.111 1969 0.963 1970 0.498 1971 0.658 1972 1.29 1973 1.314 1974 1.296 1975 1.196 1976 1.411 1977 1.403 1978 1.023 1979 1.275 1980 1.207 1981 1.528 1982 1.29 1983 1.467 1984 1.208 1985 0.964 1986 1.111 1987 0.952 1988 1.235 1989 0.748 1990 0.968 1991 1.392 1992 1.346 1993 0.663 1994 0.908 1995 0.884 1996 0.886 1997 0.584 1998 0.549 1999 0.496 2000 0.865 2001 1.152 2002 1.426