# asia_leba002 - Wadi Balat - 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/5560 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_leba002 - Wadi Balat - 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: Wadi Balat # Location: # Country: Lebanon # Northernmost_Latitude: 34.47 # Southernmost_Latitude: 34.47 # Easternmost_Longitude: 36.23 # Westernmost_Longitude: 36.23 # Elevation: 1175 m #-------------------- # Data_Collection # Collection_Name: asia_leba002B # Earliest_Year: 1860 # Most_Recent_Year: 2001 # 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":"6.44605916919","T2":"15.0370983257","M1":"0.0223046049713","M2":"0.526152977542"}} #-------------------- # Species # Species_Name: Cilician fir # Species_Code: ABCI #-------------------- # 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 1860 0.622 1861 0.905 1862 0.905 1863 0.971 1864 1.074 1865 0.995 1866 0.767 1867 0.377 1868 0.81 1869 0.884 1870 0.927 1871 1.225 1872 1.256 1873 1.014 1874 1.375 1875 1.316 1876 1.112 1877 1.05 1878 1.503 1879 1.159 1880 1.404 1881 1.1 1882 1.025 1883 1.103 1884 1.009 1885 1.428 1886 0.52 1887 0.562 1888 0.613 1889 0.78 1890 0.779 1891 0.608 1892 0.659 1893 0.918 1894 0.935 1895 0.907 1896 0.824 1897 0.523 1898 0.524 1899 0.393 1900 0.707 1901 0.531 1902 0.611 1903 0.817 1904 1.147 1905 1.287 1906 1.141 1907 1.416 1908 1.267 1909 0.858 1910 0.718 1911 1.288 1912 0.66 1913 0.709 1914 0.826 1915 0.763 1916 0.443 1917 0.61 1918 0.747 1919 0.837 1920 1.114 1921 0.979 1922 0.808 1923 0.729 1924 0.9 1925 0.798 1926 0.742 1927 0.977 1928 0.593 1929 0.93 1930 0.763 1931 0.951 1932 0.771 1933 0.76 1934 1.152 1935 0.77 1936 1.189 1937 0.978 1938 0.949 1939 0.929 1940 0.889 1941 0.705 1942 0.904 1943 1.06 1944 1.137 1945 1.271 1946 1.233 1947 1.236 1948 1.2 1949 1.343 1950 1.759 1951 1.517 1952 1.394 1953 1.472 1954 1.292 1955 0.974 1956 1.266 1957 1.078 1958 0.717 1959 0.647 1960 0.731 1961 0.616 1962 0.685 1963 0.723 1964 0.886 1965 0.732 1966 0.882 1967 1.069 1968 1.193 1969 0.959 1970 1.036 1971 1.059 1972 1.098 1973 0.959 1974 1.054 1975 1.068 1976 1.227 1977 1.042 1978 1.015 1979 1.127 1980 1.048 1981 1.222 1982 1.375 1983 1.476 1984 1.1 1985 1.181 1986 0.939 1987 1.05 1988 0.855 1989 0.765 1990 0.762 1991 0.87 1992 1.253 1993 1.206 1994 1.255 1995 0.928 1996 0.763 1997 0.854 1998 0.909 1999 0.56 2000 0.876 2001 0.692