# asia_indi012 - Kufri - 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/2794 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi012 - Kufri - 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: Kufri # Location: # Country: India # Northernmost_Latitude: 31.12 # Southernmost_Latitude: 31.12 # Easternmost_Longitude: 77.17 # Westernmost_Longitude: 77.17 # Elevation: 2700 m #-------------------- # Data_Collection # Collection_Name: asia_indi012B # Earliest_Year: 1858 # Most_Recent_Year: 1988 # 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":"3.18109147377","T2":"15.180077936","M1":"0.0234267810343","M2":"0.443754226795"}} #-------------------- # Species # Species_Name: deodar cedar # Species_Code: CDDE #-------------------- # 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 1858 0.704 1859 0.958 1860 1.047 1861 0.968 1862 1.123 1863 0.949 1864 0.988 1865 1.011 1866 1.205 1867 0.939 1868 1.086 1869 0.858 1870 0.959 1871 0.726 1872 0.881 1873 0.83 1874 0.966 1875 0.583 1876 0.726 1877 1.1 1878 1.051 1879 0.611 1880 0.776 1881 0.897 1882 0.677 1883 0.735 1884 0.661 1885 0.87 1886 0.95 1887 0.693 1888 0.861 1889 1.047 1890 0.831 1891 0.958 1892 0.604 1893 1.047 1894 1.044 1895 1.15 1896 0.857 1897 1.148 1898 0.865 1899 0.99 1900 1.048 1901 1.11 1902 0.973 1903 1.04 1904 1.247 1905 1.089 1906 1.233 1907 1.391 1908 0.981 1909 1.197 1910 0.945 1911 0.935 1912 1.26 1913 1.405 1914 1.498 1915 1.427 1916 1.018 1917 1.464 1918 1.201 1919 1.187 1920 1.145 1921 0.236 1922 0.913 1923 0.765 1924 0.702 1925 0.868 1926 0.909 1927 0.915 1928 1.12 1929 1.0 1930 1.191 1931 1.126 1932 1.038 1933 1.426 1934 0.966 1935 1.003 1936 1.289 1937 1.398 1938 1.117 1939 1.114 1940 1.111 1941 0.742 1942 0.92 1943 0.907 1944 0.843 1945 0.904 1946 0.914 1947 0.937 1948 0.805 1949 0.972 1950 1.128 1951 0.983 1952 0.953 1953 0.48 1954 0.669 1955 1.058 1956 0.842 1957 1.228 1958 0.684 1959 0.94 1960 0.904 1961 1.067 1962 0.959 1963 1.086 1964 0.952 1965 1.119 1966 0.863 1967 0.697 1968 1.015 1969 0.992 1970 0.858 1971 1.111 1972 0.457 1973 0.933 1974 0.726 1975 0.841 1976 0.852 1977 0.716 1978 0.837 1979 0.949 1980 0.742 1981 1.124 1982 1.292 1983 1.185 1984 0.691 1985 0.567 1986 0.884 1987 0.974 1988 0.838