# asia_indi019 - Dhanolti - 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/2788 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi019 - Dhanolti - 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: Dhanolti # Location: # Country: India # Northernmost_Latitude: 30.75 # Southernmost_Latitude: 30.75 # Easternmost_Longitude: 78.42 # Westernmost_Longitude: 78.42 # Elevation: 2400 m #-------------------- # Data_Collection # Collection_Name: asia_indi019B # Earliest_Year: 1850 # Most_Recent_Year: 1990 # 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":"2.29331867791","T2":"14.0699984408","M1":"0.022818262798","M2":"0.502792808333"}} #-------------------- # Species # Species_Name: Himalayan spruce # Species_Code: PCSM #-------------------- # 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 1850 1.053 1851 1.062 1852 0.817 1853 0.92 1854 0.875 1855 0.784 1856 1.055 1857 0.819 1858 0.773 1859 1.029 1860 1.095 1861 0.871 1862 0.866 1863 1.077 1864 0.804 1865 1.251 1866 1.274 1867 1.059 1868 1.089 1869 0.85 1870 0.54 1871 0.992 1872 0.842 1873 0.511 1874 0.657 1875 1.141 1876 1.062 1877 0.879 1878 1.085 1879 0.787 1880 1.351 1881 1.122 1882 1.372 1883 1.493 1884 0.969 1885 1.216 1886 1.18 1887 0.684 1888 0.985 1889 1.184 1890 0.702 1891 0.87 1892 0.473 1893 1.183 1894 1.077 1895 0.98 1896 0.822 1897 1.142 1898 1.196 1899 1.284 1900 1.426 1901 1.33 1902 1.226 1903 1.552 1904 1.603 1905 1.846 1906 1.249 1907 1.017 1908 1.062 1909 0.933 1910 1.23 1911 1.091 1912 1.646 1913 1.898 1914 1.734 1915 1.317 1916 1.183 1917 1.434 1918 1.444 1919 1.363 1920 1.046 1921 0.419 1922 0.803 1923 0.848 1924 0.75 1925 1.312 1926 1.632 1927 1.286 1928 1.391 1929 1.441 1930 1.08 1931 0.675 1932 0.336 1933 0.987 1934 0.663 1935 0.936 1936 0.826 1937 0.786 1938 0.746 1939 0.584 1940 0.973 1941 0.595 1942 0.825 1943 0.701 1944 0.73 1945 0.874 1946 0.984 1947 0.799 1948 0.502 1949 0.717 1950 0.982 1951 1.078 1952 0.997 1953 0.622 1954 1.031 1955 1.084 1956 1.177 1957 1.267 1958 0.823 1959 0.792 1960 0.646 1961 0.919 1962 0.924 1963 1.057 1964 0.807 1965 1.01 1966 0.564 1967 0.347 1968 0.634 1969 0.595 1970 0.511 1971 0.997 1972 0.845 1973 0.571 1974 0.311 1975 0.548 1976 0.684 1977 0.79 1978 0.74 1979 0.79 1980 0.753 1981 1.427 1982 1.053 1983 0.97 1984 0.715 1985 0.776 1986 0.864 1987 1.106 1988 1.086 1989 1.253 1990 1.8