# asia_indi009 - Pahalgam - 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/4085 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_indi009 - Pahalgam - 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: Pahalgam # Location: # Country: India # Northernmost_Latitude: 34.03 # Southernmost_Latitude: 34.03 # Easternmost_Longitude: 75.7 # Westernmost_Longitude: 75.7 # Elevation: 2900 m #-------------------- # Data_Collection # Collection_Name: asia_indi009B # Earliest_Year: 1848 # Most_Recent_Year: 1982 # 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":"4.81494713604","T2":"13.2336385743","M1":"0.0234204409412","M2":"0.563791354122"}} #-------------------- # 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 1848 0.978 1849 1.054 1850 1.085 1851 1.281 1852 0.841 1853 1.051 1854 0.969 1855 1.291 1856 0.977 1857 1.004 1858 1.088 1859 1.103 1860 1.0 1861 0.825 1862 0.994 1863 0.887 1864 0.828 1865 0.732 1866 0.868 1867 0.875 1868 0.855 1869 0.93 1870 0.889 1871 0.955 1872 0.793 1873 1.353 1874 1.226 1875 0.776 1876 1.19 1877 1.22 1878 1.077 1879 0.638 1880 0.647 1881 0.797 1882 0.836 1883 0.691 1884 0.863 1885 0.775 1886 0.869 1887 0.961 1888 1.137 1889 1.163 1890 1.164 1891 1.214 1892 1.237 1893 1.377 1894 1.46 1895 1.193 1896 1.108 1897 0.899 1898 0.746 1899 0.926 1900 1.084 1901 1.21 1902 1.188 1903 1.25 1904 1.212 1905 0.912 1906 0.822 1907 0.873 1908 0.803 1909 0.946 1910 0.992 1911 0.63 1912 0.856 1913 0.987 1914 1.049 1915 0.704 1916 0.905 1917 0.954 1918 0.769 1919 1.058 1920 0.805 1921 0.61 1922 0.953 1923 0.988 1924 0.962 1925 0.767 1926 0.977 1927 0.816 1928 1.07 1929 1.228 1930 1.348 1931 1.407 1932 1.336 1933 0.888 1934 0.991 1935 0.893 1936 0.91 1937 0.454 1938 0.556 1939 0.615 1940 0.735 1941 0.92 1942 1.234 1943 1.467 1944 1.126 1945 1.029 1946 0.661 1947 0.618 1948 1.128 1949 1.186 1950 0.99 1951 1.074 1952 1.184 1953 0.916 1954 1.049 1955 1.194 1956 0.91 1957 0.945 1958 1.194 1959 1.209 1960 1.175 1961 0.806 1962 0.816 1963 0.757 1964 0.979 1965 1.082 1966 1.128 1967 0.934 1968 0.838 1969 0.931 1970 0.862 1971 0.701 1972 0.922 1973 0.902 1974 1.018 1975 1.092 1976 1.041 1977 1.14 1978 1.122 1979 0.883 1980 1.125 1981 1.177 1982 0.537