# asia_nepa001 - Ghorepanipass Annapurne - 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/4422 # # Description/Documentation lines begin with # # Data lines have no # # # Archive: Tree Rings #-------------------- # Contribution_Date # Date: 2016-01-07 #-------------------- # Title # Study_Name: asia_nepa001 - Ghorepanipass Annapurne - 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: Ghorepanipass Annapurne # Location: # Country: Nepal # Northernmost_Latitude: 28.42 # Southernmost_Latitude: 28.42 # Easternmost_Longitude: 83.75 # Westernmost_Longitude: 83.75 # Elevation: 3220 m #-------------------- # Data_Collection # Collection_Name: asia_nepa001B # Earliest_Year: 1829 # Most_Recent_Year: 1978 # 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":"4.17061369255","T2":"15.1407421466","M1":"0.0229546911771","M2":"0.629940977813"}} #-------------------- # Species # Species_Name: silver fir # Species_Code: ABSB #-------------------- # 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 1829 0.988 1830 0.971 1831 1.124 1832 0.998 1833 0.904 1834 0.519 1835 0.622 1836 0.721 1837 0.904 1838 0.648 1839 0.763 1840 0.84 1841 0.916 1842 0.925 1843 0.801 1844 0.828 1845 0.907 1846 0.981 1847 0.879 1848 0.849 1849 0.701 1850 0.741 1851 0.987 1852 0.913 1853 1.114 1854 1.379 1855 1.66 1856 1.583 1857 0.872 1858 1.058 1859 0.895 1860 1.077 1861 0.794 1862 0.895 1863 0.957 1864 0.987 1865 1.011 1866 0.913 1867 0.987 1868 1.004 1869 0.865 1870 0.91 1871 1.097 1872 0.884 1873 0.914 1874 0.548 1875 0.653 1876 0.976 1877 0.863 1878 0.893 1879 0.692 1880 0.518 1881 0.821 1882 0.931 1883 0.846 1884 0.707 1885 0.859 1886 0.884 1887 0.829 1888 0.927 1889 0.823 1890 0.743 1891 1.085 1892 0.81 1893 0.482 1894 0.988 1895 1.038 1896 1.161 1897 1.169 1898 0.937 1899 1.147 1900 1.32 1901 0.663 1902 0.871 1903 1.253 1904 1.146 1905 1.177 1906 1.001 1907 0.91 1908 1.334 1909 1.078 1910 1.532 1911 1.776 1912 1.167 1913 1.232 1914 1.672 1915 1.643 1916 1.397 1917 1.493 1918 1.727 1919 1.347 1920 0.996 1921 0.826 1922 0.851 1923 0.942 1924 1.737 1925 1.388 1926 1.105 1927 1.064 1928 0.679 1929 1.022 1930 1.482 1931 0.886 1932 0.605 1933 1.16 1934 1.54 1935 1.025 1936 1.087 1937 1.103 1938 0.87 1939 0.901 1940 0.912 1941 1.045 1942 1.323 1943 1.113 1944 0.664 1945 0.562 1946 0.625 1947 0.53 1948 0.479 1949 0.932 1950 1.03 1951 1.168 1952 1.004 1953 0.687 1954 0.834 1955 0.604 1956 0.614 1957 0.935 1958 1.078 1959 0.805 1960 0.44 1961 0.639 1962 0.885 1963 0.682 1964 0.577 1965 0.225 1966 0.447 1967 0.641 1968 0.968 1969 1.284 1970 1.031 1971 0.643 1972 0.848 1973 0.799 1974 0.514 1975 0.602 1976 1.253 1977 1.623 1978 1.099