# asia_russ155w - Under Vangapur River A - Breitenmoser Tree Ring Chronology Data
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#		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.
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# Online_Resource:
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# Original_Source_URL:
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
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# Title
#	Study_Name: asia_russ155w - Under Vangapur River A - 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.
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# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
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# Site_Information
#	Site_Name: Under Vangapur River A
#	Location:
#	Country: Russia
#	Northernmost_Latitude: 62.93
#	Southernmost_Latitude: 62.93
#	Easternmost_Longitude: 76.38
#	Westernmost_Longitude: 76.38
#	Elevation: 180 m
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# Data_Collection
#	Collection_Name: asia_russ155wB
#	Earliest_Year: 1802
#	Most_Recent_Year: 1994
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"5.64621858511"}{"T2":"19.8653754923"}{"M1":"0.0223386209769"}{"M2":"0.267640461298"}
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# Species
#	Species_Name: Scots pine
#	Species_Code: PISY
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# Chronology:
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# Variables
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# 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)
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##age	age, , ,years AD, , , , ,N
##trsgi	tree ring standardized growth index, tree ring, ,percent relative to mean growth, , Tree Rings, , ,N
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# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1802	0.711
1803	0.963
1804	1.129
1805	0.905
1806	1.019
1807	1.324
1808	1.328
1809	1.29
1810	0.966
1811	0.937
1812	1.084
1813	0.905
1814	1.098
1815	1.0
1816	0.559
1817	0.742
1818	0.703
1819	0.458
1820	0.791
1821	0.888
1822	1.006
1823	0.982
1824	1.412
1825	1.083
1826	0.88
1827	1.168
1828	0.755
1829	0.969
1830	1.204
1831	0.949
1832	1.196
1833	0.993
1834	0.752
1835	0.906
1836	0.778
1837	0.783
1838	0.965
1839	0.957
1840	1.284
1841	0.931
1842	0.944
1843	1.157
1844	1.151
1845	1.195
1846	1.065
1847	1.088
1848	1.34
1849	1.375
1850	1.201
1851	0.758
1852	0.963
1853	1.178
1854	1.166
1855	1.103
1856	1.194
1857	1.126
1858	1.197
1859	1.318
1860	1.223
1861	1.343
1862	0.733
1863	0.938
1864	1.086
1865	0.918
1866	1.094
1867	0.906
1868	1.222
1869	1.181
1870	0.903
1871	1.243
1872	0.989
1873	0.617
1874	0.779
1875	0.743
1876	0.801
1877	0.661
1878	0.758
1879	0.924
1880	1.014
1881	0.756
1882	0.489
1883	0.542
1884	0.606
1885	0.512
1886	0.919
1887	0.721
1888	0.759
1889	0.726
1890	0.571
1891	0.671
1892	0.698
1893	1.058
1894	0.992
1895	1.152
1896	1.06
1897	1.011
1898	0.954
1899	0.898
1900	1.314
1901	1.295
1902	0.798
1903	0.606
1904	0.733
1905	0.901
1906	0.854
1907	0.932
1908	1.114
1909	1.465
1910	1.081
1911	1.276
1912	1.093
1913	0.852
1914	0.622
1915	0.848
1916	0.659
1917	0.778
1918	1.154
1919	0.918
1920	0.77
1921	1.066
1922	1.122
1923	0.934
1924	1.076
1925	1.021
1926	0.793
1927	0.654
1928	0.861
1929	1.11
1930	1.045
1931	1.017
1932	1.058
1933	1.049
1934	0.596
1935	0.641
1936	0.755
1937	0.742
1938	0.92
1939	1.073
1940	0.997
1941	0.614
1942	0.958
1943	1.122
1944	1.178
1945	1.177
1946	1.074
1947	0.641
1948	1.404
1949	0.849
1950	0.728
1951	0.834
1952	0.93
1953	0.608
1954	0.59
1955	0.758
1956	1.012
1957	1.055
1958	1.059
1959	1.089
1960	0.821
1961	0.88
1962	1.151
1963	1.285
1964	1.245
1965	1.275
1966	1.452
1967	1.425
1968	1.681
1969	1.193
1970	1.313
1971	1.152
1972	1.068
1973	0.636
1974	1.003
1975	1.077
1976	1.312
1977	1.176
1978	1.38
1979	1.265
1980	1.095
1981	0.792
1982	1.211
1983	0.924
1984	1.042
1985	1.022
1986	1.111
1987	1.023
1988	1.333
1989	1.321
1990	1.168
1991	0.847
1992	1.112
1993	1.046
1994	1.264