# europe_fran002 - Foret de Chinon - 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: europe_fran002 - Foret de Chinon - 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: Foret de Chinon
#	Location:
#	Country: France
#	Northernmost_Latitude: 47.23
#	Southernmost_Latitude: 47.23
#	Easternmost_Longitude: 0.37
#	Westernmost_Longitude: 0.37
#	Elevation: 110 m
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# Data_Collection
#	Collection_Name: europe_fran002B
#	Earliest_Year: 1813
#	Most_Recent_Year: 1979
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.16830778077"}{"T2":"15.7340854796"}{"M1":"0.0231322084077"}{"M2":"0.522111254273"}
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# Species
#	Species_Name: durmast oak
#	Species_Code: QUPE
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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
1813	1.253
1814	1.148
1815	0.778
1816	1.101
1817	0.822
1818	0.55
1819	0.537
1820	0.844
1821	1.094
1822	0.99
1823	1.166
1824	1.344
1825	0.79
1826	0.708
1827	0.833
1828	1.231
1829	1.517
1830	1.283
1831	1.093
1832	0.776
1833	0.835
1834	0.85
1835	0.56
1836	0.845
1837	0.726
1838	1.436
1839	1.207
1840	1.211
1841	1.444
1842	1.091
1843	1.101
1844	0.657
1845	0.689
1846	0.405
1847	0.366
1848	0.728
1849	0.701
1850	0.802
1851	0.714
1852	0.868
1853	1.05
1854	0.802
1855	1.069
1856	0.818
1857	0.689
1858	0.627
1859	0.8
1860	1.088
1861	1.559
1862	1.361
1863	1.047
1864	1.017
1865	1.031
1866	1.244
1867	1.2
1868	1.077
1869	1.137
1870	0.581
1871	1.286
1872	1.094
1873	0.916
1874	0.563
1875	0.741
1876	0.903
1877	0.826
1878	0.897
1879	0.896
1880	0.659
1881	0.764
1882	1.087
1883	1.033
1884	1.038
1885	0.946
1886	1.063
1887	0.775
1888	1.188
1889	0.955
1890	0.907
1891	0.768
1892	0.711
1893	0.619
1894	0.968
1895	1.07
1896	0.901
1897	1.124
1898	0.796
1899	0.869
1900	0.964
1901	0.695
1902	0.823
1903	0.882
1904	1.041
1905	0.907
1906	0.692
1907	0.963
1908	1.219
1909	0.799
1910	1.167
1911	1.022
1912	1.615
1913	1.204
1914	1.192
1915	1.245
1916	1.16
1917	1.374
1918	1.027
1919	0.944
1920	1.203
1921	0.712
1922	0.802
1923	0.869
1924	1.165
1925	1.0
1926	1.302
1927	1.372
1928	1.037
1929	1.156
1930	1.323
1931	1.348
1932	1.251
1933	0.874
1934	0.691
1935	0.722
1936	0.945
1937	0.919
1938	0.973
1939	1.1
1940	1.073
1941	0.899
1942	0.927
1943	0.773
1944	0.754
1945	0.894
1946	0.982
1947	0.784
1948	0.954
1949	0.873
1950	0.962
1951	0.915
1952	0.639
1953	0.993
1954	0.932
1955	0.764
1956	0.736
1957	0.813
1958	0.974
1959	0.677
1960	0.859
1961	0.939
1962	0.901
1963	0.973
1964	0.869
1965	1.051
1966	0.953
1967	1.248
1968	0.908
1969	1.114
1970	1.092
1971	1.291
1972	1.081
1973	1.185
1974	1.084
1975	1.39
1976	0.986
1977	1.028
1978	1.477
1979	1.337