# europe_fran023 - Roc de Perches Blancas - 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_fran023 - Roc de Perches Blancas - 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: Roc de Perches Blancas
#	Location:
#	Country: France
#	Northernmost_Latitude: 42.6
#	Southernmost_Latitude: 42.6
#	Easternmost_Longitude: 2.05
#	Westernmost_Longitude: 2.05
#	Elevation: 2100 m
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# Data_Collection
#	Collection_Name: europe_fran023B
#	Earliest_Year: 1787
#	Most_Recent_Year: 1977
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"5.59464231677"}{"T2":"19.6558293317"}{"M1":"0.0224913062928"}{"M2":"0.260286860537"}
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# Species
#	Species_Name: krummholz pine
#	Species_Code: PIMU
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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
1787	0.904
1788	1.125
1789	1.028
1790	0.907
1791	0.943
1792	0.813
1793	0.82
1794	0.851
1795	1.044
1796	1.042
1797	0.92
1798	1.061
1799	1.005
1800	0.99
1801	1.031
1802	1.087
1803	0.987
1804	0.989
1805	1.144
1806	0.889
1807	1.279
1808	1.198
1809	0.873
1810	0.828
1811	0.967
1812	1.053
1813	0.889
1814	0.893
1815	0.892
1816	0.827
1817	0.799
1818	1.013
1819	1.056
1820	0.883
1821	0.831
1822	0.831
1823	1.026
1824	0.894
1825	1.163
1826	0.948
1827	0.954
1828	1.272
1829	1.111
1830	0.931
1831	1.208
1832	1.013
1833	0.876
1834	0.881
1835	0.945
1836	0.958
1837	1.108
1838	1.156
1839	0.926
1840	0.967
1841	1.041
1842	0.911
1843	1.093
1844	1.108
1845	0.985
1846	1.216
1847	0.921
1848	0.99
1849	1.002
1850	0.943
1851	0.918
1852	1.062
1853	1.025
1854	0.959
1855	0.78
1856	0.792
1857	0.941
1858	0.846
1859	1.135
1860	0.896
1861	0.96
1862	0.987
1863	1.044
1864	1.247
1865	1.091
1866	0.918
1867	1.067
1868	1.023
1869	1.155
1870	0.927
1871	1.04
1872	0.898
1873	0.945
1874	0.957
1875	1.098
1876	0.996
1877	0.974
1878	1.136
1879	0.834
1880	0.802
1881	0.961
1882	0.868
1883	0.834
1884	1.106
1885	1.238
1886	0.998
1887	1.038
1888	0.883
1889	1.199
1890	1.036
1891	1.037
1892	1.201
1893	1.121
1894	1.032
1895	0.824
1896	0.713
1897	0.853
1898	0.876
1899	0.778
1900	0.739
1901	0.761
1902	0.895
1903	0.925
1904	1.031
1905	0.927
1906	1.019
1907	0.87
1908	0.872
1909	0.773
1910	0.976
1911	1.234
1912	0.815
1913	0.867
1914	0.799
1915	0.968
1916	0.967
1917	1.039
1918	0.959
1919	0.918
1920	1.125
1921	1.097
1922	0.933
1923	1.038
1924	1.104
1925	1.134
1926	0.999
1927	1.061
1928	1.194
1929	1.024
1930	1.117
1931	1.122
1932	1.154
1933	1.17
1934	0.813
1935	1.087
1936	0.953
1937	0.934
1938	0.907
1939	1.082
1940	1.068
1941	0.996
1942	0.893
1943	0.886
1944	0.802
1945	0.772
1946	1.006
1947	1.019
1948	1.027
1949	1.12
1950	1.037
1951	1.0
1952	1.156
1953	1.087
1954	0.958
1955	1.003
1956	0.983
1957	0.704
1958	0.951
1959	0.802
1960	0.738
1961	0.858
1962	0.64
1963	0.551
1964	0.882
1965	0.767
1966	0.921
1967	0.911
1968	1.025
1969	1.205
1970	1.549
1971	1.241
1972	0.964
1973	1.347
1974	1.106
1975	1.014
1976	1.233
1977	1.085