# europe_spai035 - Guadarrama Camorca - 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
#--------------------
# Title
#	Study_Name: europe_spai035 - Guadarrama Camorca - 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: Guadarrama Camorca
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 40.82
#	Southernmost_Latitude: 40.82
#	Easternmost_Longitude: -4.05
#	Westernmost_Longitude: -4.05
#	Elevation: 1550 m
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# Data_Collection
#	Collection_Name: europe_spai035B
#	Earliest_Year: 1796
#	Most_Recent_Year: 1983
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.77079327533"}{"T2":"14.7120639851"}{"M1":"0.0224493443818"}{"M2":"0.427843687699"}
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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
1796	0.88
1797	0.772
1798	1.269
1799	0.978
1800	0.38
1801	0.71
1802	0.94
1803	0.806
1804	1.084
1805	0.978
1806	0.497
1807	1.01
1808	0.879
1809	1.205
1810	0.793
1811	1.339
1812	1.575
1813	1.905
1814	1.577
1815	1.472
1816	1.18
1817	1.109
1818	1.238
1819	1.312
1820	1.062
1821	1.204
1822	1.214
1823	0.952
1824	0.971
1825	1.163
1826	0.873
1827	1.035
1828	1.008
1829	0.309
1830	0.876
1831	0.928
1832	1.047
1833	1.003
1834	0.933
1835	0.957
1836	1.293
1837	1.359
1838	1.152
1839	0.942
1840	0.712
1841	0.489
1842	0.605
1843	0.956
1844	0.644
1845	0.623
1846	0.862
1847	0.946
1848	0.87
1849	1.038
1850	1.344
1851	0.826
1852	0.769
1853	0.866
1854	1.234
1855	0.869
1856	0.913
1857	1.032
1858	1.236
1859	1.31
1860	0.815
1861	0.596
1862	0.692
1863	0.777
1864	0.894
1865	0.557
1866	1.057
1867	1.263
1868	1.297
1869	1.455
1870	0.975
1871	0.806
1872	0.771
1873	0.955
1874	0.912
1875	0.818
1876	0.459
1877	0.806
1878	0.592
1879	0.619
1880	0.892
1881	0.789
1882	1.146
1883	1.015
1884	0.965
1885	1.016
1886	1.03
1887	1.035
1888	0.865
1889	0.324
1890	0.809
1891	1.018
1892	0.941
1893	1.091
1894	0.535
1895	0.813
1896	0.705
1897	0.738
1898	0.852
1899	0.887
1900	0.795
1901	0.753
1902	1.133
1903	1.449
1904	1.144
1905	1.103
1906	1.2
1907	1.123
1908	0.769
1909	0.896
1910	1.037
1911	1.158
1912	1.345
1913	1.151
1914	1.551
1915	1.283
1916	1.231
1917	1.051
1918	0.891
1919	0.735
1920	0.601
1921	0.569
1922	0.949
1923	1.307
1924	0.942
1925	1.268
1926	1.22
1927	1.023
1928	0.958
1929	1.126
1930	0.929
1931	0.849
1932	0.581
1933	0.351
1934	0.635
1935	0.85
1936	0.664
1937	0.654
1938	0.616
1939	0.578
1940	0.958
1941	0.891
1942	0.865
1943	1.043
1944	1.397
1945	1.574
1946	1.221
1947	1.232
1948	1.252
1949	0.77
1950	0.577
1951	0.865
1952	0.491
1953	1.005
1954	0.987
1955	1.342
1956	1.145
1957	1.321
1958	1.458
1959	1.391
1960	0.872
1961	1.009
1962	0.767
1963	0.447
1964	0.879
1965	0.792
1966	0.935
1967	1.049
1968	1.181
1969	1.302
1970	1.293
1971	1.045
1972	0.897
1973	1.294
1974	1.059
1975	0.848
1976	0.768
1977	0.951
1978	0.986
1979	0.927
1980	1.215
1981	1.095
1982	1.008
1983	1.079