# europe_spai033 - Gredos Hoyos de Espino - 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_spai033 - Gredos Hoyos de Espino - 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: Gredos Hoyos de Espino
#	Location:
#	Country: Spain
#	Northernmost_Latitude: 40.33
#	Southernmost_Latitude: 40.33
#	Easternmost_Longitude: -5.17
#	Westernmost_Longitude: -5.17
#	Elevation: 1465 m
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# Data_Collection
#	Collection_Name: europe_spai033B
#	Earliest_Year: 1837
#	Most_Recent_Year: 1985
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.96442591241"}{"T2":"16.3296133581"}{"M1":"0.0227079471244"}{"M2":"0.462057342839"}
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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
1837	0.852
1838	0.845
1839	0.952
1840	0.744
1841	1.024
1842	0.825
1843	0.879
1844	0.889
1845	0.989
1846	1.0
1847	0.906
1848	1.059
1849	0.876
1850	1.237
1851	0.854
1852	1.018
1853	1.17
1854	1.109
1855	1.023
1856	1.064
1857	1.171
1858	0.941
1859	1.261
1860	0.958
1861	1.183
1862	0.896
1863	0.784
1864	0.685
1865	1.236
1866	1.431
1867	1.505
1868	1.03
1869	0.986
1870	0.86
1871	1.026
1872	1.023
1873	0.929
1874	0.63
1875	0.376
1876	0.372
1877	0.949
1878	1.026
1879	0.894
1880	1.113
1881	1.012
1882	0.644
1883	0.731
1884	0.764
1885	1.206
1886	1.401
1887	1.181
1888	0.993
1889	1.16
1890	0.939
1891	1.1
1892	0.938
1893	1.131
1894	0.734
1895	1.109
1896	1.001
1897	0.773
1898	0.824
1899	0.844
1900	0.772
1901	0.973
1902	1.461
1903	1.704
1904	1.433
1905	1.23
1906	1.08
1907	1.258
1908	1.139
1909	0.939
1910	0.983
1911	1.063
1912	1.133
1913	0.544
1914	1.211
1915	1.162
1916	1.017
1917	1.027
1918	1.097
1919	1.177
1920	1.135
1921	0.801
1922	0.995
1923	1.265
1924	0.797
1925	0.376
1926	0.725
1927	0.741
1928	0.898
1929	0.923
1930	1.023
1931	1.082
1932	0.894
1933	0.876
1934	0.728
1935	0.804
1936	1.153
1937	0.992
1938	0.672
1939	0.925
1940	1.451
1941	1.192
1942	0.932
1943	1.204
1944	1.193
1945	1.004
1946	0.908
1947	1.184
1948	1.385
1949	1.07
1950	0.793
1951	0.077
1952	0.954
1953	0.984
1954	0.848
1955	0.965
1956	1.083
1957	0.958
1958	0.939
1959	1.16
1960	0.96
1961	0.972
1962	1.087
1963	0.891
1964	0.93
1965	0.307
1966	0.774
1967	0.959
1968	0.811
1969	0.868
1970	0.924
1971	1.05
1972	0.885
1973	1.045
1974	1.087
1975	0.775
1976	0.852
1977	1.246
1978	1.364
1979	1.497
1980	1.152
1981	0.714
1982	1.25
1983	1.378
1984	1.119
1985	1.121