# europe_neth026 - Leudal - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: europe_neth026 - Leudal - 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: Leudal
#	Location:
#	Country: Netherlands
#	Northernmost_Latitude: 51.25
#	Southernmost_Latitude: 51.25
#	Easternmost_Longitude: 5.93
#	Westernmost_Longitude: 5.93
#	Elevation: 25 m
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# Data_Collection
#	Collection_Name: europe_neth026B
#	Earliest_Year: 1864
#	Most_Recent_Year: 1986
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"4.70660242053"}{"T2":"16.7299214402"}{"M1":"0.0227807245395"}{"M2":"0.505837285149"}
#--------------------
# Species
#	Species_Name: English oak
#	Species_Code: QURO
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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)
#
##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
1864	0.897
1865	0.803
1866	0.846
1867	0.932
1868	0.865
1869	0.944
1870	1.047
1871	0.929
1872	0.81
1873	0.781
1874	0.845
1875	0.867
1876	0.93
1877	0.952
1878	0.924
1879	0.855
1880	0.658
1881	0.64
1882	0.745
1883	0.917
1884	1.167
1885	1.234
1886	1.256
1887	1.16
1888	1.105
1889	1.064
1890	1.174
1891	1.157
1892	0.956
1893	0.875
1894	0.943
1895	1.028
1896	1.07
1897	1.093
1898	0.864
1899	0.854
1900	0.957
1901	1.053
1902	1.153
1903	1.184
1904	1.049
1905	0.967
1906	0.861
1907	0.879
1908	1.002
1909	0.966
1910	1.067
1911	1.135
1912	1.172
1913	1.194
1914	1.184
1915	1.163
1916	1.122
1917	1.152
1918	1.047
1919	0.929
1920	0.841
1921	0.728
1922	0.908
1923	0.928
1924	1.047
1925	0.971
1926	0.934
1927	1.033
1928	0.815
1929	0.81
1930	0.811
1931	1.047
1932	0.993
1933	0.918
1934	0.875
1935	0.88
1936	1.003
1937	0.897
1938	0.799
1939	0.765
1940	0.755
1941	0.759
1942	0.694
1943	0.881
1944	0.959
1945	1.003
1946	1.074
1947	0.856
1948	0.914
1949	1.112
1950	1.195
1951	1.153
1952	1.254
1953	1.195
1954	1.009
1955	1.11
1956	0.801
1957	0.743
1958	0.753
1959	0.786
1960	0.865
1961	0.993
1962	0.873
1963	0.8
1964	0.817
1965	0.956
1966	0.991
1967	0.975
1968	0.963
1969	1.012
1970	0.967
1971	0.926
1972	0.994
1973	0.962
1974	0.941
1975	1.151
1976	0.882
1977	0.962
1978	1.126
1979	1.226
1980	1.136
1981	1.19
1982	1.261
1983	1.076
1984	0.888
1985	0.96
1986	1.088