# europe_germ003 - Koln Abt. 48 - 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
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: europe_germ003 - Koln Abt. 48 - 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: Koln Abt. 48
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 50.92
#	Southernmost_Latitude: 50.92
#	Easternmost_Longitude: 7.15
#	Westernmost_Longitude: 7.15
#	Elevation: 131 m
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# Data_Collection
#	Collection_Name: europe_germ003B
#	Earliest_Year: 1802
#	Most_Recent_Year: 1971
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"4.82741651484"}{"T2":"19.1879546771"}{"M1":"0.0225735009581"}{"M2":"0.439854703302"}
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# 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)
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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
1802	1.057
1803	0.809
1804	1.194
1805	1.064
1806	1.076
1807	0.941
1808	1.263
1809	1.107
1810	0.94
1811	1.152
1812	1.167
1813	1.145
1814	1.033
1815	1.017
1816	1.193
1817	1.118
1818	1.02
1819	0.915
1820	0.741
1821	0.917
1822	0.884
1823	1.054
1824	1.281
1825	0.828
1826	0.828
1827	1.044
1828	1.123
1829	1.185
1830	1.058
1831	1.027
1832	0.899
1833	0.809
1834	1.119
1835	0.905
1836	0.843
1837	1.009
1838	0.806
1839	0.823
1840	0.94
1841	0.796
1842	0.936
1843	1.001
1844	0.907
1845	0.82
1846	0.813
1847	0.869
1848	1.031
1849	0.929
1850	0.985
1851	0.987
1852	0.891
1853	0.979
1854	0.791
1855	0.841
1856	0.86
1857	0.781
1858	0.582
1859	0.817
1860	1.0
1861	0.962
1862	0.866
1863	0.952
1864	0.942
1865	0.759
1866	0.969
1867	1.169
1868	0.895
1869	0.596
1870	0.557
1871	0.559
1872	0.62
1873	0.839
1874	0.916
1875	1.202
1876	0.938
1877	0.956
1878	1.344
1879	1.238
1880	0.94
1881	1.079
1882	1.264
1883	0.963
1884	1.083
1885	0.969
1886	1.023
1887	1.015
1888	0.781
1889	0.706
1890	0.689
1891	0.733
1892	0.906
1893	0.815
1894	1.085
1895	1.024
1896	0.983
1897	1.072
1898	1.213
1899	0.974
1900	1.097
1901	1.081
1902	1.05
1903	1.289
1904	1.326
1905	1.153
1906	0.748
1907	0.585
1908	0.634
1909	0.422
1910	0.6
1911	0.885
1912	1.28
1913	1.05
1914	1.17
1915	0.957
1916	1.0
1917	1.029
1918	1.218
1919	1.152
1920	1.146
1921	0.82
1922	0.795
1923	0.698
1924	0.703
1925	0.655
1926	0.899
1927	1.142
1928	1.032
1929	0.89
1930	0.996
1931	1.255
1932	1.127
1933	1.086
1934	0.924
1935	1.028
1936	1.205
1937	0.99
1938	0.927
1939	0.662
1940	0.675
1941	0.698
1942	0.628
1943	0.905
1944	0.995
1945	1.204
1946	1.171
1947	0.997
1948	1.226
1949	1.488
1950	1.526
1951	1.43
1952	1.358
1953	1.378
1954	1.307
1955	1.518
1956	0.844
1957	0.913
1958	0.883
1959	0.635
1960	1.029
1961	1.059
1962	1.104
1963	1.031
1964	1.071
1965	0.99
1966	0.998
1967	1.14
1968	0.913
1969	1.184
1970	1.324
1971	1.521