# europe_germ018 - Oberer Bannwald B - 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_germ018 - Oberer Bannwald B - 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: Oberer Bannwald B
#	Location:
#	Country: Germany
#	Northernmost_Latitude: 48.57
#	Southernmost_Latitude: 48.57
#	Easternmost_Longitude: 9.08
#	Westernmost_Longitude: 9.08
#	Elevation: 750 m
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# Data_Collection
#	Collection_Name: europe_germ018B
#	Earliest_Year: 1790
#	Most_Recent_Year: 1971
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"4.98696978654"}{"T2":"16.0542282844"}{"M1":"0.022268183659"}{"M2":"0.287729862903"}
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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
1790	1.008
1791	1.002
1792	1.504
1793	1.138
1794	1.215
1795	1.181
1796	1.316
1797	1.286
1798	1.407
1799	1.204
1800	1.249
1801	1.136
1802	1.165
1803	1.148
1804	0.948
1805	0.941
1806	0.943
1807	0.941
1808	1.008
1809	0.89
1810	1.054
1811	0.93
1812	0.687
1813	0.903
1814	1.015
1815	0.737
1816	0.747
1817	0.779
1818	0.917
1819	1.072
1820	0.829
1821	0.903
1822	1.413
1823	1.166
1824	0.993
1825	0.963
1826	0.89
1827	0.798
1828	1.079
1829	1.079
1830	0.971
1831	1.108
1832	0.968
1833	0.986
1834	1.204
1835	0.883
1836	0.942
1837	1.017
1838	0.82
1839	0.73
1840	0.963
1841	1.018
1842	0.944
1843	0.919
1844	0.879
1845	0.692
1846	0.97
1847	0.694
1848	1.195
1849	0.733
1850	0.557
1851	0.792
1852	0.686
1853	1.032
1854	0.67
1855	0.631
1856	0.81
1857	0.735
1858	0.63
1859	0.819
1860	0.801
1861	0.995
1862	1.16
1863	1.09
1864	1.328
1865	1.001
1866	0.926
1867	1.05
1868	0.979
1869	0.901
1870	0.655
1871	0.919
1872	0.737
1873	0.998
1874	1.145
1875	1.153
1876	1.036
1877	0.995
1878	1.1
1879	1.11
1880	0.924
1881	1.28
1882	1.422
1883	1.059
1884	1.287
1885	1.267
1886	0.919
1887	0.732
1888	0.623
1889	0.419
1890	0.876
1891	0.572
1892	0.693
1893	0.846
1894	0.92
1895	1.024
1896	1.026
1897	1.375
1898	1.109
1899	1.107
1900	0.928
1901	1.107
1902	1.14
1903	1.079
1904	1.219
1905	1.325
1906	0.969
1907	1.025
1908	0.937
1909	0.805
1910	0.709
1911	0.626
1912	0.937
1913	0.905
1914	0.914
1915	0.873
1916	0.979
1917	0.617
1918	0.665
1919	0.757
1920	0.918
1921	0.799
1922	0.873
1923	0.805
1924	1.145
1925	1.422
1926	0.746
1927	1.332
1928	1.42
1929	1.177
1930	1.074
1931	0.94
1932	0.883
1933	0.709
1934	0.612
1935	0.55
1936	0.792
1937	0.822
1938	1.075
1939	1.168
1940	0.744
1941	0.687
1942	0.868
1943	1.324
1944	1.233
1945	1.151
1946	1.188
1947	1.345
1948	1.307
1949	1.305
1950	1.401
1951	1.221
1952	1.002
1953	1.184
1954	0.934
1955	1.065
1956	0.951
1957	0.9
1958	1.085
1959	1.268
1960	1.032
1961	1.097
1962	1.019
1963	0.8
1964	0.823
1965	1.321
1966	1.159
1967	1.345
1968	1.162
1969	1.095
1970	1.233
1971	1.648