# northamerica_usa_or050 - Surveyor Flow - 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: northamerica_usa_or050 - Surveyor Flow - 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: Surveyor Flow
#	Location:
#	Country: United States
#	Northernmost_Latitude: 43.62
#	Southernmost_Latitude: 43.62
#	Easternmost_Longitude: -121.3
#	Westernmost_Longitude: -121.3
#	Elevation: 1550 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or050B
#	Earliest_Year: 1809
#	Most_Recent_Year: 1995
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.59833856152"}{"T2":"14.3439488495"}{"M1":"0.0229272882391"}{"M2":"0.524265124166"}
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# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1809	1.144
1810	0.91
1811	1.26
1812	1.143
1813	1.241
1814	1.439
1815	1.175
1816	1.136
1817	1.137
1818	1.397
1819	1.087
1820	1.126
1821	0.875
1822	1.144
1823	0.695
1824	0.798
1825	0.865
1826	1.008
1827	0.912
1828	1.013
1829	0.926
1830	0.756
1831	0.952
1832	1.208
1833	0.961
1834	1.019
1835	0.978
1836	1.098
1837	1.254
1838	1.196
1839	1.211
1840	1.087
1841	1.164
1842	1.069
1843	1.003
1844	0.882
1845	1.136
1846	1.029
1847	0.711
1848	0.97
1849	0.869
1850	0.869
1851	0.902
1852	0.898
1853	0.929
1854	0.968
1855	1.064
1856	0.914
1857	0.944
1858	0.898
1859	0.672
1860	1.031
1861	1.219
1862	1.045
1863	1.163
1864	1.196
1865	1.132
1866	1.251
1867	1.012
1868	1.114
1869	1.039
1870	0.178
1871	0.122
1872	0.141
1873	0.225
1874	0.267
1875	0.593
1876	0.683
1877	0.896
1878	0.939
1879	0.955
1880	0.856
1881	1.042
1882	1.021
1883	1.146
1884	0.956
1885	1.1
1886	1.021
1887	1.035
1888	0.977
1889	0.839
1890	0.579
1891	0.604
1892	0.781
1893	0.829
1894	0.913
1895	0.87
1896	0.736
1897	0.817
1898	0.767
1899	0.726
1900	0.998
1901	1.099
1902	0.966
1903	1.179
1904	1.116
1905	1.074
1906	0.864
1907	1.035
1908	1.076
1909	1.03
1910	1.001
1911	1.005
1912	1.046
1913	1.1
1914	0.998
1915	1.004
1916	0.883
1917	0.909
1918	0.78
1919	0.891
1920	0.671
1921	0.713
1922	0.706
1923	0.846
1924	0.655
1925	0.714
1926	0.672
1927	0.66
1928	0.749
1929	0.596
1930	0.531
1931	0.506
1932	0.631
1933	0.605
1934	0.587
1935	0.549
1936	0.541
1937	0.598
1938	0.702
1939	0.654
1940	0.693
1941	0.69
1942	1.032
1943	1.231
1944	1.371
1945	1.556
1946	1.885
1947	1.86
1948	1.527
1949	1.344
1950	1.396
1951	1.543
1952	1.391
1953	1.346
1954	1.25
1955	1.659
1956	1.393
1957	1.263
1958	1.001
1959	1.104
1960	1.378
1961	1.152
1962	1.091
1963	1.229
1964	1.342
1965	1.301
1966	1.701
1967	1.294
1968	0.984
1969	1.246
1970	1.218
1971	1.021
1972	0.888
1973	0.825
1974	0.884
1975	0.88
1976	1.097
1977	1.056
1978	1.246
1979	1.217
1980	1.166
1981	0.96
1982	1.023
1983	1.023
1984	1.172
1985	1.079
1986	1.199
1987	1.047
1988	1.294
1989	0.771
1990	1.103
1991	0.928
1992	0.61
1993	0.761
1994	0.482
1995	0.504