# northamerica_usa_az530 - North Slope - 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
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# Title
#	Study_Name: northamerica_usa_az530 - North Slope - 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: North Slope
#	Location:
#	Country: United States
#	Northernmost_Latitude: 32.22
#	Southernmost_Latitude: 32.22
#	Easternmost_Longitude: -110.55
#	Westernmost_Longitude: -110.55
#	Elevation: 2441 m
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# Data_Collection
#	Collection_Name: northamerica_usa_az530B
#	Earliest_Year: 1788
#	Most_Recent_Year: 1987
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"4.92928888523"}{"T2":"17.4635339982"}{"M1":"0.0229943314305"}{"M2":"0.309408598038"}
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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
1788	0.867
1789	0.856
1790	1.073
1791	0.889
1792	1.178
1793	1.34
1794	0.959
1795	1.04
1796	1.2
1797	1.117
1798	0.718
1799	1.205
1800	0.954
1801	0.827
1802	1.018
1803	0.976
1804	1.199
1805	0.949
1806	0.879
1807	1.18
1808	0.989
1809	1.204
1810	1.144
1811	1.18
1812	0.99
1813	1.049
1814	1.139
1815	1.215
1816	1.017
1817	0.644
1818	0.866
1819	0.61
1820	0.804
1821	0.839
1822	0.952
1823	0.816
1824	1.009
1825	1.085
1826	1.573
1827	1.082
1828	1.21
1829	1.299
1830	1.106
1831	1.017
1832	0.942
1833	0.787
1834	0.635
1835	0.785
1836	0.616
1837	0.83
1838	0.906
1839	1.285
1840	0.986
1841	0.954
1842	0.803
1843	1.163
1844	1.139
1845	1.159
1846	1.024
1847	0.709
1848	1.144
1849	0.949
1850	0.951
1851	0.516
1852	0.425
1853	0.638
1854	0.749
1855	0.629
1856	1.04
1857	0.899
1858	1.331
1859	1.072
1860	1.293
1861	1.111
1862	0.885
1863	0.712
1864	0.529
1865	0.656
1866	1.143
1867	0.883
1868	1.168
1869	0.953
1870	0.889
1871	1.054
1872	0.882
1873	1.001
1874	0.985
1875	1.077
1876	1.203
1877	1.032
1878	1.458
1879	1.149
1880	1.115
1881	0.963
1882	1.121
1883	1.05
1884	0.959
1885	0.97
1886	0.662
1887	0.86
1888	1.041
1889	1.276
1890	1.237
1891	0.832
1892	0.602
1893	0.515
1894	0.449
1895	0.553
1896	0.743
1897	0.93
1898	1.627
1899	1.459
1900	1.021
1901	1.408
1902	0.795
1903	1.379
1904	0.837
1905	1.337
1906	1.427
1907	1.534
1908	1.864
1909	1.349
1910	0.975
1911	1.167
1912	0.911
1913	1.471
1914	1.633
1915	1.123
1916	1.334
1917	1.492
1918	1.162
1919	1.318
1920	1.252
1921	1.051
1922	0.993
1923	0.785
1924	0.889
1925	0.784
1926	0.995
1927	1.172
1928	1.312
1929	1.401
1930	1.8
1931	1.574
1932	1.539
1933	1.235
1934	0.657
1935	1.219
1936	0.923
1937	1.245
1938	1.116
1939	1.009
1940	1.448
1941	1.12
1942	0.911
1943	0.624
1944	0.831
1945	0.6
1946	0.533
1947	0.509
1948	0.485
1949	1.079
1950	1.143
1951	0.516
1952	0.82
1953	0.705
1954	0.824
1955	0.423
1956	0.218
1957	0.758
1958	0.857
1959	0.389
1960	0.879
1961	0.293
1962	0.947
1963	1.038
1964	0.864
1965	1.357
1966	1.505
1967	1.419
1968	1.044
1969	1.134
1970	0.912
1971	0.345
1972	0.767
1973	0.772
1974	0.235
1975	1.187
1976	0.869
1977	1.143
1978	0.89
1979	1.035
1980	1.131
1981	0.947
1982	0.546
1983	0.583
1984	1.034
1985	0.39
1986	0.75
1987	0.531