# australia_newz085 - Huia - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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: australia_newz085 - Huia - 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: Huia
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -36.97
#	Southernmost_Latitude: -36.97
#	Easternmost_Longitude: 174.57
#	Westernmost_Longitude: 174.57
#	Elevation: 300 m
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# Data_Collection
#	Collection_Name: australia_newz085B
#	Earliest_Year: 1800
#	Most_Recent_Year: 1981
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"temperature"}{"T1":"4.80069434893"}{"T2":"18.7416186337"}{"M1":"0.0221825350898"}{"M2":"0.513271427643"}
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# Species
#	Species_Name: kauri pine
#	Species_Code: AGAU
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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
1800	0.579
1801	0.675
1802	0.871
1803	1.138
1804	0.973
1805	0.541
1806	1.303
1807	1.104
1808	0.78
1809	1.22
1810	0.989
1811	1.286
1812	1.277
1813	1.208
1814	1.009
1815	1.272
1816	1.48
1817	1.171
1818	1.171
1819	1.09
1820	1.164
1821	0.838
1822	1.144
1823	1.006
1824	1.251
1825	0.745
1826	1.389
1827	1.248
1828	0.811
1829	1.113
1830	0.772
1831	1.41
1832	1.058
1833	1.263
1834	0.568
1835	0.677
1836	0.559
1837	1.231
1838	1.232
1839	0.423
1840	1.175
1841	1.024
1842	0.89
1843	1.139
1844	0.7
1845	1.265
1846	0.547
1847	1.239
1848	1.161
1849	0.926
1850	1.241
1851	1.053
1852	1.555
1853	1.443
1854	0.925
1855	1.229
1856	0.772
1857	1.221
1858	0.862
1859	1.228
1860	0.63
1861	0.941
1862	0.847
1863	0.656
1864	0.952
1865	0.609
1866	0.609
1867	0.768
1868	1.376
1869	1.111
1870	1.334
1871	0.908
1872	0.501
1873	1.189
1874	1.204
1875	0.56
1876	1.013
1877	1.228
1878	0.472
1879	0.905
1880	0.692
1881	1.284
1882	0.995
1883	0.687
1884	1.318
1885	0.853
1886	0.361
1887	0.803
1888	0.57
1889	0.42
1890	0.505
1891	1.29
1892	0.505
1893	1.572
1894	0.825
1895	1.051
1896	0.921
1897	0.452
1898	0.75
1899	0.982
1900	1.051
1901	0.94
1902	1.074
1903	0.583
1904	1.297
1905	0.861
1906	0.61
1907	0.444
1908	0.459
1909	0.719
1910	0.49
1911	1.036
1912	0.392
1913	0.993
1914	0.681
1915	0.338
1916	0.327
1917	1.709
1918	1.48
1919	1.51
1920	0.744
1921	0.847
1922	0.675
1923	1.048
1924	0.859
1925	0.979
1926	0.554
1927	1.093
1928	0.286
1929	0.508
1930	0.749
1931	0.818
1932	0.624
1933	1.059
1934	0.609
1935	0.413
1936	0.641
1937	1.021
1938	0.791
1939	0.697
1940	1.265
1941	0.741
1942	1.394
1943	0.861
1944	1.265
1945	1.03
1946	0.711
1947	0.876
1948	0.376
1949	1.085
1950	0.339
1951	1.157
1952	0.628
1953	0.99
1954	1.281
1955	1.09
1956	1.294
1957	1.634
1958	1.029
1959	1.68
1960	1.035
1961	1.454
1962	1.148
1963	2.1
1964	1.019
1965	1.064
1966	1.171
1967	1.713
1968	1.079
1969	0.879
1970	0.654
1971	0.892
1972	0.54
1973	0.559
1974	0.889
1975	0.81
1976	1.397
1977	1.01
1978	1.243
1979	0.681
1980	1.096
1981	0.987