# northamerica_usa_nm500 - El Valle - 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
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_nm500 - El Valle - 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: El Valle
#	Location:
#	Country: United States
#	Northernmost_Latitude: 36.12
#	Southernmost_Latitude: 36.12
#	Easternmost_Longitude: -105.73
#	Westernmost_Longitude: -105.73
#	Elevation: 2316 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm500B
#	Earliest_Year: 1796
#	Most_Recent_Year: 1972
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"sensitivity":"moisture"}{"T1":"3.95462581043"}{"T2":"15.4031840858"}{"M1":"0.0228199240052"}{"M2":"0.520441145632"}
#--------------------
# 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
1796	1.696
1797	1.197
1798	0.849
1799	1.45
1800	1.574
1801	0.603
1802	0.804
1803	0.829
1804	1.156
1805	0.804
1806	0.554
1807	0.884
1808	0.821
1809	0.75
1810	0.963
1811	0.584
1812	1.104
1813	1.293
1814	0.757
1815	1.588
1816	1.729
1817	1.01
1818	0.724
1819	0.202
1820	0.682
1821	0.684
1822	0.356
1823	0.752
1824	0.623
1825	1.127
1826	0.947
1827	1.12
1828	1.382
1829	0.814
1830	0.654
1831	1.055
1832	1.23
1833	1.211
1834	1.233
1835	0.931
1836	0.595
1837	1.199
1838	1.34
1839	1.777
1840	1.432
1841	1.013
1842	0.164
1843	0.386
1844	0.936
1845	0.283
1846	0.272
1847	0.395
1848	0.729
1849	0.989
1850	0.857
1851	0.413
1852	1.096
1853	1.024
1854	1.189
1855	0.879
1856	1.261
1857	0.947
1858	1.268
1859	1.0
1860	0.95
1861	0.052
1862	0.618
1863	0.769
1864	0.511
1865	0.696
1866	1.222
1867	1.178
1868	1.821
1869	1.39
1870	1.163
1871	0.91
1872	1.439
1873	0.141
1874	0.825
1875	0.611
1876	0.654
1877	0.717
1878	1.094
1879	0.795
1880	0.449
1881	1.133
1882	1.004
1883	0.646
1884	1.046
1885	1.188
1886	1.189
1887	1.73
1888	1.599
1889	0.943
1890	1.069
1891	1.325
1892	1.415
1893	0.587
1894	0.529
1895	0.937
1896	0.882
1897	0.834
1898	1.022
1899	0.546
1900	0.687
1901	0.952
1902	0.209
1903	1.135
1904	-0.013
1905	1.231
1906	1.151
1907	1.622
1908	1.272
1909	1.25
1910	0.695
1911	1.224
1912	1.13
1913	0.679
1914	1.471
1915	1.312
1916	1.323
1917	0.542
1918	0.929
1919	1.448
1920	1.441
1921	2.129
1922	0.527
1923	0.693
1924	1.048
1925	0.892
1926	1.152
1927	1.057
1928	0.825
1929	1.84
1930	1.932
1931	1.629
1932	2.744
1933	2.22
1934	1.223
1935	2.117
1936	1.919
1937	1.683
1938	1.401
1939	1.035
1940	1.308
1941	1.606
1942	1.716
1943	1.747
1944	1.505
1945	1.248
1946	0.504
1947	0.587
1948	0.847
1949	1.036
1950	0.548
1951	0.325
1952	0.781
1953	0.57
1954	0.608
1955	0.64
1956	-0.002
1957	0.491
1958	0.595
1959	0.343
1960	0.628
1961	0.624
1962	0.433
1963	0.513
1964	0.434
1965	0.854
1966	0.457
1967	0.541
1968	0.521
1969	0.708
1970	0.607
1971	0.19
1972	0.581