# southamerica_arge081 - Pilcaniyeu - Breitenmoser Tree Ring Chronology Data
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#		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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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
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# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/5180
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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: southamerica_arge081 - Pilcaniyeu - Breitenmoser Tree Ring Chronology Data
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# 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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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#	Authors: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G.J., Noone, D., Perkins, W.A., and E. Steig
#	Published_Date_or_Year: 2018
#	Published_Title: Additions to the last millennium reanalysis multi-proxy database
#	Journal_Name: Data Science Journal
#	Volume:
#	Edition:
#	Issue:
#	Pages:
#	Report_Number:
#	DOI:
#	Online_Resource:
#	Full_Citation: Anderson, D.M., Tardif, R., Horlick, K., Erb, M.P., Hakim, G., J., Noone, D., Perkins, W.A., and E. Steig, submitted. Additions to the last millennium reanalysis multi-proxy database. Data Science Journal.
#	Abstract: Progress in paleoclimatology increasingly occurs via data syntheses. We describe additions to a collection prepared for use in paleoclimate state estimation, specifically the Last Millennium Reanalysis (LMR).  The 2290 additional series include 2152 tree ring chronologies and 138 other series.  They supplement the collection used previously and together form a database titled LMRdb 1.0.0. The additional data draws from lake core, ice core, coral, speleothem, and tree ring archives, using published data primarily from the NOAA Paleoclimatology archive and a set of tree ring width chronologies standardized from raw International Tree Ring Data Bank ring width series. In contrast to many previous paleo compilations, the data were not selected (screened) on the basis of their environmental correlation, multi-century length, or other attributes. The inclusion of proxies sensitive to moisture and other environmental variables expands their use in data assimilation.  A preliminary calibration using linear regression with mean annual temperature reveals characteristics of the proxy series and their relationship to temperature, as well as the noise and error characteristics of the records. The additional records are structured as individual files in the NOAA Paleoclimatology format and archived at NOAA Paleoclimatology (Anderson et al. 2018) and will continue to be improved and expanded as part of the LMR Project.  The additions represent a four-fold increase in the number of records available for assimilation, provide expanded geographic coverage, and add additional proxy variables.  Applications include data assimilation, proxy system model development, and paleoclimate reconstruction using climate field reconstruction and other methods.
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# Funding_Agency
#	Funding_Agency_Name: Swiss National Science Foundation
#	Grant:
#--------------------
#	Funding_Agency_Name: National Science Foundation
#	Grant:AGS-1304263
#	Funding_Agency_Name: National Oceanic and Atmospheric Administration
#	Grant:NA14OAR4310176
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# Site_Information
#	Site_Name: Pilcaniyeu
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -41.18
#	Southernmost_Latitude: -41.18
#	Easternmost_Longitude: -70.75
#	Westernmost_Longitude: -70.75
#	Elevation: 1100 m
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# Data_Collection
#	Collection_Name: southamerica_arge081B
#	Earliest_Year: 1804
#	Most_Recent_Year: 1991
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"3.28423798318","T2":"13.7095187262","M1":"0.0231503860888","M2":"0.567882937329"}}
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# Species
#	Species_Name: Chilean cedar
#	Species_Code: AUCH
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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
1804	1.214
1805	0.895
1806	1.019
1807	0.354
1808	0.934
1809	0.803
1810	1.182
1811	1.112
1812	1.062
1813	0.368
1814	0.582
1815	0.939
1816	0.605
1817	1.027
1818	1.243
1819	0.838
1820	0.836
1821	0.84
1822	0.911
1823	1.279
1824	1.075
1825	1.095
1826	1.006
1827	0.635
1828	0.424
1829	0.984
1830	0.504
1831	0.841
1832	1.08
1833	1.131
1834	1.441
1835	0.955
1836	0.691
1837	0.974
1838	1.242
1839	1.159
1840	0.788
1841	0.401
1842	0.551
1843	0.945
1844	1.191
1845	0.829
1846	0.613
1847	0.784
1848	1.193
1849	1.332
1850	0.832
1851	0.898
1852	1.016
1853	0.958
1854	1.09
1855	1.077
1856	1.394
1857	1.308
1858	1.309
1859	0.925
1860	0.609
1861	0.882
1862	0.788
1863	1.201
1864	1.185
1865	0.444
1866	0.598
1867	0.887
1868	1.372
1869	1.907
1870	1.272
1871	1.055
1872	1.401
1873	1.487
1874	1.169
1875	0.926
1876	0.805
1877	0.805
1878	0.686
1879	1.051
1880	1.066
1881	0.688
1882	0.797
1883	1.073
1884	0.896
1885	0.774
1886	0.937
1887	0.983
1888	0.813
1889	0.911
1890	0.754
1891	0.523
1892	0.777
1893	0.528
1894	1.092
1895	0.92
1896	1.051
1897	0.869
1898	0.836
1899	0.785
1900	0.686
1901	0.583
1902	0.363
1903	0.306
1904	0.669
1905	0.413
1906	0.603
1907	0.619
1908	0.442
1909	0.451
1910	0.531
1911	0.696
1912	1.07
1913	0.679
1914	0.476
1915	1.238
1916	1.138
1917	0.64
1918	1.012
1919	0.824
1920	1.209
1921	0.944
1922	0.596
1923	0.249
1924	0.447
1925	0.441
1926	1.051
1927	1.023
1928	1.534
1929	1.222
1930	1.485
1931	1.03
1932	0.644
1933	0.883
1934	0.806
1935	1.041
1936	1.195
1937	1.14
1938	1.373
1939	1.112
1940	1.59
1941	1.77
1942	1.082
1943	0.605
1944	0.617
1945	1.599
1946	1.874
1947	1.333
1948	1.296
1949	1.012
1950	0.746
1951	1.022
1952	1.128
1953	1.008
1954	0.852
1955	1.281
1956	0.879
1957	0.693
1958	0.725
1959	0.633
1960	0.526
1961	0.543
1962	0.4
1963	0.885
1964	1.246
1965	1.337
1966	1.312
1967	0.738
1968	0.618
1969	0.867
1970	1.036
1971	1.067
1972	1.003
1973	1.391
1974	1.6
1975	1.485
1976	1.196
1977	1.283
1978	1.199
1979	1.168
1980	1.375
1981	1.165
1982	1.295
1983	1.292
1984	1.056
1985	0.976
1986	1.11
1987	0.953
1988	0.874
1989	0.606
1990	0.845
1991	1.075