# southamerica_arge050 - Paso Cordova Neuquen - 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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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
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# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/4273
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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_arge050 - Paso Cordova Neuquen - 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 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: Paso Cordova Neuquen
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -40.67
#	Southernmost_Latitude: -40.67
#	Easternmost_Longitude: -71.25
#	Westernmost_Longitude: -71.25
#	Elevation: 1890 m
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# Data_Collection
#	Collection_Name: southamerica_arge050B
#	Earliest_Year: 1770
#	Most_Recent_Year: 1986
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"3.58110290559","T2":"13.5224010567","M1":"0.0228518037851","M2":"0.58499975417"}}
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# Species
#	Species_Name: lenga nothofagus
#	Species_Code: NOPU
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# Chronology:
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# Variables
#
# 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
1770	0.825
1771	1.282
1772	1.041
1773	1.192
1774	1.154
1775	1.042
1776	0.994
1777	0.735
1778	0.764
1779	0.809
1780	0.799
1781	1.095
1782	1.114
1783	1.204
1784	0.995
1785	0.816
1786	0.917
1787	0.793
1788	0.542
1789	0.862
1790	0.791
1791	1.031
1792	1.125
1793	0.93
1794	1.093
1795	0.988
1796	1.015
1797	1.134
1798	1.137
1799	1.014
1800	1.004
1801	1.042
1802	1.018
1803	0.937
1804	1.347
1805	1.131
1806	0.961
1807	1.078
1808	0.974
1809	1.13
1810	0.894
1811	0.842
1812	0.893
1813	0.409
1814	0.448
1815	1.061
1816	1.101
1817	0.909
1818	0.794
1819	1.208
1820	0.646
1821	0.472
1822	0.85
1823	0.694
1824	0.868
1825	0.875
1826	0.809
1827	0.899
1828	1.072
1829	0.954
1830	0.908
1831	0.846
1832	0.914
1833	0.664
1834	1.125
1835	1.293
1836	1.491
1837	1.319
1838	1.282
1839	1.35
1840	0.93
1841	0.867
1842	1.024
1843	1.255
1844	0.81
1845	0.46
1846	0.823
1847	0.937
1848	1.118
1849	1.368
1850	0.993
1851	0.647
1852	1.189
1853	1.245
1854	0.679
1855	0.824
1856	1.464
1857	1.198
1858	1.298
1859	1.072
1860	1.023
1861	0.9
1862	1.108
1863	1.359
1864	1.112
1865	1.043
1866	0.993
1867	1.103
1868	1.453
1869	1.064
1870	1.438
1871	0.9
1872	0.772
1873	1.095
1874	0.782
1875	0.927
1876	0.928
1877	0.863
1878	0.92
1879	1.034
1880	1.496
1881	0.74
1882	0.955
1883	1.034
1884	0.932
1885	0.822
1886	1.278
1887	0.858
1888	0.792
1889	1.007
1890	1.23
1891	1.115
1892	1.334
1893	1.405
1894	1.034
1895	1.178
1896	0.682
1897	0.854
1898	1.017
1899	0.789
1900	0.791
1901	1.264
1902	1.154
1903	0.954
1904	0.898
1905	0.923
1906	0.75
1907	0.884
1908	0.573
1909	0.729
1910	1.431
1911	0.494
1912	0.67
1913	0.737
1914	0.587
1915	1.036
1916	0.889
1917	1.035
1918	1.057
1919	0.937
1920	1.101
1921	1.396
1922	1.252
1923	0.679
1924	1.412
1925	1.229
1926	0.71
1927	1.181
1928	1.028
1929	1.018
1930	1.178
1931	1.217
1932	0.889
1933	1.042
1934	1.469
1935	1.132
1936	1.256
1937	1.317
1938	1.592
1939	1.227
1940	1.108
1941	1.122
1942	1.582
1943	0.862
1944	0.754
1945	1.225
1946	1.092
1947	1.193
1948	1.26
1949	1.386
1950	0.894
1951	1.162
1952	1.13
1953	1.142
1954	1.095
1955	1.147
1956	1.097
1957	0.591
1958	1.116
1959	1.134
1960	0.691
1961	0.848
1962	0.902
1963	0.754
1964	1.149
1965	0.885
1966	0.712
1967	1.11
1968	0.545
1969	1.004
1970	0.554
1971	0.707
1972	1.148
1973	0.826
1974	1.104
1975	0.674
1976	0.92
1977	0.604
1978	0.911
1979	0.545
1980	0.582
1981	0.662
1982	0.546
1983	1.053
1984	0.884
1985	0.7
1986	0.428