# southamerica_arge086 - Paso del Viento - 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/5177
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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_arge086 - Paso del Viento - 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 VaganovÃÂ¢ÃÂÃÂ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 4ÃÂ¢ÃÂÃÂ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 modelÃÂ¢ÃÂÃÂ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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#	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 del Viento
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -40.7
#	Southernmost_Latitude: -40.7
#	Easternmost_Longitude: -71.13
#	Westernmost_Longitude: -71.13
#	Elevation: 910 m
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# Data_Collection
#	Collection_Name: southamerica_arge086B
#	Earliest_Year: 1784
#	Most_Recent_Year: 1991
#	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":"1.99113851075","T2":"11.4525097241","M1":"0.022691948828","M2":"0.619399106743"}}
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# Species
#	Species_Name: Chilean cedar
#	Species_Code: AUCH
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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
1784	0.991
1785	0.782
1786	0.623
1787	0.746
1788	1.11
1789	1.066
1790	1.22
1791	1.411
1792	1.111
1793	1.019
1794	1.212
1795	0.994
1796	1.066
1797	0.999
1798	0.912
1799	0.909
1800	1.016
1801	1.02
1802	0.897
1803	1.069
1804	0.996
1805	0.923
1806	0.875
1807	0.857
1808	1.105
1809	1.193
1810	1.088
1811	1.233
1812	1.119
1813	0.313
1814	0.681
1815	1.033
1816	1.027
1817	0.905
1818	0.891
1819	0.775
1820	0.709
1821	0.655
1822	0.903
1823	0.989
1824	1.171
1825	1.417
1826	1.238
1827	0.868
1828	0.932
1829	1.178
1830	1.158
1831	0.956
1832	1.0
1833	1.147
1834	1.259
1835	1.095
1836	0.954
1837	0.949
1838	0.937
1839	0.771
1840	0.822
1841	0.687
1842	0.921
1843	1.305
1844	1.294
1845	0.951
1846	1.079
1847	0.888
1848	1.114
1849	0.871
1850	0.945
1851	0.946
1852	1.272
1853	1.129
1854	1.125
1855	1.103
1856	1.022
1857	1.055
1858	0.912
1859	0.759
1860	0.886
1861	0.863
1862	0.954
1863	1.152
1864	0.914
1865	0.682
1866	0.925
1867	0.819
1868	1.063
1869	0.99
1870	0.971
1871	0.767
1872	1.021
1873	1.018
1874	0.994
1875	0.766
1876	0.978
1877	0.635
1878	0.743
1879	0.776
1880	0.656
1881	0.557
1882	0.641
1883	0.687
1884	0.675
1885	0.59
1886	0.683
1887	0.732
1888	0.811
1889	0.845
1890	0.798
1891	0.739
1892	0.821
1893	0.683
1894	0.669
1895	0.737
1896	0.772
1897	0.712
1898	0.903
1899	0.939
1900	0.954
1901	0.913
1902	0.937
1903	0.807
1904	0.869
1905	1.064
1906	0.965
1907	1.004
1908	0.634
1909	0.67
1910	0.837
1911	0.545
1912	0.733
1913	0.786
1914	0.962
1915	1.214
1916	1.371
1917	1.227
1918	1.468
1919	1.199
1920	1.265
1921	1.313
1922	1.108
1923	0.514
1924	0.62
1925	0.761
1926	1.01
1927	0.901
1928	0.995
1929	1.045
1930	1.045
1931	0.894
1932	1.116
1933	1.361
1934	1.202
1935	1.627
1936	1.449
1937	1.403
1938	1.505
1939	1.619
1940	1.917
1941	1.805
1942	1.52
1943	0.981
1944	1.008
1945	1.99
1946	1.919
1947	1.462
1948	1.225
1949	0.985
1950	0.949
1951	1.258
1952	1.105
1953	0.706
1954	0.743
1955	0.875
1956	0.553
1957	0.675
1958	0.843
1959	0.746
1960	0.718
1961	0.626
1962	0.55
1963	0.836
1964	1.058
1965	1.107
1966	1.069
1967	0.89
1968	1.1
1969	0.916
1970	1.1
1971	0.953
1972	0.935
1973	1.222
1974	1.32
1975	1.29
1976	1.131
1977	1.26
1978	1.059
1979	1.009
1980	1.073
1981	1.005
1982	1.041
1983	1.158
1984	1.352
1985	1.109
1986	1.114
1987	0.824
1988	0.95
1989	0.717
1990	0.671
1991	0.852