# southamerica_arge067 - El Arrasayal - 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/5157
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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
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# Title
#	Study_Name: southamerica_arge067 - El Arrasayal - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# Description_and_Notes
#	Description: Data from Breitenmoser 2014 Journal of past Climate supplementary, see publication for ARSTAN standardization details
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# 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:
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#	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: El Arrasayal
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -22.73
#	Southernmost_Latitude: -22.73
#	Easternmost_Longitude: -64.53
#	Westernmost_Longitude: -64.53
#	Elevation: 880 m
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# Data_Collection
#	Collection_Name: southamerica_arge067B
#	Earliest_Year: 1833
#	Most_Recent_Year: 1980
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]"}}{"VSLite_parameters":{"T1":"4.97173078086","T2":"17.9857484115","M1":"0.0222792154423","M2":"0.388994253516"}}
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# Species
#	Species_Name: Argentine walnut
#	Species_Code: JGAU
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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
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age	trsgi
1833	1.048
1834	1.002
1835	0.773
1836	0.842
1837	0.522
1838	1.406
1839	0.629
1840	1.021
1841	0.719
1842	0.858
1843	1.346
1844	1.653
1845	1.114
1846	0.518
1847	2.066
1848	0.39
1849	0.646
1850	1.748
1851	1.455
1852	1.692
1853	1.447
1854	1.53
1855	0.647
1856	0.39
1857	1.519
1858	0.761
1859	0.561
1860	1.443
1861	1.063
1862	0.721
1863	0.17
1864	0.999
1865	0.368
1866	1.027
1867	0.787
1868	0.757
1869	0.488
1870	0.32
1871	1.334
1872	1.639
1873	1.601
1874	1.015
1875	1.353
1876	0.921
1877	0.866
1878	1.045
1879	0.997
1880	0.598
1881	0.512
1882	0.891
1883	1.265
1884	0.578
1885	0.759
1886	0.726
1887	1.245
1888	1.052
1889	0.802
1890	0.781
1891	0.992
1892	0.31
1893	0.517
1894	0.8
1895	0.745
1896	0.444
1897	1.874
1898	0.721
1899	1.218
1900	1.719
1901	1.262
1902	0.988
1903	0.872
1904	1.37
1905	1.384
1906	1.407
1907	1.645
1908	1.496
1909	0.804
1910	0.534
1911	1.063
1912	1.573
1913	1.168
1914	0.802
1915	0.789
1916	0.172
1917	1.035
1918	0.551
1919	1.045
1920	1.384
1921	0.466
1922	0.838
1923	0.835
1924	0.596
1925	0.62
1926	0.87
1927	0.816
1928	1.07
1929	1.136
1930	1.297
1931	1.139
1932	0.622
1933	0.663
1934	0.484
1935	1.268
1936	0.413
1937	0.111
1938	0.766
1939	0.809
1940	0.935
1941	0.9
1942	0.922
1943	1.339
1944	0.485
1945	0.9
1946	0.946
1947	1.09
1948	0.749
1949	1.734
1950	0.624
1951	1.037
1952	1.09
1953	1.199
1954	1.256
1955	0.641
1956	1.299
1957	1.324
1958	0.934
1959	1.091
1960	1.08
1961	1.008
1962	0.57
1963	0.855
1964	1.121
1965	0.676
1966	1.292
1967	1.375
1968	0.936
1969	1.083
1970	0.502
1971	0.903
1972	1.063
1973	0.992
1974	0.919
1975	1.034
1976	0.774
1977	1.017
1978	0.963
1979	0.702
1980	0.843