# southamerica_arge026 - Bahia del Buen Suceso - 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/2770
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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_arge026 - Bahia del Buen Suceso - 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
#--------------------
# 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: Bahia del Buen Suceso
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -54.83
#	Southernmost_Latitude: -54.83
#	Easternmost_Longitude: -65.2
#	Westernmost_Longitude: -65.2
#	Elevation: 35 m
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# Data_Collection
#	Collection_Name: southamerica_arge026B
#	Earliest_Year: 1831
#	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":"5.20750641615","T2":"17.4623229296","M1":"0.0227003943977","M2":"0.382792846842"}}
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# Species
#	Species_Name: coihue de Magallanes
#	Species_Code: NOBE
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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
1831	0.732
1832	0.887
1833	0.858
1834	0.845
1835	0.892
1836	0.72
1837	0.771
1838	0.955
1839	0.594
1840	0.669
1841	0.818
1842	0.874
1843	1.021
1844	1.253
1845	0.84
1846	1.684
1847	1.274
1848	1.335
1849	0.883
1850	1.218
1851	0.941
1852	0.976
1853	0.78
1854	0.999
1855	0.893
1856	0.715
1857	0.949
1858	1.004
1859	1.081
1860	1.135
1861	1.272
1862	1.094
1863	1.479
1864	1.176
1865	1.023
1866	0.978
1867	0.97
1868	1.177
1869	0.831
1870	0.889
1871	0.776
1872	0.99
1873	0.87
1874	0.974
1875	0.856
1876	1.271
1877	0.98
1878	0.735
1879	0.496
1880	0.612
1881	0.579
1882	0.642
1883	0.613
1884	0.708
1885	0.676
1886	0.711
1887	0.731
1888	0.842
1889	0.637
1890	0.869
1891	0.815
1892	0.825
1893	1.158
1894	1.319
1895	1.523
1896	1.001
1897	1.436
1898	1.046
1899	1.022
1900	0.78
1901	0.888
1902	0.613
1903	0.944
1904	0.707
1905	1.032
1906	0.637
1907	0.748
1908	0.646
1909	0.657
1910	0.872
1911	1.096
1912	1.115
1913	1.38
1914	1.302
1915	1.284
1916	1.175
1917	1.174
1918	1.055
1919	1.012
1920	1.069
1921	1.189
1922	1.106
1923	0.878
1924	1.038
1925	0.88
1926	0.931
1927	0.883
1928	1.075
1929	0.868
1930	1.394
1931	0.726
1932	0.881
1933	0.596
1934	0.72
1935	0.892
1936	1.136
1937	1.067
1938	1.098
1939	1.268
1940	1.207
1941	1.237
1942	1.112
1943	0.843
1944	1.245
1945	0.782
1946	0.762
1947	0.641
1948	0.68
1949	0.978
1950	1.038
1951	1.221
1952	0.558
1953	0.699
1954	0.684
1955	0.669
1956	0.804
1957	0.827
1958	0.811
1959	0.859
1960	1.073
1961	1.245
1962	1.139
1963	1.163
1964	1.319
1965	1.208
1966	1.084
1967	1.309
1968	0.933
1969	0.713
1970	0.564
1971	0.881
1972	1.123
1973	0.899
1974	0.925
1975	0.973
1976	0.69
1977	0.919
1978	0.883
1979	1.011
1980	0.943
1981	1.363
1982	0.99
1983	0.826
1984	1.112
1985	1.032
1986	0.857