# southamerica_arge023 - Balmaceda - 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/4269
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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
#--------------------
# Title
#	Study_Name: southamerica_arge023 - Balmaceda - 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: Balmaceda
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -45.92
#	Southernmost_Latitude: -45.92
#	Easternmost_Longitude: -71.75
#	Westernmost_Longitude: -71.75
#	Elevation: 600 m
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# Data_Collection
#	Collection_Name: southamerica_arge023B
#	Earliest_Year: 1830
#	Most_Recent_Year: 1988
#	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":"4.02025698724","T2":"14.0962018423","M1":"0.022925063692","M2":"0.525595452117"}}
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# Species
#	Species_Name: lenga nothofagus
#	Species_Code: NOPU
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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
1830	0.968
1831	0.898
1832	1.225
1833	1.384
1834	1.234
1835	0.936
1836	0.913
1837	1.159
1838	1.28
1839	1.203
1840	0.98
1841	0.885
1842	0.672
1843	0.719
1844	1.149
1845	0.902
1846	0.75
1847	0.961
1848	1.083
1849	1.193
1850	0.796
1851	0.473
1852	0.14
1853	0.716
1854	0.752
1855	0.967
1856	1.054
1857	1.138
1858	1.226
1859	1.33
1860	1.224
1861	0.986
1862	0.437
1863	0.958
1864	0.917
1865	1.389
1866	1.261
1867	1.162
1868	0.932
1869	1.401
1870	1.131
1871	0.99
1872	0.815
1873	0.693
1874	0.531
1875	1.356
1876	1.693
1877	0.774
1878	1.214
1879	0.974
1880	1.371
1881	0.629
1882	0.428
1883	0.55
1884	0.839
1885	0.644
1886	1.006
1887	0.849
1888	0.353
1889	0.642
1890	0.988
1891	1.125
1892	1.166
1893	1.09
1894	1.083
1895	0.914
1896	0.726
1897	1.036
1898	1.275
1899	1.171
1900	0.609
1901	0.658
1902	0.885
1903	0.823
1904	0.502
1905	1.041
1906	1.091
1907	0.982
1908	0.92
1909	1.018
1910	1.639
1911	0.901
1912	0.651
1913	0.62
1914	0.819
1915	0.838
1916	1.058
1917	0.965
1918	0.851
1919	0.616
1920	0.769
1921	0.881
1922	0.688
1923	0.709
1924	1.182
1925	1.483
1926	0.898
1927	0.963
1928	1.374
1929	0.923
1930	0.961
1931	1.213
1932	1.081
1933	1.161
1934	1.348
1935	0.724
1936	1.233
1937	1.062
1938	0.566
1939	0.692
1940	1.305
1941	0.749
1942	1.175
1943	0.913
1944	0.849
1945	1.322
1946	0.981
1947	1.047
1948	0.682
1949	0.407
1950	0.737
1951	1.235
1952	0.973
1953	0.817
1954	1.077
1955	1.202
1956	1.381
1957	0.968
1958	1.188
1959	1.306
1960	0.721
1961	0.716
1962	1.343
1963	1.461
1964	2.019
1965	1.186
1966	0.948
1967	1.399
1968	1.128
1969	1.207
1970	1.002
1971	0.987
1972	1.245
1973	0.514
1974	0.309
1975	0.273
1976	0.895
1977	0.97
1978	0.986
1979	0.969
1980	0.933
1981	0.943
1982	1.075
1983	0.893
1984	0.874
1985	1.084
1986	0.978
1987	0.768
1988	0.626