# southamerica_arge048 - Alto Los Manantiales - 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/4268
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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_arge048 - Alto Los Manantiales - 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: Alto Los Manantiales
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -32.72
#	Southernmost_Latitude: -32.72
#	Easternmost_Longitude: -69.08
#	Westernmost_Longitude: -69.08
#	Elevation: 3100 m
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# Data_Collection
#	Collection_Name: southamerica_arge048B
#	Earliest_Year: 1842
#	Most_Recent_Year: 1983
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"3.57748906175","T2":"16.105758967","M1":"0.022729112094","M2":"0.48035266908"}}
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# Species
#	Species_Name: adesmia horrida
#	Species_Code: ADHO
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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
1842	1.243
1843	1.173
1844	0.799
1845	0.783
1846	1.008
1847	0.468
1848	1.238
1849	0.86
1850	0.835
1851	1.392
1852	1.169
1853	1.171
1854	1.325
1855	0.504
1856	0.866
1857	1.291
1858	0.933
1859	0.808
1860	1.185
1861	1.238
1862	1.016
1863	1.152
1864	0.832
1865	1.056
1866	0.952
1867	0.693
1868	0.867
1869	1.031
1870	0.732
1871	0.847
1872	1.016
1873	0.843
1874	0.847
1875	0.927
1876	0.844
1877	1.022
1878	1.499
1879	0.709
1880	1.137
1881	1.377
1882	1.033
1883	0.53
1884	0.499
1885	0.703
1886	1.148
1887	1.336
1888	0.804
1889	0.769
1890	0.531
1891	1.253
1892	0.997
1893	1.037
1894	1.311
1895	0.788
1896	0.86
1897	0.745
1898	0.587
1899	1.142
1900	0.835
1901	0.969
1902	1.373
1903	1.167
1904	0.875
1905	1.075
1906	0.537
1907	1.053
1908	1.103
1909	1.543
1910	1.21
1911	1.011
1912	0.833
1913	1.085
1914	0.735
1915	0.545
1916	0.725
1917	1.031
1918	0.982
1919	1.128
1920	0.869
1921	0.875
1922	0.788
1923	0.86
1924	0.82
1925	1.043
1926	0.94
1927	0.868
1928	1.027
1929	1.04
1930	1.13
1931	0.798
1932	1.226
1933	0.75
1934	1.194
1935	0.761
1936	0.993
1937	1.199
1938	0.542
1939	1.4
1940	0.636
1941	0.814
1942	1.563
1943	1.479
1944	1.153
1945	1.315
1946	0.831
1947	1.043
1948	1.044
1949	1.02
1950	0.824
1951	0.855
1952	1.292
1953	1.2
1954	0.616
1955	1.295
1956	1.824
1957	1.176
1958	1.65
1959	0.96
1960	0.456
1961	1.015
1962	1.074
1963	1.427
1964	1.026
1965	1.089
1966	0.765
1967	0.747
1968	0.302
1969	0.478
1970	0.645
1971	1.191
1972	1.345
1973	1.301
1974	0.743
1975	1.014
1976	0.586
1977	0.956
1978	1.355
1979	0.868
1980	0.572
1981	0.97
1982	0.702
1983	0.997