# southamerica_chil001 - Alto de las Mesas - 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/3504
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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_chil001 - Alto de las Mesas - 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 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: Alto de las Mesas
#	Location:
#	Country: Chile
#	Northernmost_Latitude: -34.92
#	Southernmost_Latitude: -34.92
#	Easternmost_Longitude: -70.7
#	Westernmost_Longitude: -70.7
#	Elevation: 1020 m
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# Data_Collection
#	Collection_Name: southamerica_chil001B
#	Earliest_Year: 1840
#	Most_Recent_Year: 1975
#	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":"4.78025020943","T2":"16.1208140843","M1":"0.0227457892601","M2":"0.479850946477"}}
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# Species
#	Species_Name: Chilean cedar
#	Species_Code: AUCH
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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
1840	0.719
1841	0.736
1842	0.923
1843	1.135
1844	0.96
1845	0.84
1846	0.939
1847	0.943
1848	1.184
1849	1.167
1850	1.314
1851	1.35
1852	1.192
1853	1.066
1854	1.054
1855	1.459
1856	1.169
1857	1.667
1858	1.356
1859	0.912
1860	1.006
1861	1.087
1862	1.216
1863	1.113
1864	0.974
1865	0.917
1866	0.926
1867	0.94
1868	1.344
1869	1.179
1870	0.993
1871	0.774
1872	0.714
1873	0.769
1874	0.967
1875	1.222
1876	0.931
1877	0.776
1878	0.977
1879	0.809
1880	0.814
1881	1.007
1882	0.802
1883	1.001
1884	1.436
1885	1.319
1886	1.023
1887	1.158
1888	1.039
1889	0.957
1890	0.638
1891	0.863
1892	0.735
1893	0.598
1894	0.733
1895	0.856
1896	0.737
1897	0.746
1898	1.037
1899	0.889
1900	0.786
1901	0.848
1902	0.809
1903	0.918
1904	1.207
1905	1.261
1906	0.934
1907	0.893
1908	0.786
1909	0.768
1910	0.853
1911	0.829
1912	0.963
1913	0.823
1914	0.925
1915	1.118
1916	1.075
1917	0.919
1918	1.186
1919	1.295
1920	1.678
1921	1.23
1922	1.178
1923	1.131
1924	0.69
1925	0.762
1926	0.827
1927	0.935
1928	0.956
1929	0.869
1930	1.102
1931	1.063
1932	1.173
1933	0.731
1934	0.607
1935	0.641
1936	0.781
1937	0.754
1938	1.009
1939	1.061
1940	1.17
1941	1.058
1942	1.419
1943	1.178
1944	1.141
1945	0.987
1946	0.933
1947	0.97
1948	1.011
1949	0.913
1950	1.16
1951	1.073
1952	0.909
1953	0.973
1954	1.102
1955	1.265
1956	1.166
1957	0.845
1958	0.914
1959	0.779
1960	0.825
1961	0.981
1962	0.7
1963	1.142
1964	0.932
1965	1.165
1966	1.372
1967	1.143
1968	0.364
1969	0.922
1970	0.772
1971	1.03
1972	0.789
1973	1.049
1974	0.947
1975	0.949
