# northamerica_canada_cana232 - Silverstar - 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/5528
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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: northamerica_canada_cana232 - Silverstar - 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:
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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: Silverstar
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 50.37
#	Southernmost_Latitude: 50.37
#	Easternmost_Longitude: -119.07
#	Westernmost_Longitude: -119.07
#	Elevation: 1700 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana232B
#	Earliest_Year: 1853
#	Most_Recent_Year: 1997
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.91847289761","T2":"19.1521117924","M1":"0.022237382101","M2":"0.202886438724"}}
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# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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
1853	0.902
1854	0.781
1855	0.845
1856	0.796
1857	0.978
1858	0.983
1859	0.995
1860	1.017
1861	0.933
1862	0.938
1863	0.915
1864	1.006
1865	1.111
1866	1.052
1867	0.915
1868	1.009
1869	0.908
1870	0.827
1871	0.874
1872	0.838
1873	0.839
1874	0.95
1875	0.815
1876	0.859
1877	1.069
1878	1.121
1879	1.17
1880	1.116
1881	0.973
1882	1.099
1883	1.036
1884	0.965
1885	1.139
1886	1.121
1887	0.931
1888	1.077
1889	1.024
1890	1.035
1891	1.142
1892	1.014
1893	0.968
1894	0.931
1895	0.977
1896	1.071
1897	1.077
1898	1.198
1899	0.9
1900	1.085
1901	1.144
1902	1.084
1903	1.098
1904	1.131
1905	1.072
1906	0.974
1907	0.933
1908	1.03
1909	0.865
1910	0.989
1911	1.0
1912	1.049
1913	1.12
1914	1.226
1915	1.029
1916	0.926
1917	1.015
1918	1.074
1919	1.147
1920	1.101
1921	0.934
1922	1.067
1923	0.899
1924	0.862
1925	0.988
1926	0.789
1927	0.846
1928	0.893
1929	0.804
1930	0.862
1931	0.918
1932	0.95
1933	0.97
1934	0.947
1935	0.938
1936	1.124
1937	1.026
1938	1.092
1939	0.889
1940	1.067
1941	0.971
1942	0.801
1943	0.936
1944	1.092
1945	0.977
1946	0.737
1947	0.848
1948	0.891
1949	0.88
1950	0.971
1951	0.801
1952	0.963
1953	0.929
1954	0.87
1955	0.956
1956	0.9
1957	0.828
1958	1.067
1959	0.859
1960	1.056
1961	0.938
1962	0.811
1963	1.004
1964	0.879
1965	1.145
1966	1.051
1967	1.111
1968	0.663
1969	0.676
1970	0.774
1971	0.78
1972	0.78
1973	0.963
1974	0.877
1975	1.01
1976	0.953
1977	0.986
1978	0.972
1979	1.007
1980	0.853
1981	0.988
1982	0.981
1983	1.073
1984	1.282
1985	1.263
1986	1.154
1987	1.344
1988	1.256
1989	1.296
1990	1.228
1991	0.764
1992	1.256
1993	0.877
1994	1.216
1995	1.068
1996	1.039
1997	0.859