# northamerica_canada_cana043 - Armstrong Eben - 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/4314
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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_cana043 - Armstrong Eben - 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
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# 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: Armstrong Eben
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 50.3
#	Southernmost_Latitude: 50.3
#	Easternmost_Longitude: -89.05
#	Westernmost_Longitude: -89.05
#	Elevation: 1120 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana043B
#	Earliest_Year: 1867
#	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":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.01535188625","T2":"15.9194571102","M1":"0.0228638898603","M2":"0.472250435452"}}
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# Species
#	Species_Name: white spruce
#	Species_Code: PCGL
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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
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age	trsgi
1867	0.953
1868	1.003
1869	1.199
1870	1.061
1871	1.024
1872	1.295
1873	1.007
1874	0.934
1875	1.128
1876	1.069
1877	1.127
1878	1.199
1879	1.021
1880	1.163
1881	1.036
1882	0.937
1883	0.955
1884	1.064
1885	0.945
1886	0.986
1887	0.843
1888	0.772
1889	0.932
1890	0.644
1891	0.871
1892	1.019
1893	0.846
1894	0.705
1895	0.92
1896	0.749
1897	0.787
1898	0.822
1899	0.797
1900	0.849
1901	0.682
1902	0.915
1903	0.973
1904	1.009
1905	1.137
1906	0.837
1907	0.707
1908	0.93
1909	0.786
1910	0.806
1911	1.006
1912	1.024
1913	1.158
1914	0.88
1915	0.929
1916	0.954
1917	1.056
1918	1.287
1919	0.891
1920	0.874
1921	0.877
1922	0.977
1923	0.772
1924	1.194
1925	1.149
1926	1.02
1927	1.111
1928	1.062
1929	0.946
1930	0.981
1931	0.905
1932	0.93
1933	0.975
1934	1.01
1935	1.194
1936	0.927
1937	0.999
1938	1.131
1939	1.181
1940	0.961
1941	1.005
1942	1.196
1943	1.119
1944	1.228
1945	0.832
1946	0.676
1947	0.604
1948	0.705
1949	0.738
1950	0.672
1951	0.994
1952	1.245
1953	1.097
1954	1.002
1955	1.219
1956	0.991
1957	1.457
1958	1.16
1959	1.203
1960	1.003
1961	1.076
1962	0.932
1963	0.973
1964	0.867
1965	1.213
1966	0.992
1967	0.874
1968	1.104
1969	1.07
1970	0.924
1971	1.188
1972	1.194
1973	1.065
1974	0.756
1975	0.921
1976	0.837
1977	1.034
1978	1.053
1979	0.982
1980	1.03
1981	1.016
1982	0.779
1983	0.755
1984	0.729
1985	0.874
1986	0.944
1987	1.061
1988	0.657