# northamerica_canada_cana042 - Armstrong - 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/4313
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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_cana042 - Armstrong - 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
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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:
#--------------------
#	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
#	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_cana042B
#	Earliest_Year: 1846
#	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":"3.70404865971","T2":"16.199824182","M1":"0.021972906808","M2":"0.512586930176"}}
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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
#
age	trsgi
1846	0.921
1847	0.895
1848	0.972
1849	0.926
1850	0.948
1851	1.077
1852	1.148
1853	1.147
1854	1.106
1855	1.174
1856	1.233
1857	0.835
1858	0.891
1859	1.087
1860	0.896
1861	1.021
1862	1.04
1863	0.894
1864	0.867
1865	0.814
1866	1.089
1867	0.901
1868	0.803
1869	1.057
1870	1.094
1871	0.954
1872	1.261
1873	1.041
1874	0.858
1875	1.065
1876	0.978
1877	0.893
1878	0.942
1879	0.966
1880	0.987
1881	0.959
1882	1.046
1883	0.938
1884	1.019
1885	1.065
1886	0.999
1887	0.795
1888	1.001
1889	1.12
1890	0.882
1891	1.034
1892	1.04
1893	0.956
1894	0.948
1895	1.127
1896	0.973
1897	1.013
1898	1.146
1899	1.232
1900	1.01
1901	1.151
1902	1.159
1903	1.188
1904	1.139
1905	1.304
1906	0.911
1907	0.914
1908	1.084
1909	0.877
1910	0.916
1911	0.948
1912	0.863
1913	0.997
1914	0.871
1915	0.9
1916	0.951
1917	0.824
1918	1.046
1919	0.83
1920	0.708
1921	0.762
1922	0.641
1923	0.564
1924	0.708
1925	0.874
1926	0.773
1927	1.078
1928	1.012
1929	0.83
1930	0.931
1931	0.941
1932	1.138
1933	1.029
1934	1.064
1935	1.333
1936	0.899
1937	0.965
1938	1.041
1939	1.077
1940	1.071
1941	1.111
1942	1.328
1943	1.412
1944	1.153
1945	0.703
1946	0.713
1947	0.549
1948	0.452
1949	0.468
1950	0.582
1951	0.918
1952	1.079
1953	0.983
1954	0.978
1955	1.141
1956	0.889
1957	1.179
1958	1.104
1959	1.241
1960	1.033
1961	1.196
1962	0.991
1963	0.998
1964	1.011
1965	1.37
1966	1.239
1967	1.07
1968	1.122
1969	1.249
1970	1.133
1971	1.295
1972	1.259
1973	1.186
1974	0.886
1975	1.059
1976	1.059
1977	1.061
1978	1.094
1979	1.123
1980	1.057
1981	1.047
1982	0.704
1983	0.845
1984	0.77
1985	0.888
1986	0.889
1987	0.814
1988	0.674