# northamerica_canada_cana139 - St-Marguerite - 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/3756
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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_cana139 - St-Marguerite - 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: St-Marguerite
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 48.03
#	Southernmost_Latitude: 48.03
#	Easternmost_Longitude: -70.0
#	Westernmost_Longitude: -70.0
#	Elevation: 150 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana139B
#	Earliest_Year: 1871
#	Most_Recent_Year: 1995
#	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":"4.13175258305","T2":"13.4408180214","M1":"0.0230201776219","M2":"0.593389815791"}}
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# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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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
1871	0.925
1872	0.574
1873	1.022
1874	1.076
1875	0.758
1876	0.531
1877	0.594
1878	0.527
1879	1.005
1880	0.709
1881	0.979
1882	1.267
1883	1.213
1884	0.833
1885	1.242
1886	1.472
1887	1.436
1888	1.508
1889	1.473
1890	1.013
1891	0.845
1892	0.981
1893	0.998
1894	0.914
1895	1.004
1896	1.279
1897	1.115
1898	0.973
1899	1.172
1900	1.158
1901	1.198
1902	1.352
1903	1.357
1904	1.257
1905	1.272
1906	0.67
1907	0.851
1908	0.836
1909	0.762
1910	0.947
1911	1.177
1912	0.894
1913	1.284
1914	0.85
1915	0.927
1916	0.717
1917	0.683
1918	0.646
1919	0.626
1920	0.634
1921	0.535
1922	0.706
1923	0.528
1924	0.664
1925	0.831
1926	0.946
1927	0.93
1928	0.886
1929	0.976
1930	1.098
1931	1.379
1932	1.357
1933	1.121
1934	1.11
1935	0.961
1936	0.849
1937	0.962
1938	0.77
1939	1.188
1940	1.129
1941	0.79
1942	0.966
1943	0.835
1944	0.824
1945	1.019
1946	0.912
1947	0.779
1948	1.033
1949	0.945
1950	1.262
1951	1.169
1952	1.216
1953	1.476
1954	1.241
1955	1.077
1956	1.146
1957	1.089
1958	1.211
1959	1.325
1960	1.109
1961	1.41
1962	1.102
1963	1.012
1964	1.305
1965	1.183
1966	1.171
1967	1.14
1968	0.916
1969	0.989
1970	0.958
1971	0.863
1972	0.844
1973	0.803
1974	0.996
1975	1.028
1976	0.708
1977	0.772
1978	0.872
1979	0.937
1980	1.233
1981	0.877
1982	0.958
1983	0.675
1984	1.021
1985	1.051
1986	1.238
1987	1.105
1988	1.227
1989	1.051
1990	0.856
1991	0.71
1992	0.87
1993	0.678
1994	0.753
1995	0.724