# northamerica_canada_cana286 - APIT - 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/8574
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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_cana286 - APIT - 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: APIT
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 62.48
#	Southernmost_Latitude: 62.48
#	Easternmost_Longitude: -114.37
#	Westernmost_Longitude: -114.37
#	Elevation: 211 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana286B
#	Earliest_Year: 1863
#	Most_Recent_Year: 2005
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.72060336512","T2":"16.770611617","M1":"0.0226922218093","M2":"0.399439248314"}}
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# Species
#	Species_Name: jack pine
#	Species_Code: PIBN
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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
1863	1.014
1864	0.792
1865	0.706
1866	0.909
1867	0.771
1868	0.755
1869	0.838
1870	1.308
1871	1.299
1872	1.329
1873	1.395
1874	1.118
1875	0.727
1876	0.69
1877	0.772
1878	1.127
1879	0.77
1880	1.163
1881	0.856
1882	1.221
1883	0.815
1884	0.797
1885	1.222
1886	0.793
1887	0.959
1888	0.699
1889	0.966
1890	0.674
1891	1.04
1892	1.099
1893	0.711
1894	1.364
1895	0.943
1896	1.274
1897	0.9
1898	1.017
1899	1.139
1900	0.92
1901	0.954
1902	0.817
1903	1.3
1904	0.513
1905	0.714
1906	0.892
1907	1.455
1908	0.882
1909	1.216
1910	1.174
1911	1.129
1912	0.937
1913	1.007
1914	1.061
1915	0.692
1916	0.904
1917	1.103
1918	1.014
1919	1.54
1920	1.206
1921	1.317
1922	1.718
1923	1.111
1924	1.172
1925	0.996
1926	1.128
1927	0.425
1928	0.669
1929	0.957
1930	1.012
1931	1.096
1932	1.581
1933	1.299
1934	1.048
1935	1.044
1936	0.961
1937	0.693
1938	0.641
1939	0.621
1940	0.545
1941	1.066
1942	0.327
1943	0.808
1944	1.118
1945	1.046
1946	0.689
1947	0.77
1948	1.661
1949	1.451
1950	1.143
1951	2.227
1952	0.742
1953	0.92
1954	0.746
1955	0.85
1956	1.094
1957	1.392
1958	0.362
1959	0.448
1960	0.729
1961	0.836
1962	0.862
1963	1.325
1964	0.474
1965	0.806
1966	0.772
1967	0.331
1968	0.544
1969	0.586
1970	0.76
1971	0.601
1972	0.756
1973	0.586
1974	0.829
1975	0.451
1976	1.097
1977	1.121
1978	0.881
1979	0.891
1980	1.256
1981	2.108
1982	0.964
1983	1.086
1984	1.57
1985	1.01
1986	1.045
1987	1.018
1988	1.56
1989	1.344
1990	0.989
1991	1.105
1992	1.178
1993	0.387
1994	0.885
1995	0.496
1996	0.709
1997	0.786
1998	1.052
1999	0.62
2000	1.003
2001	1.272
2002	1.487
2003	1.313
2004	0.789
2005	1.225