# northamerica_canada_cana133 - Wood Buffalo National Park Site NL - 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/3862
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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_cana133 - Wood Buffalo National Park Site NL - 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
#--------------------
# 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: Wood Buffalo National Park Site NL
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 59.58
#	Southernmost_Latitude: 59.58
#	Easternmost_Longitude: -111.33
#	Westernmost_Longitude: -111.33
#	Elevation: 300 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana133B
#	Earliest_Year: 1856
#	Most_Recent_Year: 1992
#	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":"5.03663556948","T2":"17.0266277754","M1":"0.023042951083","M2":"0.43092388387"}}
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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
1856	1.194
1857	1.153
1858	1.079
1859	0.959
1860	1.02
1861	0.868
1862	0.761
1863	1.001
1864	0.784
1865	0.886
1866	1.113
1867	1.045
1868	0.939
1869	0.99
1870	1.134
1871	1.13
1872	1.13
1873	1.15
1874	0.89
1875	0.948
1876	0.853
1877	0.988
1878	1.189
1879	0.785
1880	1.004
1881	0.998
1882	1.371
1883	1.204
1884	1.153
1885	0.906
1886	0.905
1887	0.956
1888	0.935
1889	1.002
1890	0.954
1891	0.854
1892	0.822
1893	0.796
1894	0.933
1895	0.943
1896	0.919
1897	0.968
1898	0.96
1899	0.974
1900	1.038
1901	1.093
1902	0.933
1903	1.053
1904	1.022
1905	1.022
1906	0.906
1907	0.86
1908	0.826
1909	0.844
1910	1.124
1911	1.06
1912	0.822
1913	0.679
1914	0.663
1915	0.635
1916	0.609
1917	0.825
1918	0.812
1919	1.138
1920	0.916
1921	1.017
1922	1.254
1923	0.979
1924	1.059
1925	1.156
1926	1.134
1927	0.923
1928	0.663
1929	1.104
1930	1.174
1931	1.176
1932	0.966
1933	0.767
1934	0.731
1935	1.004
1936	1.147
1937	1.211
1938	1.078
1939	0.851
1940	0.885
1941	0.793
1942	0.853
1943	0.856
1944	0.817
1945	0.762
1946	1.001
1947	0.919
1948	0.938
1949	1.172
1950	1.022
1951	1.029
1952	0.952
1953	1.013
1954	1.013
1955	1.024
1956	1.269
1957	1.184
1958	0.971
1959	1.177
1960	1.215
1961	0.934
1962	0.952
1963	1.186
1964	1.228
1965	1.305
1966	1.152
1967	1.018
1968	1.145
1969	1.167
1970	1.102
1971	0.851
1972	0.716
1973	0.792
1974	0.981
1975	0.992
1976	1.234
1977	1.19
1978	1.17
1979	1.04
1980	0.827
1981	0.66
1982	0.446
1983	0.65
1984	0.903
1985	0.823
1986	1.037
1987	0.996
1988	1.013
1989	0.857
1990	0.783
1991	0.998
1992	0.801