# northamerica_canada_cana130 - Wood Buffalo National Park Site RL - 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/3864
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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_cana130 - Wood Buffalo National Park Site RL - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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 RL
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 59.8
#	Southernmost_Latitude: 59.8
#	Easternmost_Longitude: -112.17
#	Westernmost_Longitude: -112.17
#	Elevation: 240 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana130B
#	Earliest_Year: 1860
#	Most_Recent_Year: 1989
#	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":"4.65309609019","T2":"17.0373005425","M1":"0.0232144940036","M2":"0.464405020969"}}
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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
1860	0.864
1861	0.764
1862	0.697
1863	0.809
1864	0.756
1865	0.794
1866	0.596
1867	0.689
1868	0.654
1869	0.613
1870	0.829
1871	0.92
1872	0.787
1873	0.821
1874	0.804
1875	0.808
1876	0.733
1877	0.699
1878	0.806
1879	0.807
1880	0.99
1881	1.126
1882	0.983
1883	0.969
1884	0.917
1885	0.827
1886	0.889
1887	0.874
1888	0.998
1889	1.09
1890	1.155
1891	1.168
1892	1.101
1893	1.08
1894	1.067
1895	1.215
1896	1.271
1897	1.342
1898	1.39
1899	1.551
1900	1.398
1901	1.386
1902	1.03
1903	1.136
1904	1.015
1905	0.989
1906	0.934
1907	0.942
1908	1.001
1909	0.88
1910	1.185
1911	1.119
1912	1.051
1913	0.978
1914	1.122
1915	0.925
1916	1.019
1917	0.953
1918	1.074
1919	1.174
1920	1.015
1921	1.27
1922	1.279
1923	1.172
1924	1.001
1925	1.104
1926	0.98
1927	1.001
1928	0.765
1929	1.004
1930	1.249
1931	1.177
1932	1.19
1933	1.084
1934	1.158
1935	1.14
1936	1.04
1937	1.208
1938	1.136
1939	0.954
1940	0.866
1941	0.739
1942	0.685
1943	0.626
1944	0.587
1945	0.66
1946	0.821
1947	0.839
1948	0.828
1949	0.898
1950	0.726
1951	0.793
1952	0.735
1953	0.906
1954	0.801
1955	1.006
1956	1.431
1957	1.259
1958	1.209
1959	1.054
1960	1.269
1961	1.021
1962	1.32
1963	1.496
1964	1.133
1965	1.323
1966	1.227
1967	1.116
1968	0.945
1969	0.722
1970	0.632
1971	0.827
1972	0.662
1973	0.54
1974	0.618
1975	0.676
1976	0.691
1977	0.789
1978	0.84
1979	0.692
1980	0.621
1981	0.726
1982	0.517
1983	0.651
1984	1.066
1985	1.087
1986	1.348
1987	1.243
1988	1.303
1989	1.305