# northamerica_canada_cana132 - Wood Buffalo National Park Site PR - 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/3863
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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_cana132 - Wood Buffalo National Park Site PR - 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:
#--------------------
#	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 PR
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 59.75
#	Southernmost_Latitude: 59.75
#	Easternmost_Longitude: -112.2
#	Westernmost_Longitude: -112.2
#	Elevation: 250 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana132B
#	Earliest_Year: 1863
#	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":"4.97791813889","T2":"17.3226890241","M1":"0.0228437754943","M2":"0.399667265267"}}
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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	0.935
1864	0.896
1865	0.991
1866	1.107
1867	1.026
1868	0.734
1869	0.735
1870	0.871
1871	0.737
1872	0.835
1873	0.677
1874	0.556
1875	0.57
1876	0.612
1877	0.941
1878	1.068
1879	0.813
1880	0.7
1881	0.941
1882	0.991
1883	1.02
1884	1.079
1885	0.876
1886	0.822
1887	1.155
1888	1.26
1889	1.284
1890	1.257
1891	1.002
1892	0.881
1893	1.158
1894	1.268
1895	1.23
1896	1.205
1897	1.143
1898	1.169
1899	1.149
1900	1.244
1901	1.151
1902	0.877
1903	1.08
1904	1.099
1905	1.023
1906	0.803
1907	0.799
1908	0.723
1909	0.842
1910	1.267
1911	1.174
1912	0.957
1913	0.761
1914	0.671
1915	0.748
1916	0.717
1917	0.889
1918	0.86
1919	0.847
1920	0.784
1921	0.816
1922	0.95
1923	0.861
1924	0.923
1925	1.043
1926	1.023
1927	0.86
1928	0.838
1929	1.097
1930	1.185
1931	1.548
1932	1.21
1933	1.045
1934	0.857
1935	1.089
1936	1.045
1937	1.069
1938	1.044
1939	0.853
1940	0.848
1941	0.869
1942	0.878
1943	0.864
1944	0.907
1945	0.984
1946	1.148
1947	0.999
1948	0.793
1949	1.103
1950	0.829
1951	0.943
1952	0.688
1953	0.843
1954	0.985
1955	1.054
1956	1.256
1957	1.123
1958	1.052
1959	1.312
1960	1.376
1961	1.105
1962	1.054
1963	1.302
1964	1.155
1965	1.24
1966	1.141
1967	0.942
1968	0.995
1969	1.081
1970	1.081
1971	0.882
1972	0.763
1973	0.676
1974	0.898
1975	1.003
1976	1.367
1977	1.504
1978	1.236
1979	1.075
1980	0.986
1981	0.844
1982	0.655
1983	0.745
1984	1.084
1985	0.969
1986	0.951
1987	0.902
1988	1.058
1989	0.896
1990	0.872
1991	1.048
1992	0.792