# northamerica_canada_cana236 - Grey Creek - 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/5515
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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_cana236 - Grey Creek - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
#--------------------
# 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: Grey Creek
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.62
#	Southernmost_Latitude: 49.62
#	Easternmost_Longitude: -116.65
#	Westernmost_Longitude: -116.65
#	Elevation: 2000 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana236B
#	Earliest_Year: 1860
#	Most_Recent_Year: 1997
#	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":"5.06638327117","T2":"17.6888281953","M1":"0.0228330136039","M2":"0.387779363331"}}
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# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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	0.816
1861	0.97
1862	0.95
1863	1.096
1864	0.734
1865	1.055
1866	0.739
1867	0.515
1868	0.685
1869	0.724
1870	0.642
1871	0.974
1872	0.878
1873	0.877
1874	0.863
1875	0.862
1876	0.675
1877	0.897
1878	0.984
1879	0.779
1880	0.654
1881	0.653
1882	0.869
1883	0.855
1884	0.699
1885	1.012
1886	1.104
1887	0.706
1888	0.878
1889	1.031
1890	0.962
1891	0.984
1892	1.072
1893	0.977
1894	0.92
1895	1.063
1896	1.101
1897	1.076
1898	1.218
1899	0.922
1900	1.133
1901	1.193
1902	1.129
1903	1.19
1904	1.294
1905	1.135
1906	1.001
1907	1.069
1908	1.278
1909	1.165
1910	1.263
1911	1.177
1912	1.164
1913	1.214
1914	1.328
1915	0.931
1916	1.054
1917	1.212
1918	1.337
1919	1.355
1920	1.228
1921	1.074
1922	1.237
1923	1.063
1924	0.958
1925	1.314
1926	1.136
1927	0.899
1928	1.035
1929	0.965
1930	0.865
1931	0.984
1932	1.115
1933	1.161
1934	1.157
1935	1.056
1936	1.292
1937	1.155
1938	1.368
1939	1.038
1940	1.148
1941	1.076
1942	0.898
1943	1.079
1944	1.247
1945	1.336
1946	0.987
1947	1.1
1948	1.2
1949	1.076
1950	1.267
1951	1.135
1952	1.029
1953	1.289
1954	1.175
1955	1.165
1956	0.932
1957	1.095
1958	1.322
1959	0.898
1960	1.006
1961	1.216
1962	0.934
1963	1.077
1964	0.937
1965	1.201
1966	1.01
1967	1.163
1968	0.692
1969	0.674
1970	1.046
1971	0.646
1972	0.482
1973	0.991
1974	0.86
1975	1.021
1976	0.883
1977	1.06
1978	0.877
1979	0.9
1980	0.706
1981	0.698
1982	0.739
1983	0.641
1984	0.863
1985	0.752
1986	0.642
1987	0.818
1988	0.933
1989	0.994
1990	0.984
1991	0.714
1992	1.003
1993	0.606
1994	1.013
1995	0.675
1996	0.633
1997	0.573