# northamerica_canada_cana181 - Kildonan Park - 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/4792
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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_cana181 - Kildonan Park - 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: Kildonan Park
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.93
#	Southernmost_Latitude: 49.93
#	Easternmost_Longitude: -97.1
#	Westernmost_Longitude: -97.1
#	Elevation: 230 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana181B
#	Earliest_Year: 1850
#	Most_Recent_Year: 1999
#	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":"5.03762009405","T2":"16.42082317","M1":"0.0229637409464","M2":"0.501376869521"}}
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# Species
#	Species_Name: burr oak
#	Species_Code: QUMA
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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
1850	1.288
1851	0.716
1852	0.66
1853	0.937
1854	1.175
1855	1.216
1856	1.188
1857	1.13
1858	1.12
1859	1.081
1860	1.136
1861	1.221
1862	0.942
1863	0.577
1864	0.46
1865	0.563
1866	1.019
1867	0.863
1868	0.715
1869	0.763
1870	0.78
1871	0.736
1872	0.88
1873	0.834
1874	0.858
1875	0.496
1876	0.609
1877	1.049
1878	0.96
1879	1.214
1880	1.249
1881	1.18
1882	1.205
1883	0.872
1884	1.153
1885	1.566
1886	1.061
1887	0.94
1888	0.908
1889	0.559
1890	1.094
1891	1.357
1892	1.684
1893	1.62
1894	1.511
1895	1.451
1896	1.714
1897	1.173
1898	1.424
1899	1.459
1900	0.84
1901	1.404
1902	1.384
1903	0.873
1904	1.203
1905	1.277
1906	0.959
1907	0.862
1908	0.742
1909	1.012
1910	0.82
1911	0.926
1912	0.981
1913	1.083
1914	0.948
1915	0.494
1916	0.986
1917	0.516
1918	0.876
1919	0.816
1920	0.919
1921	0.905
1922	1.069
1923	1.36
1924	0.909
1925	1.1
1926	0.884
1927	1.033
1928	1.1
1929	1.034
1930	0.867
1931	0.675
1932	0.722
1933	0.919
1934	1.163
1935	1.272
1936	0.856
1937	0.97
1938	0.87
1939	0.959
1940	0.919
1941	1.061
1942	0.932
1943	1.022
1944	1.168
1945	1.265
1946	0.707
1947	1.121
1948	1.23
1949	1.286
1950	1.419
1951	0.908
1952	0.992
1953	1.305
1954	1.246
1955	0.872
1956	0.786
1957	0.95
1958	0.775
1959	0.74
1960	0.619
1961	0.644
1962	0.649
1963	0.758
1964	0.59
1965	0.662
1966	0.673
1967	0.659
1968	0.652
1969	0.714
1970	0.612
1971	0.798
1972	0.756
1973	0.898
1974	0.776
1975	0.983
1976	0.778
1977	0.967
1978	1.292
1979	1.111
1980	0.642
1981	1.106
1982	0.803
1983	0.682
1984	0.483
1985	0.638
1986	1.082
1987	1.013
1988	1.098
1989	1.307
1990	1.178
1991	0.868
1992	1.153
1993	1.502
1994	1.496
1995	1.337
1996	1.369
1997	0.983
1998	1.386
1999	1.587