# northamerica_canada_cana199 - Fraser Bay, Otter Lake - 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/2724
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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_cana199 - Fraser Bay, Otter Lake - 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 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:
#--------------------
#	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: Fraser Bay, Otter Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 55.55
#	Southernmost_Latitude: 55.55
#	Easternmost_Longitude: -104.68
#	Westernmost_Longitude: -104.68
#	Elevation: 355 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana199B
#	Earliest_Year: 1865
#	Most_Recent_Year: 2001
#	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":"3.85435765123","T2":"14.6670489851","M1":"0.0229608838072","M2":"0.539145713282"}}
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# Species
#	Species_Name: spruce
#	Species_Code: PCSP
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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
1865	0.752
1866	0.703
1867	0.821
1868	0.851
1869	0.606
1870	0.938
1871	0.763
1872	0.895
1873	0.901
1874	1.183
1875	0.995
1876	1.061
1877	1.041
1878	1.002
1879	0.978
1880	0.964
1881	1.116
1882	1.071
1883	0.857
1884	0.433
1885	0.653
1886	0.527
1887	0.622
1888	0.685
1889	0.811
1890	0.657
1891	0.663
1892	0.64
1893	0.629
1894	0.728
1895	1.012
1896	0.821
1897	1.002
1898	1.014
1899	1.069
1900	1.068
1901	0.943
1902	0.906
1903	0.979
1904	1.009
1905	0.771
1906	1.029
1907	0.971
1908	1.054
1909	1.111
1910	1.095
1911	1.009
1912	0.881
1913	1.015
1914	1.241
1915	0.952
1916	1.302
1917	1.25
1918	1.062
1919	0.648
1920	0.951
1921	1.284
1922	1.157
1923	1.128
1924	0.932
1925	1.402
1926	1.068
1927	1.25
1928	0.914
1929	0.924
1930	1.024
1931	1.154
1932	1.274
1933	1.204
1934	1.232
1935	1.06
1936	0.99
1937	0.743
1938	0.864
1939	0.925
1940	0.806
1941	0.886
1942	0.954
1943	0.878
1944	0.929
1945	1.115
1946	1.134
1947	1.144
1948	1.041
1949	1.414
1950	1.137
1951	1.316
1952	1.239
1953	0.97
1954	0.877
1955	1.169
1956	1.044
1957	0.83
1958	0.872
1959	1.069
1960	0.876
1961	0.564
1962	0.564
1963	0.734
1964	0.533
1965	1.058
1966	1.029
1967	0.929
1968	1.136
1969	1.096
1970	0.951
1971	1.147
1972	1.059
1973	0.967
1974	1.091
1975	1.208
1976	1.262
1977	1.297
1978	1.166
1979	1.097
1980	0.998
1981	1.033
1982	0.717
1983	0.85
1984	0.812
1985	0.843
1986	0.941
1987	0.821
1988	0.515
1989	0.64
1990	0.822
1991	1.033
1992	0.857
1993	0.96
1994	1.221
1995	0.735
1996	1.008
1997	0.645
1998	0.567
1999	0.567
2000	0.669
2001	0.954