# northamerica_canada_cana291 - Prelude 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/8581
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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_cana291 - Prelude Lake - 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: Prelude Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 62.55
#	Southernmost_Latitude: 62.55
#	Easternmost_Longitude: -113.85
#	Westernmost_Longitude: -113.85
#	Elevation: 197 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana291B
#	Earliest_Year: 1863
#	Most_Recent_Year: 2005
#	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":"4.89992637412","T2":"16.2724789496","M1":"0.0230104392496","M2":"0.443030197211"}}
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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
#
age	trsgi
1863	1.093
1864	0.701
1865	0.71
1866	1.296
1867	1.146
1868	0.991
1869	0.758
1870	1.532
1871	1.415
1872	1.366
1873	1.052
1874	0.877
1875	0.695
1876	0.781
1877	0.892
1878	0.954
1879	0.828
1880	1.104
1881	0.344
1882	0.331
1883	0.392
1884	0.487
1885	0.768
1886	0.523
1887	0.974
1888	0.802
1889	1.346
1890	0.999
1891	0.838
1892	1.224
1893	0.647
1894	1.433
1895	1.267
1896	1.047
1897	0.885
1898	1.496
1899	1.257
1900	1.054
1901	1.139
1902	0.917
1903	1.251
1904	0.682
1905	0.927
1906	1.431
1907	1.612
1908	1.156
1909	1.396
1910	1.335
1911	1.201
1912	1.028
1913	1.048
1914	0.828
1915	0.898
1916	0.718
1917	0.834
1918	0.993
1919	1.336
1920	0.902
1921	0.951
1922	1.579
1923	1.026
1924	1.258
1925	0.954
1926	1.074
1927	0.45
1928	0.476
1929	0.946
1930	0.926
1931	1.014
1932	1.369
1933	1.205
1934	1.037
1935	0.936
1936	0.76
1937	0.782
1938	0.677
1939	0.747
1940	0.661
1941	1.142
1942	0.562
1943	0.862
1944	0.895
1945	0.847
1946	0.734
1947	0.469
1948	0.927
1949	0.746
1950	0.596
1951	1.214
1952	0.781
1953	0.789
1954	0.829
1955	0.979
1956	1.083
1957	1.409
1958	0.684
1959	0.932
1960	1.1
1961	0.771
1962	1.067
1963	1.224
1964	0.817
1965	1.188
1966	0.965
1967	0.767
1968	0.694
1969	0.475
1970	0.911
1971	0.734
1972	0.745
1973	0.641
1974	1.254
1975	0.617
1976	1.083
1977	0.918
1978	0.906
1979	1.004
1980	1.114
1981	1.268
1982	0.839
1983	1.022
1984	1.369
1985	0.998
1986	1.409
1987	1.28
1988	1.462
1989	1.05
1990	1.205
1991	1.493
1992	1.405
1993	0.446
1994	1.014
1995	0.565
1996	1.153
1997	1.236
1998	1.015
1999	0.813
2000	0.804
2001	1.037
2002	0.971
2003	1.067
2004	0.751
2005	1.334