# northamerica_canada_cana253 - Granite Lake - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/6158
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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
#--------------------
# Title
#	Study_Name: northamerica_canada_cana253 - Granite 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 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: Granite Lake
#	Location:
#	Country: Canada
#	Northernmost_Latitude: 49.68
#	Southernmost_Latitude: 49.68
#	Easternmost_Longitude: -94.87
#	Westernmost_Longitude: -94.87
#	Elevation: 395 m
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# Data_Collection
#	Collection_Name: northamerica_canada_cana253B
#	Earliest_Year: 1793
#	Most_Recent_Year: 2004
#	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":"2.83039973126","T2":"13.6029354161","M1":"0.0230876483388","M2":"0.574107321"}}
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# Species
#	Species_Name: red pine
#	Species_Code: PIRE
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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
1793	1.193
1794	1.239
1795	1.439
1796	1.263
1797	0.989
1798	0.706
1799	1.069
1800	0.701
1801	1.136
1802	1.405
1803	0.87
1804	0.815
1805	1.014
1806	0.878
1807	0.942
1808	0.607
1809	0.748
1810	0.938
1811	0.879
1812	0.917
1813	0.728
1814	0.868
1815	1.132
1816	0.982
1817	0.727
1818	0.958
1819	1.146
1820	0.73
1821	0.65
1822	1.038
1823	0.771
1824	0.976
1825	0.864
1826	0.923
1827	0.969
1828	1.25
1829	0.893
1830	0.731
1831	0.565
1832	0.716
1833	1.002
1834	1.251
1835	0.717
1836	0.931
1837	0.801
1838	0.823
1839	0.741
1840	0.477
1841	0.523
1842	0.701
1843	0.807
1844	0.724
1845	0.563
1846	0.777
1847	0.397
1848	0.498
1849	0.675
1850	0.693
1851	0.933
1852	0.907
1853	1.059
1854	0.7
1855	0.909
1856	1.215
1857	0.987
1858	1.025
1859	0.84
1860	0.889
1861	0.977
1862	0.704
1863	0.405
1864	0.495
1865	0.597
1866	0.83
1867	0.862
1868	0.884
1869	1.008
1870	1.398
1871	1.187
1872	1.446
1873	1.332
1874	1.019
1875	1.132
1876	1.202
1877	1.401
1878	1.365
1879	1.725
1880	1.388
1881	1.325
1882	1.318
1883	0.75
1884	1.052
1885	1.268
1886	0.723
1887	0.747
1888	0.71
1889	0.507
1890	0.821
1891	0.82
1892	0.769
1893	1.012
1894	0.68
1895	1.074
1896	0.963
1897	0.903
1898	1.189
1899	1.631
1900	1.064
1901	1.272
1902	1.246
1903	1.054
1904	1.312
1905	1.104
1906	1.11
1907	0.834
1908	0.885
1909	0.971
1910	0.52
1911	1.104
1912	1.454
1913	1.129
1914	1.004
1915	0.97
1916	0.847
1917	0.883
1918	0.962
1919	1.009
1920	0.747
1921	1.008
1922	1.121
1923	0.761
1924	0.727
1925	1.099
1926	1.323
1927	0.991
1928	1.187
1929	0.78
1930	0.948
1931	0.982
1932	0.634
1933	0.536
1934	0.499
1935	0.812
1936	0.659
1937	0.734
1938	0.915
1939	0.55
1940	0.615
1941	0.679
1942	0.719
1943	0.707
1944	0.813
1945	0.8
1946	0.82
1947	0.989
1948	0.857
1949	0.863
1950	0.916
1951	0.687
1952	0.907
1953	1.178
1954	1.128
1955	1.287
1956	1.236
1957	1.412
1958	1.758
1959	2.154
1960	1.496
1961	0.988
1962	1.716
1963	1.502
1964	1.064
1965	1.594
1966	1.522
1967	1.374
1968	1.172
1969	1.69
1970	1.281
1971	1.559
1972	0.887
1973	1.216
1974	0.818
1975	1.184
1976	0.976
1977	0.649
1978	0.909
1979	0.616
1980	0.409
1981	0.798
1982	0.694
1983	0.598
1984	0.676
1985	0.697
1986	0.619
1987	0.723
1988	0.59
1989	0.82
1990	0.641
1991	0.538
1992	0.744
1993	0.888
1994	0.935
1995	0.688
1996	0.88
1997	0.979
1998	1.153
1999	1.354
2000	1.553
2001	1.385
2002	0.934
2003	0.965
2004	0.875