# northamerica_usa_ks004 - Toronto Lake - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/4949
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_ks004 - Toronto Lake - Breitenmoser Tree Ring Chronology Data
#--------------------
# 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.
#--------------------
#	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: Toronto Lake
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.78
#	Southernmost_Latitude: 37.78
#	Easternmost_Longitude: -95.95
#	Westernmost_Longitude: -95.95
#	Elevation: 290 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ks004B
#	Earliest_Year: 1746
#	Most_Recent_Year: 1982
#	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":"4.88065256777","T2":"15.8723319838","M1":"0.0225965101955","M2":"0.552973300375"}}
#--------------------
# Species
#	Species_Name: post oak
#	Species_Code: QUST
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# Chronology:
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# Variables
#
# 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)
#
##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
1746	1.828
1747	1.714
1748	1.242
1749	1.259
1750	1.66
1751	1.226
1752	1.554
1753	1.06
1754	0.859
1755	0.756
1756	0.683
1757	0.456
1758	0.586
1759	0.769
1760	0.664
1761	0.931
1762	1.13
1763	0.993
1764	1.218
1765	0.853
1766	1.124
1767	0.603
1768	0.624
1769	0.592
1770	0.693
1771	0.911
1772	0.669
1773	0.625
1774	0.661
1775	1.095
1776	1.19
1777	0.891
1778	0.973
1779	1.15
1780	0.954
1781	1.105
1782	1.127
1783	0.972
1784	1.047
1785	0.865
1786	0.927
1787	1.203
1788	1.417
1789	1.076
1790	0.901
1791	0.85
1792	0.917
1793	1.06
1794	1.047
1795	1.287
1796	1.108
1797	1.077
1798	0.714
1799	0.936
1800	1.023
1801	0.753
1802	0.873
1803	0.948
1804	1.1
1805	1.035
1806	1.142
1807	1.095
1808	0.533
1809	0.692
1810	0.832
1811	1.105
1812	0.758
1813	0.93
1814	0.824
1815	0.865
1816	1.024
1817	0.815
1818	1.079
1819	0.875
1820	0.766
1821	0.978
1822	1.019
1823	0.699
1824	0.61
1825	0.831
1826	0.901
1827	0.996
1828	0.955
1829	0.884
1830	0.919
1831	1.183
1832	1.084
1833	0.735
1834	0.841
1835	0.768
1836	1.099
1837	1.298
1838	0.99
1839	1.026
1840	1.244
1841	1.076
1842	1.223
1843	1.308
1844	1.369
1845	1.162
1846	1.048
1847	1.267
1848	0.818
1849	0.946
1850	0.804
1851	0.662
1852	0.683
1853	0.857
1854	0.85
1855	0.439
1856	0.642
1857	0.689
1858	0.783
1859	1.046
1860	0.608
1861	1.013
1862	0.81
1863	1.411
1864	0.849
1865	0.957
1866	0.977
1867	1.114
1868	0.73
1869	1.105
1870	1.13
1871	0.929
1872	1.034
1873	1.072
1874	0.97
1875	1.001
1876	1.27
1877	1.058
1878	1.287
1879	1.036
1880	1.042
1881	0.92
1882	1.294
1883	1.222
1884	0.959
1885	1.155
1886	1.027
1887	0.866
1888	0.921
1889	1.143
1890	0.938
1891	1.128
1892	1.071
1893	0.98
1894	0.795
1895	0.763
1896	0.938
1897	0.757
1898	0.985
1899	0.916
1900	0.779
1901	0.754
1902	1.191
1903	1.133
1904	1.173
1905	0.949
1906	1.089
1907	0.938
1908	1.261
1909	1.303
1910	0.94
1911	0.77
1912	1.173
1913	0.696
1914	0.753
1915	1.21
1916	1.336
1917	1.046
1918	0.915
1919	1.291
1920	1.186
1921	1.165
1922	1.106
1923	1.2
1924	1.068
1925	0.884
1926	1.065
1927	1.198
1928	1.373
1929	1.148
1930	1.069
1931	1.042
1932	1.224
1933	0.862
1934	0.927
1935	1.242
1936	0.893
1937	0.997
1938	1.223
1939	0.883
1940	0.803
1941	1.004
1942	1.073
1943	0.971
1944	0.904
1945	1.073
1946	0.83
1947	1.098
1948	0.878
1949	1.077
1950	0.885
1951	1.023
1952	0.884
1953	0.718
1954	0.834
1955	0.989
1956	0.836
1957	0.939
1958	1.073
1959	1.01
1960	0.98
1961	1.033
1962	0.986
1963	0.878
1964	0.867
1965	1.126
1966	0.84
1967	0.943
1968	1.012
1969	0.921
1970	1.018
1971	1.026
1972	0.857
1973	1.015
1974	1.008
1975	1.207
1976	0.844
1977	0.789
1978	0.842
1979	0.835
1980	0.69
1981	0.736
1982	1.061