# northamerica_usa_or079 - Wizard Island - 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/4198
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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_or079 - Wizard Island - 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: Wizard Island
#	Location:
#	Country: United States
#	Northernmost_Latitude: 43.0
#	Southernmost_Latitude: 43.0
#	Easternmost_Longitude: -122.17
#	Westernmost_Longitude: -122.17
#	Elevation: 2215 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or079B
#	Earliest_Year: 1771
#	Most_Recent_Year: 1992
#	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":"4.62075145864","T2":"12.4765786813","M1":"0.0225578597454","M2":"0.480878246149"}}
#--------------------
# Species
#	Species_Name: mountain hemlock
#	Species_Code: TSME
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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
1771	1.083
1772	1.136
1773	1.23
1774	0.844
1775	0.723
1776	1.056
1777	1.018
1778	1.185
1779	1.04
1780	1.14
1781	0.835
1782	0.831
1783	0.795
1784	0.881
1785	0.726
1786	0.983
1787	0.779
1788	1.007
1789	0.972
1790	1.21
1791	1.423
1792	1.177
1793	1.222
1794	1.329
1795	1.115
1796	1.145
1797	1.184
1798	1.177
1799	1.096
1800	1.164
1801	0.498
1802	0.559
1803	0.951
1804	0.856
1805	0.994
1806	0.916
1807	0.8
1808	0.737
1809	0.873
1810	0.573
1811	1.03
1812	1.381
1813	0.936
1814	1.234
1815	1.234
1816	1.1
1817	1.043
1818	1.102
1819	0.881
1820	0.959
1821	1.377
1822	1.223
1823	0.937
1824	0.942
1825	1.013
1826	1.156
1827	0.95
1828	1.06
1829	1.257
1830	1.033
1831	0.863
1832	1.164
1833	1.001
1834	1.477
1835	0.915
1836	0.83
1837	1.108
1838	1.166
1839	1.109
1840	0.473
1841	0.659
1842	0.665
1843	1.145
1844	1.002
1845	1.005
1846	1.312
1847	0.771
1848	1.149
1849	0.925
1850	0.902
1851	1.089
1852	1.078
1853	0.845
1854	1.335
1855	1.312
1856	0.978
1857	1.045
1858	1.103
1859	0.905
1860	1.113
1861	0.784
1862	0.72
1863	1.296
1864	1.192
1865	0.819
1866	0.674
1867	0.852
1868	1.033
1869	0.981
1870	1.113
1871	0.763
1872	0.964
1873	1.082
1874	1.216
1875	1.211
1876	0.617
1877	1.225
1878	1.035
1879	1.086
1880	0.657
1881	1.366
1882	0.941
1883	0.962
1884	0.824
1885	1.219
1886	0.978
1887	0.754
1888	1.203
1889	1.037
1890	0.9
1891	1.049
1892	0.967
1893	0.843
1894	0.944
1895	1.341
1896	0.688
1897	0.921
1898	0.982
1899	0.501
1900	0.945
1901	0.921
1902	1.062
1903	0.919
1904	1.176
1905	0.985
1906	0.694
1907	1.121
1908	1.077
1909	0.882
1910	1.199
1911	0.904
1912	0.963
1913	1.175
1914	1.45
1915	1.016
1916	0.524
1917	0.716
1918	0.714
1919	0.898
1920	0.936
1921	0.803
1922	0.742
1923	0.705
1924	1.058
1925	0.681
1926	0.882
1927	0.765
1928	0.927
1929	0.614
1930	0.78
1931	0.923
1932	0.806
1933	0.763
1934	1.3
1935	0.987
1936	1.16
1937	0.76
1938	1.112
1939	1.275
1940	0.976
1941	1.044
1942	1.287
1943	0.909
1944	1.465
1945	1.244
1946	0.968
1947	1.341
1948	1.264
1949	1.211
1950	1.083
1951	0.942
1952	0.729
1953	0.798
1954	1.324
1955	1.41
1956	1.186
1957	1.209
1958	1.064
1959	0.991
1960	0.828
1961	0.699
1962	1.025
1963	1.364
1964	1.151
1965	0.995
1966	1.35
1967	0.806
1968	0.739
1969	1.023
1970	0.751
1971	0.561
1972	0.566
1973	1.009
1974	0.562
1975	0.712
1976	0.907
1977	1.067
1978	1.135
1979	1.118
1980	1.11
1981	1.007
1982	0.576
1983	0.641
1984	0.925
1985	1.025
1986	1.045
1987	1.053
1988	0.789
1989	0.89
1990	1.016
1991	0.899
1992	0.921