# northamerica_usa_wa092 - Thornton Lakes Low - 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/4196
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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
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# Title
#	Study_Name: northamerica_usa_wa092 - Thornton Lakes Low - 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: Thornton Lakes Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.67
#	Southernmost_Latitude: 48.67
#	Easternmost_Longitude: -121.33
#	Westernmost_Longitude: -121.33
#	Elevation: 1220 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa092B
#	Earliest_Year: 1753
#	Most_Recent_Year: 1992
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"5.62590943636","T2":"13.772562864","M1":"0.0229677423303","M2":"0.495988276332"}}
#--------------------
# 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
1753	0.841
1754	0.573
1755	0.736
1756	1.078
1757	1.006
1758	0.952
1759	1.189
1760	0.599
1761	0.924
1762	0.791
1763	0.878
1764	0.938
1765	0.969
1766	0.84
1767	0.828
1768	0.723
1769	0.724
1770	0.844
1771	0.943
1772	0.893
1773	0.946
1774	0.727
1775	0.546
1776	0.806
1777	0.867
1778	0.628
1779	0.546
1780	0.697
1781	0.594
1782	0.804
1783	0.879
1784	0.998
1785	0.925
1786	0.805
1787	0.658
1788	0.737
1789	0.772
1790	0.845
1791	0.921
1792	0.957
1793	1.1
1794	1.114
1795	0.939
1796	0.72
1797	0.679
1798	0.623
1799	0.712
1800	0.872
1801	0.855
1802	0.946
1803	0.831
1804	1.117
1805	1.125
1806	0.863
1807	0.846
1808	0.776
1809	1.041
1810	0.595
1811	0.745
1812	0.947
1813	0.848
1814	0.878
1815	0.9
1816	1.064
1817	0.962
1818	1.099
1819	1.001
1820	0.87
1821	0.927
1822	1.207
1823	1.059
1824	1.158
1825	1.165
1826	1.153
1827	1.185
1828	1.482
1829	1.65
1830	1.38
1831	1.293
1832	1.283
1833	1.481
1834	1.251
1835	1.093
1836	1.0
1837	1.249
1838	1.195
1839	1.285
1840	1.251
1841	1.557
1842	1.501
1843	1.495
1844	1.195
1845	1.138
1846	1.357
1847	1.158
1848	1.047
1849	0.7
1850	0.975
1851	1.221
1852	0.972
1853	1.245
1854	1.057
1855	1.226
1856	1.083
1857	1.27
1858	1.133
1859	0.99
1860	0.933
1861	0.79
1862	0.557
1863	0.954
1864	1.084
1865	1.014
1866	0.83
1867	0.883
1868	1.037
1869	0.827
1870	0.856
1871	0.94
1872	1.111
1873	1.154
1874	1.109
1875	0.82
1876	0.561
1877	0.431
1878	0.516
1879	1.013
1880	0.856
1881	1.165
1882	1.022
1883	1.005
1884	0.962
1885	1.004
1886	1.098
1887	1.094
1888	1.279
1889	1.204
1890	1.204
1891	1.272
1892	1.388
1893	1.185
1894	1.26
1895	1.518
1896	1.18
1897	1.39
1898	1.454
1899	0.936
1900	1.307
1901	1.381
1902	1.257
1903	1.023
1904	1.029
1905	0.834
1906	0.877
1907	0.992
1908	0.899
1909	1.012
1910	1.426
1911	1.18
1912	1.117
1913	1.198
1914	1.103
1915	0.776
1916	0.811
1917	0.959
1918	0.995
1919	1.071
1920	0.981
1921	0.995
1922	1.002
1923	1.086
1924	0.999
1925	0.887
1926	0.788
1927	0.698
1928	0.473
1929	0.306
1930	0.24
1931	0.274
1932	0.371
1933	0.709
1934	0.841
1935	0.861
1936	0.655
1937	0.667
1938	0.644
1939	0.668
1940	0.561
1941	0.612
1942	0.726
1943	0.998
1944	1.08
1945	1.009
1946	1.202
1947	1.414
1948	1.091
1949	1.136
1950	1.238
1951	1.648
1952	1.211
1953	0.772
1954	0.83
1955	0.963
1956	0.924
1957	0.897
1958	0.981
1959	1.037
1960	1.069
1961	0.938
1962	0.889
1963	0.867
1964	1.364
1965	1.435
1966	1.693
1967	1.216
1968	1.01
1969	0.736
1970	0.67
1971	0.487
1972	0.684
1973	0.915
1974	0.935
1975	0.953
1976	0.928
1977	0.824
1978	1.113
1979	1.21
1980	0.985
1981	0.991
1982	0.834
1983	0.983
1984	1.251
1985	0.96
1986	0.731
1987	0.84
1988	1.086
1989	0.792
1990	0.977
1991	0.526
1992	0.947