# northamerica_usa_ut510 - Electric 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/2815
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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_ut510 - Electric 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: Electric Lake
#	Location:
#	Country: United States
#	Northernmost_Latitude: 39.58
#	Southernmost_Latitude: 39.58
#	Easternmost_Longitude: -111.33
#	Westernmost_Longitude: -111.33
#	Elevation: 2970 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ut510B
#	Earliest_Year: 1762
#	Most_Recent_Year: 1983
#	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":"6.12595802793","T2":"14.3504865068","M1":"0.0226866301691","M2":"0.533463984551"}}
#--------------------
# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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
1762	1.019
1763	0.762
1764	0.675
1765	0.856
1766	0.754
1767	0.983
1768	1.04
1769	0.783
1770	0.876
1771	1.08
1772	0.952
1773	1.252
1774	0.869
1775	1.045
1776	0.945
1777	0.879
1778	1.002
1779	1.042
1780	1.115
1781	0.815
1782	0.86
1783	1.043
1784	0.902
1785	0.744
1786	0.59
1787	0.951
1788	0.955
1789	1.0
1790	1.086
1791	1.286
1792	1.183
1793	0.87
1794	1.329
1795	0.881
1796	0.635
1797	0.833
1798	1.018
1799	1.022
1800	0.973
1801	1.123
1802	1.244
1803	0.855
1804	0.925
1805	0.91
1806	0.942
1807	0.956
1808	1.13
1809	1.159
1810	0.868
1811	1.111
1812	1.095
1813	0.703
1814	0.975
1815	0.993
1816	1.239
1817	1.004
1818	0.7
1819	1.132
1820	0.978
1821	1.002
1822	0.969
1823	0.693
1824	0.674
1825	0.613
1826	0.96
1827	0.977
1828	1.007
1829	1.058
1830	1.041
1831	1.065
1832	0.918
1833	1.11
1834	1.064
1835	1.117
1836	0.992
1837	1.042
1838	0.905
1839	0.818
1840	1.012
1841	1.236
1842	0.901
1843	1.119
1844	0.89
1845	0.766
1846	0.919
1847	0.727
1848	0.855
1849	0.973
1850	0.705
1851	0.976
1852	0.918
1853	1.102
1854	0.805
1855	0.991
1856	0.61
1857	1.015
1858	0.924
1859	0.978
1860	1.129
1861	1.161
1862	0.939
1863	1.384
1864	0.822
1865	1.035
1866	1.138
1867	1.159
1868	1.48
1869	1.526
1870	1.114
1871	1.17
1872	0.856
1873	1.184
1874	0.88
1875	1.269
1876	1.102
1877	1.162
1878	0.992
1879	1.05
1880	0.667
1881	1.119
1882	0.751
1883	0.765
1884	0.888
1885	1.285
1886	1.225
1887	1.158
1888	1.159
1889	0.554
1890	0.948
1891	0.773
1892	0.764
1893	0.687
1894	0.895
1895	0.93
1896	0.79
1897	1.023
1898	1.014
1899	0.686
1900	0.977
1901	0.723
1902	1.021
1903	0.943
1904	0.73
1905	0.94
1906	1.114
1907	1.263
1908	1.457
1909	1.625
1910	1.62
1911	1.311
1912	1.169
1913	1.351
1914	1.357
1915	1.209
1916	1.237
1917	1.306
1918	0.867
1919	0.952
1920	0.799
1921	1.111
1922	1.062
1923	0.914
1924	0.926
1925	0.797
1926	0.838
1927	0.713
1928	0.871
1929	0.821
1930	0.994
1931	0.817
1932	0.629
1933	0.818
1934	0.618
1935	0.713
1936	0.825
1937	1.134
1938	1.106
1939	1.124
1940	1.15
1941	0.92
1942	1.03
1943	0.799
1944	0.946
1945	1.009
1946	0.959
1947	0.803
1948	1.029
1949	0.786
1950	0.827
1951	1.075
1952	1.181
1953	1.406
1954	1.119
1955	1.128
1956	0.994
1957	1.045
1958	1.247
1959	0.943
1960	1.102
1961	0.762
1962	1.121
1963	1.11
1964	1.048
1965	1.092
1966	1.084
1967	0.678
1968	1.064
1969	1.736
1970	0.847
1971	0.746
1972	1.083
1973	1.104
1974	1.089
1975	1.041
1976	1.281
1977	0.851
1978	1.176
1979	1.271
1980	0.641
1981	0.614
1982	0.797
1983	0.832