# northamerica_usa_wa100 - Lake Minotaur High - Breitenmoser Tree Ring Chronology Data
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#		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.
#
#
# 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/4146
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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_wa100 - Lake Minotaur High - 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
#------------------
# Site_Information
#	Site_Name: Lake Minotaur High
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.83
#	Southernmost_Latitude: 47.83
#	Easternmost_Longitude: -121.0
#	Westernmost_Longitude: -121.0
#	Elevation: 1740 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa100B
#	Earliest_Year: 1730
#	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":"4.31586204049","T2":"17.6565233033","M1":"0.0216425745308","M2":"0.360108544501"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1730	1.057
1731	1.04
1732	1.157
1733	0.995
1734	0.997
1735	1.201
1736	1.405
1737	1.341
1738	1.182
1739	1.181
1740	1.078
1741	1.515
1742	0.921
1743	0.823
1744	0.818
1745	0.716
1746	0.907
1747	1.225
1748	0.962
1749	1.003
1750	1.254
1751	1.294
1752	1.054
1753	0.642
1754	0.818
1755	0.785
1756	1.242
1757	0.954
1758	1.181
1759	1.225
1760	1.025
1761	1.076
1762	0.84
1763	0.95
1764	1.009
1765	1.306
1766	1.037
1767	1.052
1768	1.174
1769	1.317
1770	1.205
1771	1.344
1772	1.085
1773	1.0
1774	1.091
1775	0.712
1776	0.989
1777	1.148
1778	1.091
1779	0.936
1780	1.094
1781	1.028
1782	1.148
1783	1.39
1784	1.247
1785	0.911
1786	0.902
1787	0.883
1788	0.834
1789	0.771
1790	1.07
1791	1.292
1792	1.508
1793	1.325
1794	1.567
1795	1.287
1796	1.254
1797	1.171
1798	1.272
1799	1.138
1800	1.053
1801	1.04
1802	0.717
1803	1.263
1804	1.455
1805	1.475
1806	0.923
1807	0.98
1808	0.738
1809	0.98
1810	0.632
1811	0.666
1812	0.744
1813	0.948
1814	1.054
1815	1.045
1816	1.228
1817	1.308
1818	1.131
1819	0.843
1820	0.685
1821	0.598
1822	0.974
1823	1.09
1824	0.901
1825	1.087
1826	1.069
1827	1.041
1828	0.937
1829	1.311
1830	1.012
1831	0.93
1832	0.598
1833	0.922
1834	1.133
1835	1.047
1836	0.857
1837	0.877
1838	0.666
1839	1.049
1840	0.549
1841	0.683
1842	0.806
1843	0.881
1844	0.671
1845	0.66
1846	0.724
1847	0.546
1848	0.863
1849	0.395
1850	0.587
1851	0.762
1852	0.899
1853	1.019
1854	0.886
1855	1.095
1856	0.573
1857	0.905
1858	0.921
1859	0.894
1860	0.804
1861	0.764
1862	0.313
1863	0.956
1864	0.597
1865	0.748
1866	0.366
1867	0.466
1868	0.55
1869	0.685
1870	0.725
1871	0.635
1872	0.654
1873	0.814
1874	0.829
1875	0.732
1876	0.641
1877	0.596
1878	0.745
1879	0.686
1880	0.609
1881	0.622
1882	0.773
1883	0.897
1884	0.959
1885	1.194
1886	1.225
1887	0.764
1888	0.856
1889	1.095
1890	0.906
1891	0.93
1892	0.826
1893	0.941
1894	0.901
1895	1.141
1896	0.843
1897	0.924
1898	0.957
1899	0.665
1900	0.907
1901	1.171
1902	1.012
1903	1.055
1904	1.451
1905	1.438
1906	0.972
1907	1.017
1908	0.93
1909	0.883
1910	1.051
1911	1.079
1912	0.901
1913	0.982
1914	1.347
1915	0.99
1916	0.812
1917	1.107
1918	1.141
1919	1.018
1920	1.112
1921	0.928
1922	1.12
1923	1.068
1924	0.925
1925	0.986
1926	1.116
1927	1.134
1928	1.119
1929	1.169
1930	1.333
1931	1.262
1932	1.141
1933	1.234
1934	1.561
1935	1.521
1936	1.182
1937	1.274
1938	1.471
1939	1.184
1940	1.371
1941	1.434
1942	1.361
1943	1.419
1944	1.378
1945	1.317
1946	1.096
1947	1.544
1948	1.762
1949	1.266
1950	1.412
1951	1.43
1952	0.942
1953	1.012
1954	0.882
1955	1.01
1956	0.735
1957	1.274
1958	1.472
1959	1.148
1960	1.179
1961	1.064
1962	0.97
1963	0.911
1964	1.0
1965	0.987
1966	1.059
1967	1.116
1968	1.076
1969	0.713
1970	0.954
1971	0.824
1972	0.656
1973	0.767
1974	0.638
1975	0.714
1976	0.626
1977	0.928
1978	0.918
1979	0.968
1980	0.886
1981	0.87
1982	0.67
1983	0.554
1984	0.931
1985	0.826
1986	0.791
1987	0.97
1988	0.968
1989	0.778
1990	1.164
1991	0.369
1992	0.878