# northamerica_usa_az556 - Scheelite Canyon Huachuca Mountains - 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.
#
#
# 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/2658
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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_az556 - Scheelite Canyon Huachuca Mountains - 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: Scheelite Canyon Huachuca Mountains
#	Location:
#	Country: United States
#	Northernmost_Latitude: 31.45
#	Southernmost_Latitude: 31.45
#	Easternmost_Longitude: -110.35
#	Westernmost_Longitude: -110.35
#	Elevation: 1750 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_az556B
#	Earliest_Year: 1733
#	Most_Recent_Year: 1995
#	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":"3.28810072858","T2":"15.1041734824","M1":"0.0235320866369","M2":"0.513455318083"}}
#--------------------
# Species
#	Species_Name: Douglas fir
#	Species_Code: PSME
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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
1733	0.488
1734	0.989
1735	0.686
1736	1.041
1737	1.579
1738	1.355
1739	1.141
1740	0.939
1741	1.224
1742	0.933
1743	1.269
1744	1.169
1745	1.308
1746	1.958
1747	1.563
1748	0.647
1749	1.46
1750	1.197
1751	0.752
1752	0.471
1753	0.325
1754	0.777
1755	0.778
1756	0.809
1757	0.704
1758	0.98
1759	0.685
1760	0.613
1761	0.604
1762	1.021
1763	1.003
1764	1.562
1765	1.403
1766	1.635
1767	1.201
1768	1.217
1769	1.449
1770	1.369
1771	1.657
1772	1.106
1773	0.892
1774	0.908
1775	0.964
1776	0.879
1777	0.912
1778	1.14
1779	1.114
1780	0.967
1781	0.935
1782	0.643
1783	1.388
1784	1.539
1785	1.24
1786	1.068
1787	0.991
1788	0.841
1789	0.798
1790	0.296
1791	0.918
1792	0.901
1793	1.185
1794	0.616
1795	0.958
1796	1.015
1797	0.904
1798	0.823
1799	1.078
1800	1.055
1801	1.067
1802	1.313
1803	0.97
1804	1.487
1805	0.972
1806	0.614
1807	1.165
1808	0.582
1809	1.088
1810	1.095
1811	1.119
1812	1.024
1813	0.874
1814	0.839
1815	1.372
1816	1.496
1817	1.133
1818	0.955
1819	0.664
1820	0.579
1821	0.988
1822	0.715
1823	0.733
1824	1.076
1825	0.896
1826	0.814
1827	1.001
1828	1.134
1829	0.855
1830	1.293
1831	1.451
1832	1.492
1833	1.702
1834	1.111
1835	1.429
1836	0.993
1837	1.57
1838	1.186
1839	1.637
1840	1.083
1841	0.469
1842	0.475
1843	0.751
1844	1.049
1845	1.115
1846	1.232
1847	0.395
1848	0.737
1849	1.051
1850	1.216
1851	0.951
1852	1.323
1853	1.128
1854	1.114
1855	0.945
1856	1.105
1857	0.939
1858	1.069
1859	1.032
1860	0.926
1861	0.942
1862	0.845
1863	0.437
1864	0.491
1865	0.945
1866	0.884
1867	1.221
1868	1.545
1869	1.164
1870	1.072
1871	0.891
1872	0.54
1873	0.708
1874	1.059
1875	1.019
1876	1.052
1877	1.035
1878	0.642
1879	0.583
1880	0.844
1881	0.478
1882	0.934
1883	0.829
1884	0.886
1885	1.06
1886	0.856
1887	0.969
1888	1.193
1889	1.164
1890	1.088
1891	1.185
1892	0.622
1893	0.215
1894	0.468
1895	0.247
1896	0.698
1897	0.897
1898	1.375
1899	1.294
1900	0.707
1901	1.027
1902	0.678
1903	1.122
1904	0.466
1905	1.248
1906	1.311
1907	1.474
1908	1.759
1909	1.378
1910	0.897
1911	1.16
1912	1.504
1913	1.325
1914	1.434
1915	1.707
1916	1.514
1917	1.557
1918	0.879
1919	1.184
1920	1.446
1921	1.137
1922	1.206
1923	0.8
1924	1.188
1925	0.459
1926	1.102
1927	0.964
1928	1.032
1929	1.008
1930	1.279
1931	1.19
1932	1.669
1933	1.129
1934	0.673
1935	1.253
1936	1.127
1937	0.993
1938	0.81
1939	0.41
1940	0.826
1941	1.015
1942	0.864
1943	0.311
1944	0.93
1945	0.966
1946	0.65
1947	0.543
1948	0.289
1949	0.636
1950	0.681
1951	0.184
1952	0.824
1953	0.576
1954	0.129
1955	0.697
1956	0.438
1957	0.798
1958	1.032
1959	1.079
1960	0.955
1961	0.439
1962	0.8
1963	0.739
1964	1.183
1965	1.313
1966	1.11
1967	0.831
1968	1.457
1969	0.797
1970	0.922
1971	0.276
1972	0.618
1973	1.019
1974	0.235
1975	0.909
1976	0.764
1977	0.518
1978	0.853
1979	1.277
1980	0.785
1981	1.067
1982	0.437
1983	1.112
1984	1.369
1985	1.424
1986	1.25
1987	1.561
1988	1.211
1989	0.913
1990	0.652
1991	1.309
1992	1.428
1993	1.379
1994	0.58
1995	1.257