# northamerica_usa_nm039 - Ruidosa Ridge - 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/3100
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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_nm039 - Ruidosa Ridge - 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: Ruidosa Ridge
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.53
#	Southernmost_Latitude: 35.53
#	Easternmost_Longitude: -105.57
#	Westernmost_Longitude: -105.57
#	Elevation: 2286 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm039B
#	Earliest_Year: 1721
#	Most_Recent_Year: 1972
#	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":"3.04986281712","T2":"13.3293639576","M1":"0.023692558652","M2":"0.568327880179"}}
#--------------------
# 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
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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
1721	1.42
1722	0.808
1723	1.082
1724	1.111
1725	0.494
1726	1.509
1727	1.179
1728	0.897
1729	0.278
1730	0.204
1731	0.633
1732	0.957
1733	0.617
1734	0.94
1735	0.586
1736	0.55
1737	0.208
1738	0.513
1739	0.196
1740	0.795
1741	0.738
1742	0.43
1743	1.11
1744	0.711
1745	0.855
1746	0.794
1747	2.008
1748	0.228
1749	1.229
1750	0.385
1751	1.504
1752	0.591
1753	1.004
1754	1.833
1755	1.181
1756	0.633
1757	0.656
1758	0.966
1759	0.956
1760	0.457
1761	1.641
1762	1.872
1763	0.712
1764	1.826
1765	1.013
1766	1.876
1767	1.283
1768	1.588
1769	1.355
1770	1.254
1771	1.275
1772	0.691
1773	0.163
1774	0.807
1775	0.509
1776	0.982
1777	0.67
1778	0.926
1779	0.534
1780	0.374
1781	0.4
1782	0.437
1783	1.066
1784	1.156
1785	0.563
1786	0.62
1787	1.105
1788	0.364
1789	0.375
1790	0.645
1791	1.191
1792	1.207
1793	1.646
1794	0.683
1795	0.744
1796	0.537
1797	0.627
1798	0.897
1799	1.298
1800	1.036
1801	0.31
1802	0.896
1803	0.688
1804	1.089
1805	0.615
1806	0.757
1807	1.531
1808	0.862
1809	0.95
1810	1.002
1811	1.103
1812	0.937
1813	0.949
1814	0.601
1815	1.179
1816	1.845
1817	1.653
1818	0.581
1819	0.451
1820	0.442
1821	1.471
1822	0.137
1823	0.799
1824	0.577
1825	0.923
1826	0.526
1827	1.139
1828	1.566
1829	1.052
1830	1.151
1831	1.19
1832	1.087
1833	1.414
1834	1.715
1835	0.735
1836	0.347
1837	1.502
1838	1.696
1839	2.028
1840	1.903
1841	1.955
1842	0.191
1843	1.338
1844	2.102
1845	0.961
1846	1.034
1847	0.419
1848	0.597
1849	1.259
1850	0.909
1851	0.286
1852	0.919
1853	0.569
1854	0.89
1855	1.246
1856	1.462
1857	1.058
1858	1.443
1859	0.744
1860	0.856
1861	0.346
1862	0.215
1863	0.66
1864	0.353
1865	0.785
1866	1.163
1867	1.4
1868	1.553
1869	2.463
1870	1.111
1871	0.889
1872	0.588
1873	0.251
1874	0.858
1875	0.503
1876	1.016
1877	1.314
1878	0.929
1879	1.149
1880	0.109
1881	1.281
1882	0.989
1883	0.42
1884	1.203
1885	1.201
1886	1.102
1887	2.404
1888	2.07
1889	0.856
1890	0.607
1891	1.316
1892	0.688
1893	0.077
1894	0.671
1895	0.755
1896	0.268
1897	1.491
1898	0.772
1899	0.239
1900	0.962
1901	0.882
1902	0.308
1903	0.892
1904	0.024
1905	1.327
1906	1.33
1907	1.525
1908	0.565
1909	0.93
1910	0.511
1911	0.653
1912	1.458
1913	0.468
1914	0.899
1915	1.282
1916	2.049
1917	0.805
1918	0.479
1919	2.574
1920	1.772
1921	1.433
1922	0.422
1923	0.966
1924	1.191
1925	0.058
1926	1.772
1927	0.678
1928	1.514
1929	1.243
1930	1.047
1931	1.234
1932	2.675
1933	1.954
1934	0.148
1935	1.864
1936	0.988
1937	1.036
1938	0.365
1939	0.92
1940	0.636
1941	2.026
1942	2.009
1943	0.802
1944	1.077
1945	0.788
1946	0.474
1947	1.162
1948	1.234
1949	2.229
1950	1.283
1951	0.454
1952	0.117
1953	0.236
1954	0.357
1955	0.07
1956	0.113
1957	0.142
1958	1.154
1959	0.93
1960	0.934
1961	0.627
1962	0.683
1963	0.733
1964	0.409
1965	0.22
1966	0.667
1967	0.278
1968	1.141
1969	1.327
1970	0.53
1971	0.129
1972	1.137