# northamerica_usa_nm050 - Tijeras Canyon - 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/3111
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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_nm050 - Tijeras Canyon - 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: Tijeras Canyon
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.08
#	Southernmost_Latitude: 35.08
#	Easternmost_Longitude: -106.38
#	Westernmost_Longitude: -106.38
#	Elevation: 1958 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_nm050B
#	Earliest_Year: 1762
#	Most_Recent_Year: 1976
#	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":"3.57815958662","T2":"14.622158158","M1":"0.0235536762619","M2":"0.52440200542"}}
#--------------------
# Species
#	Species_Name: pinyon pine
#	Species_Code: PIED
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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	1.259
1763	0.238
1764	1.189
1765	0.819
1766	1.282
1767	1.129
1768	0.834
1769	1.01
1770	1.29
1771	1.55
1772	1.39
1773	0.534
1774	0.626
1775	0.7
1776	0.946
1777	1.172
1778	1.426
1779	1.058
1780	0.454
1781	0.956
1782	0.833
1783	1.298
1784	1.376
1785	1.357
1786	0.973
1787	1.038
1788	0.839
1789	0.705
1790	1.077
1791	1.078
1792	1.093
1793	1.202
1794	1.09
1795	1.328
1796	0.729
1797	0.761
1798	0.856
1799	0.907
1800	0.989
1801	0.747
1802	0.535
1803	0.419
1804	0.649
1805	0.53
1806	0.377
1807	0.463
1808	0.388
1809	0.7
1810	0.567
1811	0.784
1812	0.571
1813	0.561
1814	0.566
1815	0.947
1816	1.404
1817	0.807
1818	0.43
1819	0.631
1820	0.817
1821	0.878
1822	0.296
1823	0.524
1824	0.806
1825	1.049
1826	0.811
1827	0.822
1828	1.395
1829	1.177
1830	1.032
1831	0.63
1832	0.531
1833	0.916
1834	0.82
1835	0.655
1836	0.581
1837	0.973
1838	0.943
1839	1.142
1840	1.057
1841	0.956
1842	0.344
1843	0.624
1844	0.642
1845	0.732
1846	0.959
1847	0.349
1848	0.673
1849	0.845
1850	0.612
1851	0.498
1852	0.39
1853	0.554
1854	0.637
1855	0.973
1856	1.392
1857	1.281
1858	1.238
1859	0.946
1860	0.833
1861	0.671
1862	0.502
1863	0.998
1864	1.223
1865	1.849
1866	2.178
1867	2.743
1868	2.692
1869	2.189
1870	0.948
1871	1.337
1872	1.632
1873	0.571
1874	1.33
1875	1.428
1876	1.444
1877	1.537
1878	1.33
1879	0.795
1880	0.424
1881	1.006
1882	1.217
1883	0.622
1884	1.155
1885	1.45
1886	0.95
1887	1.203
1888	0.952
1889	1.106
1890	1.046
1891	1.357
1892	1.038
1893	0.786
1894	0.786
1895	1.046
1896	0.541
1897	1.651
1898	1.056
1899	0.389
1900	0.305
1901	1.12
1902	0.147
1903	0.962
1904	-0.107
1905	1.611
1906	1.446
1907	1.505
1908	1.224
1909	1.198
1910	0.491
1911	1.229
1912	1.462
1913	1.061
1914	1.728
1915	2.031
1916	1.688
1917	1.576
1918	1.068
1919	2.1
1920	1.505
1921	1.002
1922	0.366
1923	0.717
1924	1.01
1925	-0.044
1926	0.869
1927	0.921
1928	0.836
1929	0.986
1930	1.154
1931	1.293
1932	1.388
1933	1.175
1934	0.566
1935	1.592
1936	1.114
1937	1.454
1938	0.642
1939	0.501
1940	0.988
1941	1.455
1942	1.582
1943	1.368
1944	1.485
1945	1.152
1946	0.49
1947	0.563
1948	0.892
1949	0.823
1950	-0.065
1951	-0.105
1952	0.792
1953	0.351
1954	0.697
1955	0.274
1956	0.226
1957	0.917
1958	0.985
1959	0.718
1960	1.199
1961	1.113
1962	0.572
1963	0.67
1964	0.706
1965	0.694
1966	0.816
1967	0.194
1968	1.161
1969	1.093
1970	1.066
1971	0.429
1972	0.771
1973	1.252
1974	0.426
1975	1.507
1976	0.456