# northamerica_usa_nm111 - Gallinas Mountains - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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.
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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/4975
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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_nm111 - Gallinas 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Gallinas Mountains
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.23
#	Southernmost_Latitude: 34.23
#	Easternmost_Longitude: -105.78
#	Westernmost_Longitude: -105.78
#	Elevation: 2170 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm111B
#	Earliest_Year: 1721
#	Most_Recent_Year: 1981
#	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":"4.20959571111","T2":"16.1008260232","M1":"0.0229350770454","M2":"0.476877523897"}}
#--------------------
# 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
1721	1.747
1722	1.713
1723	1.282
1724	1.139
1725	0.873
1726	1.03
1727	0.71
1728	1.076
1729	0.86
1730	0.966
1731	0.567
1732	1.058
1733	0.571
1734	1.166
1735	0.772
1736	0.981
1737	0.862
1738	1.121
1739	0.49
1740	0.928
1741	1.342
1742	0.806
1743	1.046
1744	1.035
1745	1.081
1746	1.625
1747	1.704
1748	0.543
1749	1.396
1750	0.901
1751	1.52
1752	0.511
1753	1.297
1754	1.014
1755	0.817
1756	0.605
1757	0.26
1758	0.922
1759	1.055
1760	0.797
1761	1.141
1762	1.368
1763	0.423
1764	1.022
1765	0.591
1766	1.107
1767	1.299
1768	1.123
1769	1.129
1770	0.92
1771	1.773
1772	0.695
1773	0.924
1774	0.846
1775	0.761
1776	1.057
1777	0.949
1778	0.921
1779	0.865
1780	0.585
1781	0.695
1782	0.814
1783	1.091
1784	1.464
1785	1.129
1786	0.913
1787	1.004
1788	0.872
1789	0.584
1790	0.909
1791	1.218
1792	0.939
1793	1.417
1794	1.263
1795	1.124
1796	0.933
1797	0.952
1798	1.22
1799	1.131
1800	1.318
1801	1.013
1802	0.887
1803	1.125
1804	1.147
1805	0.745
1806	0.391
1807	0.984
1808	1.062
1809	1.137
1810	1.121
1811	1.408
1812	1.044
1813	1.677
1814	1.048
1815	1.248
1816	1.706
1817	0.872
1818	0.325
1819	0.389
1820	0.812
1821	0.949
1822	0.344
1823	0.599
1824	0.583
1825	0.714
1826	0.666
1827	1.319
1828	1.235
1829	1.255
1830	1.18
1831	0.908
1832	0.426
1833	1.348
1834	1.457
1835	1.421
1836	0.932
1837	1.175
1838	1.152
1839	1.667
1840	1.423
1841	1.093
1842	0.557
1843	0.62
1844	0.808
1845	1.094
1846	1.326
1847	0.702
1848	0.792
1849	1.868
1850	1.224
1851	0.482
1852	0.581
1853	1.164
1854	1.175
1855	1.186
1856	1.465
1857	1.252
1858	1.651
1859	0.422
1860	0.874
1861	0.6
1862	0.397
1863	0.677
1864	0.399
1865	0.955
1866	1.158
1867	1.115
1868	1.233
1869	1.574
1870	0.039
1871	0.985
1872	0.995
1873	0.356
1874	0.817
1875	0.722
1876	0.988
1877	1.018
1878	0.959
1879	0.698
1880	0.612
1881	1.372
1882	0.695
1883	0.471
1884	0.79
1885	1.09
1886	0.47
1887	1.088
1888	0.896
1889	0.786
1890	0.547
1891	0.932
1892	0.471
1893	0.309
1894	0.644
1895	0.669
1896	0.255
1897	1.352
1898	1.383
1899	0.869
1900	1.307
1901	1.559
1902	1.127
1903	1.748
1904	0.019
1905	2.029
1906	1.314
1907	1.596
1908	1.419
1909	0.783
1910	0.61
1911	1.195
1912	1.307
1913	0.847
1914	1.36
1915	1.431
1916	1.547
1917	1.181
1918	0.697
1919	1.651
1920	1.748
1921	1.171
1922	0.565
1923	0.314
1924	0.883
1925	-0.043
1926	0.799
1927	0.807
1928	0.719
1929	1.48
1930	0.966
1931	1.382
1932	1.594
1933	0.998
1934	-0.033
1935	1.235
1936	1.058
1937	1.136
1938	0.926
1939	1.021
1940	1.214
1941	1.486
1942	1.396
1943	1.214
1944	1.496
1945	1.042
1946	0.598
1947	0.729
1948	0.674
1949	0.95
1950	0.953
1951	0.888
1952	1.136
1953	0.991
1954	0.061
1955	1.451
1956	0.57
1957	0.651
1958	1.177
1959	0.756
1960	1.429
1961	0.734
1962	1.119
1963	0.689
1964	0.593
1965	0.674
1966	1.234
1967	1.248
1968	1.215
1969	0.971
1970	1.413
1971	0.566
1972	1.246
1973	1.552
1974	0.32
1975	1.545
1976	1.082
1977	0.639
1978	1.084
1979	1.406
1980	0.746
1981	0.984