# northamerica_usa_nm112 - 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/4976
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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_nm112 - 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_nm112B
#	Earliest_Year: 1704
#	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":"4.50285646766","T2":"15.8947212686","M1":"0.0227264154856","M2":"0.507149353323"}}
#--------------------
# 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
1704	0.739
1705	0.435
1706	0.968
1707	0.606
1708	1.285
1709	0.625
1710	1.367
1711	0.922
1712	1.648
1713	1.235
1714	1.196
1715	0.478
1716	0.684
1717	0.944
1718	1.125
1719	0.838
1720	1.733
1721	2.053
1722	1.719
1723	1.15
1724	1.191
1725	0.863
1726	1.247
1727	1.042
1728	1.048
1729	0.648
1730	0.829
1731	0.701
1732	0.795
1733	0.372
1734	1.133
1735	0.774
1736	0.754
1737	0.419
1738	0.841
1739	0.441
1740	0.845
1741	1.241
1742	0.786
1743	1.638
1744	1.385
1745	1.135
1746	1.866
1747	1.488
1748	0.483
1749	1.39
1750	0.671
1751	1.556
1752	0.3
1753	1.274
1754	1.094
1755	0.583
1756	0.72
1757	0.223
1758	0.973
1759	0.972
1760	0.661
1761	1.22
1762	1.484
1763	0.482
1764	1.082
1765	0.853
1766	1.198
1767	1.186
1768	1.071
1769	1.211
1770	0.843
1771	1.585
1772	0.746
1773	0.597
1774	0.75
1775	0.553
1776	0.998
1777	0.661
1778	0.673
1779	0.882
1780	0.565
1781	0.944
1782	0.943
1783	1.306
1784	1.912
1785	1.126
1786	0.977
1787	1.548
1788	1.039
1789	0.5
1790	0.926
1791	1.088
1792	0.852
1793	1.257
1794	0.909
1795	0.884
1796	0.634
1797	0.879
1798	0.865
1799	0.947
1800	1.107
1801	0.63
1802	0.872
1803	1.154
1804	0.904
1805	0.691
1806	0.586
1807	1.097
1808	1.076
1809	0.67
1810	0.824
1811	1.234
1812	0.87
1813	1.378
1814	1.044
1815	1.178
1816	1.482
1817	0.908
1818	0.444
1819	0.654
1820	0.803
1821	1.139
1822	0.445
1823	0.903
1824	0.666
1825	0.774
1826	0.696
1827	1.111
1828	0.944
1829	1.004
1830	1.132
1831	0.709
1832	0.499
1833	0.959
1834	1.315
1835	1.257
1836	0.783
1837	1.018
1838	1.233
1839	1.452
1840	1.276
1841	1.106
1842	0.544
1843	0.602
1844	0.903
1845	1.288
1846	1.725
1847	0.769
1848	0.928
1849	1.675
1850	1.264
1851	0.778
1852	1.243
1853	1.231
1854	1.477
1855	0.99
1856	1.268
1857	1.115
1858	1.597
1859	0.715
1860	1.134
1861	0.951
1862	0.578
1863	0.562
1864	0.446
1865	0.665
1866	1.053
1867	0.97
1868	1.353
1869	1.856
1870	0.686
1871	0.948
1872	1.226
1873	0.499
1874	0.855
1875	0.723
1876	0.742
1877	0.936
1878	1.145
1879	0.88
1880	0.498
1881	1.405
1882	0.709
1883	0.762
1884	0.734
1885	1.1
1886	0.714
1887	1.201
1888	1.251
1889	1.429
1890	0.71
1891	0.899
1892	0.553
1893	0.359
1894	0.576
1895	0.975
1896	0.461
1897	0.903
1898	1.588
1899	0.976
1900	1.075
1901	1.455
1902	0.682
1903	1.074
1904	0.228
1905	1.239
1906	1.133
1907	1.736
1908	2.175
1909	1.225
1910	0.525
1911	1.178
1912	1.393
1913	0.874
1914	1.402
1915	1.045
1916	1.249
1917	1.307
1918	0.465
1919	1.9
1920	1.915
1921	1.125
1922	0.673
1923	0.446
1924	0.988
1925	0.119
1926	0.884
1927	0.656
1928	1.028
1929	1.811
1930	1.14
1931	1.141
1932	2.235
1933	1.925
1934	0.273
1935	1.614
1936	1.277
1937	1.21
1938	0.917
1939	1.269
1940	1.428
1941	1.823
1942	1.574
1943	0.95
1944	1.365
1945	0.99
1946	0.519
1947	0.783
1948	0.82
1949	0.937
1950	0.767
1951	0.45
1952	0.749
1953	0.642
1954	0.091
1955	0.83
1956	0.227
1957	0.379
1958	0.631
1959	0.699
1960	0.995
1961	0.736
1962	0.855
1963	0.622
1964	0.58
1965	0.495
1966	0.786
1967	0.859
1968	0.974
1969	0.917
1970	0.989
1971	0.247
1972	1.111
1973	1.063
1974	0.319
1975	1.194
1976	0.886
1977	0.594
1978	0.841
1979	1.499
1980	0.818
1981	0.595