# northamerica_usa_nm032 - El Morro - 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.
#
#
# 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/3076
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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_nm032 - El Morro - 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.
#------------------
# 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
#------------------
# Site_Information
#	Site_Name: El Morro
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.03
#	Southernmost_Latitude: 35.03
#	Easternmost_Longitude: -108.35
#	Westernmost_Longitude: -108.35
#	Elevation: 2225 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_nm032B
#	Earliest_Year: 1666
#	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":"4.15078029302","T2":"16.4629444054","M1":"0.022791287969","M2":"0.487516188673"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1666	0.517
1667	0.502
1668	0.466
1669	0.797
1670	0.898
1671	1.093
1672	1.577
1673	1.109
1674	0.897
1675	1.422
1676	0.683
1677	1.1
1678	0.658
1679	1.227
1680	1.94
1681	1.357
1682	1.47
1683	1.609
1684	0.58
1685	0.126
1686	1.001
1687	1.082
1688	1.093
1689	1.14
1690	1.358
1691	1.19
1692	1.591
1693	1.674
1694	1.484
1695	1.355
1696	0.638
1697	1.044
1698	0.57
1699	1.371
1700	0.726
1701	0.968
1702	0.697
1703	0.777
1704	0.325
1705	0.983
1706	1.292
1707	0.735
1708	0.619
1709	1.092
1710	1.198
1711	1.127
1712	1.182
1713	0.91
1714	0.886
1715	0.919
1716	0.506
1717	0.881
1718	1.291
1719	1.068
1720	1.714
1721	1.084
1722	1.403
1723	1.603
1724	0.655
1725	1.209
1726	1.387
1727	1.078
1728	0.2
1729	0.536
1730	1.164
1731	1.279
1732	1.446
1733	0.592
1734	1.257
1735	0.279
1736	1.295
1737	0.954
1738	1.262
1739	0.25
1740	0.799
1741	1.292
1742	1.184
1743	1.601
1744	0.652
1745	1.652
1746	1.736
1747	1.563
1748	0.259
1749	1.574
1750	0.73
1751	1.053
1752	0.553
1753	0.694
1754	1.25
1755	0.227
1756	0.275
1757	0.606
1758	0.961
1759	1.283
1760	0.923
1761	0.784
1762	1.188
1763	0.445
1764	0.93
1765	0.599
1766	0.828
1767	0.504
1768	0.934
1769	0.576
1770	0.959
1771	1.264
1772	0.499
1773	0.295
1774	0.955
1775	0.528
1776	0.78
1777	0.532
1778	0.65
1779	0.75
1780	0.566
1781	1.0
1782	0.686
1783	1.663
1784	1.935
1785	1.169
1786	1.104
1787	1.857
1788	0.928
1789	1.129
1790	0.969
1791	1.57
1792	1.611
1793	1.742
1794	1.204
1795	1.326
1796	0.907
1797	0.815
1798	0.823
1799	1.1
1800	0.582
1801	0.536
1802	0.727
1803	0.648
1804	1.345
1805	0.622
1806	-0.009
1807	1.313
1808	1.169
1809	1.269
1810	0.893
1811	1.161
1812	0.522
1813	1.113
1814	1.159
1815	1.243
1816	1.789
1817	1.45
1818	0.846
1819	0.258
1820	0.674
1821	1.041
1822	0.198
1823	0.412
1824	0.77
1825	1.033
1826	0.717
1827	1.028
1828	1.443
1829	0.462
1830	0.96
1831	1.115
1832	0.731
1833	1.381
1834	0.872
1835	0.747
1836	0.786
1837	0.846
1838	1.197
1839	1.576
1840	1.568
1841	1.358
1842	1.113
1843	0.56
1844	1.584
1845	0.842
1846	1.203
1847	-0.009
1848	1.153
1849	1.432
1850	1.008
1851	0.808
1852	0.918
1853	0.807
1854	0.822
1855	1.207
1856	1.104
1857	1.098
1858	1.164
1859	0.898
1860	0.781
1861	0.296
1862	0.911
1863	0.62
1864	0.256
1865	0.904
1866	1.179
1867	1.309
1868	1.565
1869	1.193
1870	1.195
1871	0.393
1872	0.193
1873	0.368
1874	1.05
1875	0.626
1876	0.646
1877	0.993
1878	0.746
1879	0.457
1880	0.182
1881	0.615
1882	0.949
1883	0.785
1884	1.008
1885	1.229
1886	0.646
1887	0.551
1888	1.111
1889	0.813
1890	0.0
1891	0.944
1892	0.942
1893	0.798
1894	0.558
1895	1.814
1896	0.826
1897	1.143
1898	1.249
1899	0.262
1900	0.197
1901	1.02
1902	0.855
1903	0.719
1904	0.241
1905	1.781
1906	1.744
1907	2.198
1908	1.898
1909	1.153
1910	1.173
1911	1.618
1912	1.597
1913	1.046
1914	1.52
1915	1.58
1916	1.473
1917	1.26
1918	1.005
1919	1.652
1920	1.829
1921	0.854
1922	0.657
1923	0.605
1924	0.85
1925	0.677
1926	1.058
1927	1.404
1928	0.934
1929	1.0
1930	1.247
1931	0.827
1932	1.334
1933	0.932
1934	1.097
1935	1.264
1936	1.094
1937	1.507
1938	1.061
1939	0.917
1940	1.275
1941	1.832
1942	1.287
1943	1.337
1944	0.948
1945	1.125
1946	0.799
1947	0.779
1948	1.657
1949	1.22
1950	0.9
1951	0.261
1952	0.784
1953	0.483
1954	0.741
1955	0.458
1956	0.63
1957	0.692
1958	0.905
1959	0.186
1960	1.285
1961	0.69
1962	1.035
1963	1.276
1964	1.045
1965	1.555
1966	1.163
1967	0.403
1968	1.197
1969	1.22
1970	0.828
1971	0.392
1972	0.677