# northamerica_usa_nm027 - Canyon Lobo - 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/3066
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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_nm027 - Canyon Lobo - 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: Canyon Lobo
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.23
#	Southernmost_Latitude: 35.23
#	Easternmost_Longitude: -107.68
#	Westernmost_Longitude: -107.68
#	Elevation: 2438 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm027B
#	Earliest_Year: 1693
#	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":"4.31032270814","T2":"16.4256059742","M1":"0.0237099839259","M2":"0.463875803286"}}
#--------------------
# 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
1693	1.15
1694	1.309
1695	0.867
1696	0.691
1697	0.749
1698	0.668
1699	0.971
1700	0.749
1701	0.807
1702	0.862
1703	0.965
1704	0.92
1705	0.971
1706	1.167
1707	0.883
1708	1.067
1709	0.979
1710	1.045
1711	0.787
1712	1.023
1713	0.961
1714	1.058
1715	0.836
1716	0.973
1717	0.959
1718	1.091
1719	0.618
1720	1.211
1721	1.143
1722	1.57
1723	1.232
1724	1.38
1725	1.51
1726	1.695
1727	0.887
1728	1.152
1729	1.196
1730	1.012
1731	1.069
1732	1.057
1733	0.789
1734	1.143
1735	0.478
1736	0.983
1737	0.674
1738	0.94
1739	1.013
1740	0.865
1741	0.998
1742	0.877
1743	1.159
1744	0.933
1745	1.335
1746	1.303
1747	1.08
1748	0.391
1749	1.078
1750	0.769
1751	1.422
1752	0.999
1753	1.087
1754	1.145
1755	0.726
1756	0.711
1757	0.901
1758	1.041
1759	1.131
1760	0.99
1761	1.021
1762	0.893
1763	0.569
1764	0.771
1765	0.764
1766	0.859
1767	1.036
1768	0.992
1769	0.825
1770	0.958
1771	1.153
1772	0.999
1773	0.825
1774	0.66
1775	0.634
1776	0.631
1777	0.614
1778	1.081
1779	0.855
1780	0.614
1781	0.969
1782	1.008
1783	1.162
1784	1.436
1785	1.194
1786	0.941
1787	1.072
1788	0.941
1789	0.975
1790	1.197
1791	1.202
1792	1.109
1793	1.553
1794	1.196
1795	0.964
1796	0.909
1797	0.902
1798	0.997
1799	1.19
1800	1.195
1801	0.874
1802	0.896
1803	1.096
1804	0.966
1805	0.932
1806	0.618
1807	1.022
1808	0.959
1809	1.058
1810	1.183
1811	1.327
1812	1.005
1813	0.979
1814	0.983
1815	1.105
1816	1.469
1817	1.401
1818	0.937
1819	1.143
1820	0.905
1821	0.737
1822	0.45
1823	0.529
1824	0.427
1825	0.832
1826	0.605
1827	0.915
1828	1.361
1829	0.717
1830	1.262
1831	1.239
1832	1.277
1833	1.452
1834	1.114
1835	1.263
1836	1.121
1837	1.156
1838	1.252
1839	1.536
1840	1.411
1841	1.645
1842	0.775
1843	0.854
1844	1.318
1845	1.049
1846	1.163
1847	0.638
1848	1.206
1849	1.469
1850	1.055
1851	0.681
1852	1.154
1853	1.065
1854	0.92
1855	1.198
1856	0.892
1857	0.518
1858	1.1
1859	0.448
1860	0.834
1861	0.432
1862	0.736
1863	0.895
1864	0.915
1865	0.809
1866	1.276
1867	1.441
1868	1.677
1869	1.682
1870	1.378
1871	1.079
1872	1.34
1873	0.769
1874	1.034
1875	0.959
1876	0.868
1877	1.245
1878	0.806
1879	0.555
1880	0.564
1881	0.42
1882	1.058
1883	0.722
1884	0.938
1885	1.063
1886	0.739
1887	1.267
1888	0.989
1889	1.084
1890	1.017
1891	1.09
1892	0.889
1893	0.712
1894	0.605
1895	1.026
1896	0.389
1897	1.149
1898	1.085
1899	0.291
1900	0.737
1901	1.101
1902	0.413
1903	1.201
1904	0.388
1905	1.296
1906	1.054
1907	1.435
1908	1.499
1909	1.413
1910	1.521
1911	1.425
1912	1.332
1913	0.924
1914	1.231
1915	1.416
1916	1.211
1917	1.373
1918	0.821
1919	1.466
1920	1.602
1921	0.844
1922	0.504
1923	0.482
1924	0.818
1925	-0.029
1926	1.087
1927	0.943
1928	0.751
1929	0.681
1930	1.247
1931	1.134
1932	1.242
1933	1.064
1934	0.865
1935	1.408
1936	1.473
1937	1.212
1938	0.951
1939	0.834
1940	1.083
1941	1.483
1942	0.945
1943	0.783
1944	0.986
1945	0.829
1946	0.448
1947	0.922
1948	0.77
1949	1.178
1950	0.593
1951	0.382
1952	0.921
1953	0.58
1954	0.765
1955	0.636
1956	0.553
1957	0.768
1958	0.83
1959	0.43
1960	0.834
1961	0.897
1962	0.752
1963	0.74
1964	1.091
1965	1.305
1966	0.73
1967	0.616
1968	0.879
1969	0.802
1970	1.312
1971	1.011
1972	1.264