# northamerica_usa_nm028 - Mount Taylor - 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/3086
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_nm028 - Mount Taylor - 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: Mount Taylor
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.23
#	Southernmost_Latitude: 35.23
#	Easternmost_Longitude: -107.68
#	Westernmost_Longitude: -107.68
#	Elevation: 2347 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm028B
#	Earliest_Year: 1740
#	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":"3.9880013358","T2":"16.4915276567","M1":"0.0235414250065","M2":"0.49061384119"}}
#--------------------
# 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
1740	0.808
1741	0.72
1742	0.392
1743	1.002
1744	0.864
1745	1.092
1746	1.749
1747	1.439
1748	0.393
1749	1.28
1750	0.991
1751	1.752
1752	0.66
1753	1.192
1754	1.432
1755	0.748
1756	0.788
1757	0.754
1758	1.196
1759	1.277
1760	0.896
1761	1.047
1762	0.844
1763	0.568
1764	1.007
1765	1.12
1766	1.165
1767	1.309
1768	1.294
1769	1.09
1770	1.118
1771	1.576
1772	1.261
1773	0.752
1774	0.619
1775	0.599
1776	0.586
1777	0.723
1778	1.146
1779	0.617
1780	0.371
1781	0.807
1782	0.837
1783	1.091
1784	1.566
1785	1.012
1786	0.952
1787	1.206
1788	0.885
1789	0.948
1790	1.303
1791	1.506
1792	1.391
1793	2.111
1794	1.359
1795	1.161
1796	0.913
1797	0.807
1798	1.062
1799	1.13
1800	1.191
1801	0.994
1802	0.931
1803	1.18
1804	0.921
1805	1.089
1806	0.616
1807	1.104
1808	0.885
1809	1.113
1810	0.944
1811	1.232
1812	0.785
1813	0.839
1814	0.695
1815	1.118
1816	1.635
1817	1.143
1818	0.693
1819	1.031
1820	0.829
1821	0.645
1822	0.329
1823	0.526
1824	0.398
1825	0.801
1826	0.279
1827	0.744
1828	1.179
1829	0.413
1830	1.291
1831	1.167
1832	1.306
1833	1.397
1834	1.242
1835	1.19
1836	1.1
1837	1.019
1838	1.237
1839	1.583
1840	1.285
1841	1.582
1842	0.46
1843	0.627
1844	1.304
1845	0.993
1846	1.288
1847	0.604
1848	1.224
1849	1.231
1850	0.965
1851	0.715
1852	1.083
1853	0.842
1854	0.807
1855	1.017
1856	0.729
1857	0.494
1858	1.127
1859	0.384
1860	0.979
1861	0.283
1862	0.424
1863	0.741
1864	0.72
1865	0.646
1866	1.152
1867	1.132
1868	1.624
1869	1.61
1870	1.309
1871	1.019
1872	1.293
1873	0.806
1874	1.003
1875	1.034
1876	0.968
1877	1.5
1878	0.981
1879	0.638
1880	0.339
1881	0.558
1882	1.12
1883	0.429
1884	0.894
1885	1.098
1886	0.754
1887	1.244
1888	0.866
1889	0.777
1890	0.915
1891	0.918
1892	0.626
1893	0.528
1894	0.46
1895	0.893
1896	0.3
1897	1.183
1898	1.027
1899	0.289
1900	0.596
1901	0.851
1902	0.529
1903	1.136
1904	0.327
1905	1.458
1906	1.009
1907	1.706
1908	1.777
1909	1.323
1910	1.452
1911	1.83
1912	1.483
1913	0.81
1914	1.556
1915	1.605
1916	1.255
1917	1.438
1918	0.9
1919	1.407
1920	1.398
1921	1.046
1922	0.689
1923	0.818
1924	1.145
1925	0.158
1926	1.303
1927	1.071
1928	0.874
1929	0.851
1930	1.492
1931	1.325
1932	1.245
1933	1.151
1934	0.904
1935	1.497
1936	1.397
1937	1.203
1938	0.838
1939	0.771
1940	1.084
1941	1.7
1942	0.759
1943	0.65
1944	0.968
1945	0.804
1946	0.461
1947	0.959
1948	0.877
1949	1.127
1950	0.614
1951	0.45
1952	0.697
1953	0.65
1954	0.648
1955	0.684
1956	0.708
1957	0.755
1958	0.698
1959	0.357
1960	0.774
1961	0.941
1962	0.802
1963	0.61
1964	1.006
1965	1.37
1966	0.71
1967	0.725
1968	0.877
1969	0.974
1970	1.495
1971	1.382
1972	1.733