# northamerica_usa_nm040 - Ruidosa Ridge - 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/3099
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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
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# Title
#	Study_Name: northamerica_usa_nm040 - Ruidosa Ridge - Breitenmoser Tree Ring Chronology Data
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# 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.
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#	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: Ruidosa Ridge
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.53
#	Southernmost_Latitude: 35.53
#	Easternmost_Longitude: -105.57
#	Westernmost_Longitude: -105.57
#	Elevation: 2286 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm040B
#	Earliest_Year: 1743
#	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":"3.63325412632","T2":"14.7654796777","M1":"0.0234911122484","M2":"0.545117775553"}}
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# Species
#	Species_Name: pinyon pine
#	Species_Code: PIED
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# Chronology:
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# Variables
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# 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)
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##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
1743	1.145
1744	0.845
1745	0.969
1746	1.101
1747	1.214
1748	0.508
1749	1.091
1750	0.83
1751	1.401
1752	0.993
1753	1.226
1754	1.494
1755	1.062
1756	0.748
1757	0.679
1758	1.018
1759	1.12
1760	0.828
1761	1.413
1762	1.262
1763	0.959
1764	1.544
1765	0.96
1766	1.159
1767	0.96
1768	1.11
1769	1.098
1770	1.041
1771	1.19
1772	0.917
1773	0.521
1774	0.928
1775	0.832
1776	1.162
1777	1.017
1778	1.014
1779	0.808
1780	0.453
1781	0.672
1782	0.747
1783	1.282
1784	1.29
1785	0.901
1786	0.933
1787	1.084
1788	0.724
1789	0.719
1790	1.117
1791	1.283
1792	1.467
1793	1.506
1794	0.88
1795	1.011
1796	0.903
1797	0.921
1798	1.121
1799	1.277
1800	1.008
1801	0.557
1802	0.93
1803	0.964
1804	0.988
1805	0.961
1806	1.206
1807	1.16
1808	0.801
1809	0.932
1810	1.163
1811	0.848
1812	0.873
1813	1.14
1814	0.675
1815	1.201
1816	1.442
1817	1.134
1818	0.544
1819	0.824
1820	0.638
1821	1.198
1822	0.188
1823	0.914
1824	0.915
1825	1.12
1826	0.817
1827	1.34
1828	1.215
1829	1.083
1830	1.075
1831	0.919
1832	0.932
1833	1.211
1834	1.106
1835	0.656
1836	0.426
1837	1.069
1838	1.028
1839	1.278
1840	1.301
1841	1.339
1842	0.03
1843	0.922
1844	1.202
1845	1.01
1846	0.87
1847	0.43
1848	0.809
1849	1.464
1850	0.89
1851	0.432
1852	0.954
1853	1.015
1854	1.266
1855	1.219
1856	1.097
1857	1.191
1858	1.261
1859	0.659
1860	0.85
1861	0.454
1862	0.332
1863	0.903
1864	0.829
1865	1.236
1866	1.811
1867	1.467
1868	1.245
1869	1.36
1870	0.87
1871	0.805
1872	0.927
1873	0.43
1874	0.794
1875	0.864
1876	1.519
1877	1.209
1878	1.069
1879	1.076
1880	0.15
1881	1.129
1882	1.256
1883	0.619
1884	1.219
1885	1.29
1886	1.237
1887	1.679
1888	1.16
1889	0.78
1890	0.551
1891	0.918
1892	0.916
1893	0.249
1894	1.061
1895	1.028
1896	0.804
1897	1.609
1898	1.01
1899	0.407
1900	0.85
1901	1.342
1902	0.529
1903	1.224
1904	0.154
1905	1.487
1906	1.439
1907	1.598
1908	1.047
1909	1.198
1910	0.779
1911	1.084
1912	1.557
1913	0.846
1914	1.315
1915	1.25
1916	1.744
1917	1.162
1918	1.038
1919	1.685
1920	1.485
1921	1.286
1922	0.812
1923	1.304
1924	1.324
1925	0.13
1926	1.434
1927	0.853
1928	1.272
1929	1.204
1930	0.89
1931	0.735
1932	1.158
1933	1.096
1934	0.176
1935	1.221
1936	0.676
1937	0.998
1938	0.604
1939	0.833
1940	0.744
1941	1.457
1942	1.285
1943	1.054
1944	1.187
1945	0.905
1946	0.86
1947	1.172
1948	1.179
1949	1.576
1950	0.616
1951	0.229
1952	0.228
1953	0.314
1954	0.599
1955	0.46
1956	0.029
1957	0.711
1958	1.338
1959	1.352
1960	1.318
1961	1.228
1962	1.218
1963	1.109
1964	0.508
1965	0.572
1966	0.935
1967	0.568
1968	1.245
1969	1.42
1970	0.99
1971	0.563
1972	1.359