# northamerica_usa_co560 - Wilson Ranch - 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/4282
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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_co560 - Wilson Ranch - 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.
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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: Wilson Ranch
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.63
#	Southernmost_Latitude: 37.63
#	Easternmost_Longitude: -106.68
#	Westernmost_Longitude: -106.68
#	Elevation: 2560 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co560B
#	Earliest_Year: 1765
#	Most_Recent_Year: 1997
#	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":"2.42028591032","T2":"12.6202938765","M1":"0.0234127989214","M2":"0.605241032073"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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)
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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
1765	1.123
1766	1.309
1767	1.324
1768	1.295
1769	1.067
1770	1.101
1771	1.347
1772	1.23
1773	0.594
1774	1.288
1775	1.02
1776	0.968
1777	1.032
1778	0.726
1779	0.564
1780	0.235
1781	0.639
1782	0.568
1783	0.983
1784	1.397
1785	0.538
1786	0.955
1787	1.139
1788	0.962
1789	0.936
1790	1.182
1791	1.196
1792	0.991
1793	1.135
1794	0.82
1795	0.986
1796	0.586
1797	0.716
1798	0.736
1799	0.985
1800	1.068
1801	0.944
1802	0.891
1803	0.93
1804	0.881
1805	0.653
1806	0.441
1807	0.475
1808	0.71
1809	0.777
1810	0.987
1811	0.936
1812	0.708
1813	0.722
1814	0.784
1815	0.788
1816	0.911
1817	0.696
1818	0.649
1819	0.636
1820	0.664
1821	0.885
1822	0.673
1823	0.681
1824	0.648
1825	1.002
1826	1.183
1827	1.225
1828	1.285
1829	0.609
1830	0.738
1831	1.25
1832	1.299
1833	1.273
1834	1.165
1835	1.353
1836	1.163
1837	1.208
1838	0.907
1839	0.982
1840	1.064
1841	1.14
1842	0.698
1843	1.063
1844	1.221
1845	0.806
1846	0.595
1847	0.471
1848	0.678
1849	0.965
1850	0.967
1851	0.787
1852	1.15
1853	1.356
1854	1.369
1855	1.198
1856	1.097
1857	1.259
1858	1.327
1859	0.947
1860	1.479
1861	0.864
1862	1.07
1863	1.381
1864	1.047
1865	0.811
1866	1.161
1867	1.335
1868	1.396
1869	1.282
1870	0.957
1871	0.603
1872	0.578
1873	0.441
1874	0.726
1875	0.771
1876	1.014
1877	0.967
1878	1.06
1879	0.595
1880	0.867
1881	1.004
1882	0.845
1883	0.831
1884	1.346
1885	1.923
1886	1.503
1887	1.848
1888	1.712
1889	1.597
1890	1.144
1891	1.141
1892	1.482
1893	0.909
1894	1.101
1895	1.488
1896	0.729
1897	0.852
1898	1.288
1899	0.383
1900	0.596
1901	0.609
1902	0.251
1903	1.074
1904	0.543
1905	1.348
1906	1.136
1907	2.272
1908	1.695
1909	1.479
1910	1.396
1911	1.268
1912	1.046
1913	0.764
1914	1.147
1915	1.027
1916	1.137
1917	1.254
1918	1.35
1919	1.371
1920	0.946
1921	1.003
1922	1.0
1923	0.982
1924	1.305
1925	1.279
1926	0.789
1927	1.174
1928	0.963
1929	1.159
1930	0.953
1931	0.905
1932	1.012
1933	0.649
1934	0.735
1935	0.949
1936	0.629
1937	0.721
1938	0.914
1939	0.677
1940	0.451
1941	1.074
1942	0.974
1943	1.034
1944	0.925
1945	1.106
1946	0.578
1947	0.813
1948	0.921
1949	1.143
1950	0.877
1951	0.484
1952	1.06
1953	0.859
1954	0.328
1955	0.248
1956	0.35
1957	0.651
1958	0.619
1959	0.504
1960	0.923
1961	0.814
1962	0.884
1963	0.422
1964	0.794
1965	1.24
1966	1.224
1967	0.929
1968	1.129
1969	1.411
1970	1.059
1971	0.772
1972	0.784
1973	0.926
1974	0.87
1975	1.036
1976	1.217
1977	0.361
1978	0.502
1979	0.703
1980	0.909
1981	0.675
1982	0.901
1983	1.205
1984	1.044
1985	1.18
1986	1.47
1987	1.332
1988	0.912
1989	1.209
1990	1.178
1991	1.172
1992	1.409
1993	1.121
1994	1.01
1995	1.571
1996	0.79
1997	1.217