# northamerica_usa_az527 - Muletank - 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/3385
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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_az527 - Muletank - 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: Muletank
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.32
#	Southernmost_Latitude: 34.32
#	Easternmost_Longitude: -110.77
#	Westernmost_Longitude: -110.77
#	Elevation: 2362 m
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# Data_Collection
#	Collection_Name: northamerica_usa_az527B
#	Earliest_Year: 1756
#	Most_Recent_Year: 1986
#	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":"4.31716178383","T2":"16.4463853094","M1":"0.0229474646316","M2":"0.455151063679"}}
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# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1756	0.881
1757	1.067
1758	1.211
1759	1.14
1760	0.796
1761	0.771
1762	0.979
1763	0.748
1764	1.057
1765	0.681
1766	0.731
1767	0.805
1768	0.788
1769	0.817
1770	0.981
1771	1.062
1772	1.038
1773	0.341
1774	0.789
1775	0.942
1776	0.836
1777	1.143
1778	1.173
1779	0.932
1780	0.893
1781	0.833
1782	0.715
1783	1.136
1784	1.279
1785	0.503
1786	0.855
1787	1.063
1788	0.836
1789	1.023
1790	1.312
1791	1.203
1792	1.214
1793	1.181
1794	1.073
1795	0.769
1796	0.779
1797	0.939
1798	0.765
1799	1.108
1800	0.957
1801	0.933
1802	1.155
1803	1.039
1804	1.061
1805	1.154
1806	0.996
1807	0.905
1808	0.948
1809	1.009
1810	1.058
1811	1.103
1812	1.072
1813	0.841
1814	1.103
1815	1.063
1816	0.983
1817	0.771
1818	0.692
1819	0.788
1820	0.453
1821	0.815
1822	0.751
1823	0.76
1824	0.893
1825	0.69
1826	1.137
1827	1.245
1828	1.183
1829	0.881
1830	1.305
1831	0.901
1832	1.234
1833	1.106
1834	0.91
1835	1.103
1836	1.036
1837	0.97
1838	0.969
1839	1.172
1840	1.16
1841	0.498
1842	0.815
1843	0.86
1844	1.011
1845	0.578
1846	0.846
1847	0.277
1848	0.958
1849	0.936
1850	1.02
1851	1.06
1852	1.383
1853	1.44
1854	1.39
1855	1.176
1856	1.232
1857	1.044
1858	1.219
1859	0.844
1860	1.031
1861	0.877
1862	1.057
1863	1.151
1864	0.695
1865	1.017
1866	1.42
1867	1.009
1868	1.304
1869	1.13
1870	1.193
1871	0.502
1872	0.928
1873	0.933
1874	0.869
1875	1.208
1876	1.01
1877	0.905
1878	1.151
1879	0.828
1880	0.799
1881	0.91
1882	0.885
1883	0.886
1884	0.854
1885	1.094
1886	0.819
1887	0.538
1888	0.899
1889	0.838
1890	1.068
1891	0.907
1892	0.9
1893	1.18
1894	1.128
1895	1.073
1896	1.234
1897	1.23
1898	1.23
1899	1.134
1900	0.945
1901	1.17
1902	0.719
1903	1.421
1904	0.493
1905	1.072
1906	1.151
1907	1.468
1908	1.651
1909	1.475
1910	1.094
1911	1.474
1912	1.163
1913	1.05
1914	1.13
1915	1.131
1916	1.345
1917	1.222
1918	1.227
1919	1.017
1920	1.11
1921	1.165
1922	1.189
1923	1.089
1924	1.182
1925	1.234
1926	1.019
1927	1.214
1928	1.076
1929	1.062
1930	1.17
1931	0.966
1932	0.776
1933	0.926
1934	0.92
1935	0.88
1936	0.72
1937	0.619
1938	0.721
1939	0.548
1940	0.714
1941	0.858
1942	0.975
1943	0.87
1944	0.816
1945	0.925
1946	0.758
1947	0.845
1948	0.908
1949	0.991
1950	0.912
1951	0.756
1952	1.006
1953	1.153
1954	1.132
1955	1.037
1956	0.917
1957	1.031
1958	0.963
1959	0.977
1960	0.917
1961	0.929
1962	0.867
1963	0.918
1964	0.965
1965	1.143
1966	1.021
1967	1.421
1968	0.877
1969	1.226
1970	1.251
1971	1.061
1972	0.991
1973	0.892
1974	0.613
1975	1.018
1976	1.369
1977	0.937
1978	1.017
1979	0.835
1980	0.749
1981	0.939
1982	0.74
1983	1.014
1984	0.503
1985	0.676
1986	0.854