# northamerica_usa_az511 - Mount Graham Pinaleno Mountains - 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.
#
#
# Online_Resource:
#
# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3433
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_az511 - Mount Graham Pinaleno Mountains - 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.
#------------------
# 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
#------------------
# Site_Information
#	Site_Name: Mount Graham Pinaleno Mountains
#	Location:
#	Country: United States
#	Northernmost_Latitude: 32.7
#	Southernmost_Latitude: 32.7
#	Easternmost_Longitude: -109.87
#	Westernmost_Longitude: -109.87
#	Elevation: 3221 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_az511B
#	Earliest_Year: 1736
#	Most_Recent_Year: 1990
#	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":"4.57755149755","T2":"17.1855899085","M1":"0.0226580372854","M2":"0.405556100129"}}
#--------------------
# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
#--------------------
# Chronology:
#
#
#
#--------------------
# 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
1736	0.873
1737	0.923
1738	0.999
1739	0.77
1740	0.786
1741	1.148
1742	1.056
1743	1.142
1744	1.147
1745	1.329
1746	1.312
1747	1.144
1748	0.5
1749	1.109
1750	1.009
1751	0.999
1752	0.509
1753	0.783
1754	0.774
1755	0.667
1756	0.928
1757	0.768
1758	0.891
1759	0.914
1760	0.841
1761	0.762
1762	0.859
1763	0.715
1764	1.038
1765	0.927
1766	0.671
1767	0.864
1768	0.984
1769	1.032
1770	1.193
1771	1.003
1772	0.918
1773	0.743
1774	0.727
1775	0.859
1776	0.841
1777	0.767
1778	0.795
1779	0.92
1780	0.997
1781	0.948
1782	0.771
1783	1.254
1784	1.281
1785	0.913
1786	0.871
1787	1.082
1788	0.804
1789	0.747
1790	0.987
1791	1.179
1792	1.159
1793	1.275
1794	1.014
1795	1.058
1796	1.238
1797	1.01
1798	0.764
1799	1.209
1800	0.815
1801	0.799
1802	1.127
1803	0.871
1804	1.295
1805	1.106
1806	1.16
1807	1.182
1808	1.135
1809	1.386
1810	1.389
1811	1.435
1812	1.41
1813	1.148
1814	1.62
1815	1.379
1816	1.187
1817	0.998
1818	1.017
1819	0.801
1820	0.847
1821	0.934
1822	0.632
1823	0.608
1824	0.999
1825	0.821
1826	0.835
1827	0.859
1828	0.961
1829	1.013
1830	0.945
1831	1.055
1832	1.175
1833	1.365
1834	1.196
1835	1.082
1836	0.948
1837	1.196
1838	1.06
1839	1.329
1840	1.232
1841	0.804
1842	0.772
1843	0.783
1844	0.883
1845	0.875
1846	1.23
1847	0.955
1848	0.859
1849	1.123
1850	1.223
1851	0.671
1852	1.433
1853	1.104
1854	1.068
1855	0.741
1856	1.061
1857	0.726
1858	1.277
1859	1.073
1860	1.027
1861	0.842
1862	1.009
1863	0.611
1864	0.857
1865	0.968
1866	1.187
1867	1.296
1868	1.077
1869	1.155
1870	0.892
1871	0.747
1872	0.732
1873	0.78
1874	0.957
1875	0.849
1876	0.8
1877	0.909
1878	0.879
1879	0.51
1880	0.936
1881	0.831
1882	0.979
1883	0.968
1884	0.915
1885	0.966
1886	0.789
1887	0.919
1888	0.973
1889	1.208
1890	0.966
1891	0.901
1892	0.716
1893	0.743
1894	0.679
1895	0.845
1896	0.693
1897	0.819
1898	1.306
1899	1.062
1900	0.716
1901	0.858
1902	0.864
1903	1.115
1904	0.276
1905	1.113
1906	0.987
1907	1.157
1908	1.36
1909	1.39
1910	1.0
1911	1.307
1912	1.101
1913	1.095
1914	1.236
1915	1.133
1916	1.273
1917	1.475
1918	1.03
1919	1.13
1920	1.358
1921	1.005
1922	1.011
1923	0.883
1924	1.058
1925	0.47
1926	1.07
1927	1.364
1928	0.818
1929	0.881
1930	1.092
1931	1.001
1932	1.27
1933	1.448
1934	0.903
1935	1.297
1936	1.079
1937	1.091
1938	0.977
1939	0.612
1940	0.986
1941	0.968
1942	0.834
1943	0.895
1944	1.035
1945	0.909
1946	0.736
1947	0.815
1948	0.677
1949	1.274
1950	0.852
1951	0.658
1952	1.12
1953	0.914
1954	0.827
1955	1.125
1956	0.809
1957	1.071
1958	1.14
1959	0.819
1960	0.914
1961	0.519
1962	0.756
1963	0.56
1964	0.818
1965	1.088
1966	1.276
1967	1.107
1968	1.249
1969	1.075
1970	1.142
1971	0.635
1972	0.488
1973	1.041
1974	0.744
1975	1.114
1976	0.977
1977	1.156
1978	0.959
1979	1.167
1980	1.061
1981	1.017
1982	1.115
1983	1.166
1984	0.862
1985	1.135
1986	1.246
1987	1.2
1988	1.313
1989	0.866
1990	1.2