# northamerica_usa_mt109 - Grass Mountain #2 - 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.
#
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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/3314
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_mt109 - Grass Mountain #2 - 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: Grass Mountain #2
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.17
#	Southernmost_Latitude: 45.17
#	Easternmost_Longitude: -109.52
#	Westernmost_Longitude: -109.52
#	Elevation: 3208 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mt109B
#	Earliest_Year: 1723
#	Most_Recent_Year: 1999
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"6.25224137616","T2":"19.6661300749","M1":"0.022153654093","M2":"0.295109489267"}}
#--------------------
# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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
1723	0.878
1724	1.097
1725	0.925
1726	1.011
1727	1.143
1728	1.266
1729	1.277
1730	1.41
1731	1.126
1732	1.017
1733	1.068
1734	1.062
1735	0.944
1736	0.953
1737	0.806
1738	0.901
1739	1.119
1740	0.844
1741	0.821
1742	1.118
1743	1.021
1744	0.896
1745	0.839
1746	0.649
1747	0.818
1748	0.934
1749	0.832
1750	0.971
1751	1.283
1752	0.889
1753	0.849
1754	0.803
1755	1.012
1756	1.281
1757	1.195
1758	0.812
1759	1.119
1760	0.945
1761	0.801
1762	1.185
1763	1.133
1764	1.067
1765	0.95
1766	0.8
1767	0.788
1768	0.982
1769	0.837
1770	0.776
1771	0.963
1772	1.099
1773	1.245
1774	1.207
1775	1.022
1776	1.1
1777	1.061
1778	1.072
1779	0.759
1780	0.946
1781	1.078
1782	0.848
1783	1.109
1784	1.188
1785	0.953
1786	1.12
1787	0.804
1788	0.945
1789	0.751
1790	0.813
1791	0.668
1792	0.728
1793	0.739
1794	0.995
1795	1.039
1796	1.016
1797	0.948
1798	1.177
1799	0.958
1800	0.932
1801	0.972
1802	1.107
1803	0.842
1804	1.068
1805	0.941
1806	0.831
1807	0.968
1808	1.162
1809	0.774
1810	0.95
1811	1.302
1812	1.332
1813	1.127
1814	0.88
1815	1.022
1816	0.948
1817	1.02
1818	1.123
1819	1.29
1820	1.016
1821	1.045
1822	0.921
1823	0.89
1824	0.916
1825	1.0
1826	1.021
1827	0.938
1828	1.095
1829	1.316
1830	1.073
1831	1.034
1832	0.763
1833	1.138
1834	0.887
1835	0.945
1836	0.844
1837	1.069
1838	0.716
1839	0.887
1840	0.956
1841	1.142
1842	0.999
1843	1.17
1844	1.078
1845	0.943
1846	1.233
1847	1.086
1848	1.143
1849	1.086
1850	1.279
1851	1.049
1852	0.908
1853	0.826
1854	1.062
1855	0.913
1856	0.973
1857	1.005
1858	0.926
1859	1.178
1860	0.952
1861	1.084
1862	0.899
1863	1.107
1864	0.945
1865	0.871
1866	0.962
1867	0.973
1868	0.912
1869	0.862
1870	0.957
1871	1.097
1872	0.58
1873	1.263
1874	1.194
1875	0.88
1876	0.909
1877	0.865
1878	1.034
1879	0.411
1880	0.423
1881	0.577
1882	0.473
1883	0.326
1884	0.57
1885	0.748
1886	0.898
1887	0.758
1888	1.042
1889	0.949
1890	0.945
1891	0.805
1892	0.965
1893	1.086
1894	0.845
1895	0.711
1896	1.072
1897	0.914
1898	1.017
1899	0.623
1900	1.043
1901	0.922
1902	0.676
1903	0.883
1904	0.836
1905	0.817
1906	0.782
1907	0.809
1908	1.082
1909	1.097
1910	1.042
1911	0.907
1912	1.086
1913	1.103
1914	1.335
1915	0.768
1916	1.2
1917	1.025
1918	1.092
1919	1.093
1920	1.083
1921	1.209
1922	1.045
1923	0.973
1924	0.695
1925	1.282
1926	1.009
1927	1.137
1928	1.054
1929	1.45
1930	1.272
1931	1.348
1932	1.433
1933	1.314
1934	0.758
1935	0.938
1936	0.899
1937	0.78
1938	0.804
1939	1.009
1940	1.21
1941	1.058
1942	0.972
1943	1.094
1944	1.064
1945	1.219
1946	1.171
1947	1.089
1948	1.056
1949	1.118
1950	0.945
1951	1.158
1952	1.018
1953	1.345
1954	1.139
1955	1.019
1956	0.832
1957	1.019
1958	0.664
1959	1.068
1960	0.793
1961	0.83
1962	0.73
1963	1.099
1964	1.27
1965	1.088
1966	1.243
1967	1.124
1968	1.056
1969	0.804
1970	1.177
1971	0.92
1972	0.842
1973	1.201
1974	1.089
1975	0.973
1976	1.181
1977	0.992
1978	0.963
1979	1.105
1980	1.009
1981	0.892
1982	0.839
1983	0.985
1984	1.164
1985	0.91
1986	0.921
1987	0.885
1988	1.505
1989	1.21
1990	1.067
1991	1.026
1992	0.614
1993	0.515
1994	1.039
1995	0.99
1996	0.913
1997	0.845
1998	0.924
1999	0.943