# northamerica_usa_wy024 - Granite Pass   Hunt Mountain - 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:
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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/2820
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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_wy024 - Granite Pass   Hunt Mountain - 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: Granite Pass   Hunt Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 44.78
#	Southernmost_Latitude: 44.78
#	Easternmost_Longitude: -107.87
#	Westernmost_Longitude: -107.87
#	Elevation: 2820 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wy024B
#	Earliest_Year: 1708
#	Most_Recent_Year: 1983
#	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":"4.83685409122","T2":"17.4628021007","M1":"0.0226428008634","M2":"0.413435791727"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1708	0.971
1709	1.311
1710	1.071
1711	0.87
1712	1.043
1713	1.261
1714	1.003
1715	0.923
1716	0.891
1717	1.108
1718	1.061
1719	0.87
1720	0.903
1721	1.162
1722	0.972
1723	0.825
1724	1.177
1725	0.851
1726	1.039
1727	1.0
1728	1.065
1729	1.178
1730	1.346
1731	1.253
1732	1.111
1733	1.205
1734	1.124
1735	1.096
1736	1.264
1737	1.157
1738	1.313
1739	1.454
1740	0.963
1741	0.952
1742	1.309
1743	1.179
1744	0.969
1745	0.608
1746	0.465
1747	0.506
1748	0.561
1749	0.61
1750	0.948
1751	1.367
1752	1.006
1753	0.851
1754	0.703
1755	1.011
1756	1.238
1757	1.292
1758	1.053
1759	1.396
1760	1.147
1761	0.834
1762	1.106
1763	1.054
1764	0.923
1765	1.335
1766	1.032
1767	0.947
1768	1.087
1769	0.81
1770	0.946
1771	1.051
1772	1.14
1773	1.362
1774	1.124
1775	1.05
1776	1.031
1777	1.049
1778	1.042
1779	0.842
1780	1.053
1781	1.058
1782	0.981
1783	0.988
1784	1.149
1785	0.936
1786	0.995
1787	0.829
1788	1.087
1789	0.905
1790	0.931
1791	0.843
1792	1.114
1793	1.058
1794	1.052
1795	1.123
1796	1.06
1797	1.033
1798	1.161
1799	1.027
1800	1.007
1801	1.05
1802	1.206
1803	0.957
1804	1.319
1805	0.846
1806	0.82
1807	1.057
1808	1.044
1809	0.625
1810	0.779
1811	1.102
1812	1.042
1813	0.92
1814	0.736
1815	0.969
1816	0.946
1817	0.903
1818	0.844
1819	1.024
1820	0.909
1821	1.164
1822	1.009
1823	0.926
1824	1.023
1825	0.901
1826	1.103
1827	1.117
1828	1.225
1829	1.134
1830	1.032
1831	1.159
1832	0.85
1833	1.117
1834	0.878
1835	0.8
1836	0.648
1837	0.899
1838	0.576
1839	0.82
1840	0.937
1841	1.305
1842	0.911
1843	1.097
1844	0.818
1845	0.756
1846	0.91
1847	0.844
1848	1.082
1849	1.19
1850	1.167
1851	1.003
1852	0.933
1853	0.778
1854	0.906
1855	1.005
1856	1.086
1857	1.402
1858	1.239
1859	1.408
1860	0.922
1861	1.003
1862	1.024
1863	1.356
1864	0.955
1865	0.676
1866	1.236
1867	0.971
1868	0.899
1869	0.64
1870	0.647
1871	0.869
1872	0.804
1873	1.223
1874	1.068
1875	0.923
1876	1.155
1877	1.143
1878	1.03
1879	0.455
1880	0.81
1881	0.929
1882	0.713
1883	0.644
1884	0.773
1885	0.878
1886	1.028
1887	0.817
1888	0.966
1889	0.86
1890	0.926
1891	0.739
1892	1.032
1893	0.929
1894	0.82
1895	0.738
1896	1.126
1897	1.113
1898	1.218
1899	1.058
1900	1.074
1901	0.976
1902	0.766
1903	1.09
1904	1.01
1905	0.998
1906	0.772
1907	1.025
1908	1.247
1909	1.272
1910	0.988
1911	0.99
1912	1.188
1913	1.191
1914	1.142
1915	0.821
1916	1.185
1917	0.986
1918	1.008
1919	1.172
1920	0.753
1921	0.904
1922	0.943
1923	0.844
1924	0.715
1925	0.936
1926	0.871
1927	1.087
1928	1.067
1929	1.514
1930	1.137
1931	1.168
1932	1.252
1933	1.11
1934	0.649
1935	0.926
1936	0.852
1937	0.74
1938	0.823
1939	1.094
1940	1.278
1941	0.864
1942	0.935
1943	1.053
1944	0.828
1945	1.151
1946	1.077
1947	1.076
1948	1.043
1949	1.148
1950	0.913
1951	1.195
1952	1.001
1953	1.506
1954	1.061
1955	0.831
1956	0.671
1957	1.071
1958	0.596
1959	1.097
1960	0.805
1961	0.859
1962	0.658
1963	1.196
1964	1.199
1965	1.131
1966	1.28
1967	0.906
1968	0.987
1969	0.782
1970	1.102
1971	0.774
1972	0.663
1973	1.123
1974	1.079
1975	1.244
1976	0.985
1977	0.75
1978	0.758
1979	0.841
1980	0.78
1981	0.827
1982	0.861
1983	0.857