# northamerica_usa_mt107 - Skalkaho Pass   Bitterroot - 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/2852
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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_mt107 - Skalkaho Pass   Bitterroot - 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: Skalkaho Pass   Bitterroot
#	Location:
#	Country: United States
#	Northernmost_Latitude: 46.23
#	Southernmost_Latitude: 46.23
#	Easternmost_Longitude: -113.77
#	Westernmost_Longitude: -113.77
#	Elevation: 2160 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mt107B
#	Earliest_Year: 1799
#	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":"5.56656253299","T2":"16.955854463","M1":"0.0221042400834","M2":"0.398674159229"}}
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# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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
1799	0.965
1800	0.962
1801	0.929
1802	1.012
1803	1.075
1804	0.845
1805	1.039
1806	0.865
1807	0.842
1808	0.875
1809	0.904
1810	0.874
1811	0.96
1812	1.086
1813	1.142
1814	0.984
1815	0.93
1816	0.984
1817	0.954
1818	0.948
1819	1.017
1820	0.933
1821	1.029
1822	0.879
1823	0.849
1824	0.882
1825	0.859
1826	0.848
1827	0.92
1828	0.967
1829	0.948
1830	0.964
1831	0.955
1832	0.846
1833	1.11
1834	1.162
1835	1.016
1836	0.954
1837	0.953
1838	0.906
1839	1.102
1840	0.862
1841	1.02
1842	0.922
1843	0.957
1844	0.88
1845	0.882
1846	0.961
1847	1.057
1848	1.135
1849	0.97
1850	1.209
1851	1.045
1852	1.09
1853	0.947
1854	1.041
1855	1.079
1856	1.065
1857	1.124
1858	1.146
1859	1.102
1860	0.989
1861	1.021
1862	1.044
1863	1.263
1864	1.114
1865	1.18
1866	1.153
1867	1.152
1868	1.169
1869	1.057
1870	0.967
1871	1.115
1872	1.019
1873	1.167
1874	1.048
1875	1.037
1876	1.179
1877	1.079
1878	1.099
1879	0.962
1880	0.988
1881	1.2
1882	1.152
1883	0.915
1884	0.903
1885	1.076
1886	1.143
1887	0.991
1888	1.092
1889	0.928
1890	0.99
1891	0.982
1892	0.873
1893	0.892
1894	1.004
1895	0.955
1896	1.004
1897	0.981
1898	1.071
1899	0.892
1900	1.106
1901	0.96
1902	0.86
1903	0.97
1904	0.985
1905	0.79
1906	0.683
1907	0.869
1908	0.963
1909	0.799
1910	0.877
1911	0.857
1912	0.965
1913	0.905
1914	0.942
1915	0.697
1916	0.841
1917	0.885
1918	0.89
1919	0.897
1920	0.711
1921	0.821
1922	0.799
1923	0.821
1924	0.826
1925	0.882
1926	0.655
1927	0.713
1928	0.902
1929	1.014
1930	1.124
1931	1.185
1932	1.058
1933	0.989
1934	1.165
1935	1.108
1936	1.205
1937	1.003
1938	1.218
1939	1.138
1940	1.054
1941	1.111
1942	1.007
1943	1.061
1944	1.201
1945	1.144
1946	1.043
1947	1.134
1948	1.282
1949	1.133
1950	0.999
1951	1.078
1952	0.881
1953	0.931
1954	0.921
1955	0.978
1956	1.036
1957	1.098
1958	1.191
1959	1.077
1960	1.196
1961	0.95
1962	0.81
1963	0.993
1964	0.958
1965	1.161
1966	1.031
1967	0.91
1968	0.855
1969	0.972
1970	1.144
1971	0.987
1972	0.933
1973	0.884
1974	0.88
1975	0.85
1976	0.871
1977	0.913
1978	0.927
1979	0.951
1980	0.948
1981	0.958
1982	0.904
1983	0.934