# northamerica_usa_or067 - Mount Jefferson Low - 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/4165
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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_or067 - Mount Jefferson Low - 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: Mount Jefferson Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 44.67
#	Southernmost_Latitude: 44.67
#	Easternmost_Longitude: -121.83
#	Westernmost_Longitude: -121.83
#	Elevation: 1585 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or067B
#	Earliest_Year: 1734
#	Most_Recent_Year: 1993
#	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":"3.7596598037","T2":"16.7845443287","M1":"0.0225133857166","M2":"0.330724663011"}}
#--------------------
# Species
#	Species_Name: mountain hemlock
#	Species_Code: TSME
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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
1734	0.928
1735	1.044
1736	1.001
1737	1.299
1738	1.067
1739	1.172
1740	1.05
1741	0.82
1742	0.653
1743	0.836
1744	0.837
1745	0.87
1746	0.991
1747	1.005
1748	0.968
1749	0.982
1750	1.097
1751	1.117
1752	0.907
1753	0.776
1754	0.614
1755	1.056
1756	1.02
1757	0.899
1758	0.981
1759	0.809
1760	0.927
1761	0.979
1762	1.055
1763	1.011
1764	0.861
1765	1.0
1766	0.873
1767	0.959
1768	0.98
1769	0.931
1770	1.106
1771	1.117
1772	1.015
1773	1.106
1774	1.068
1775	0.87
1776	0.957
1777	1.131
1778	1.191
1779	1.201
1780	1.169
1781	0.762
1782	0.968
1783	0.837
1784	1.078
1785	0.964
1786	1.055
1787	0.891
1788	1.306
1789	1.186
1790	0.87
1791	0.979
1792	1.033
1793	1.043
1794	1.118
1795	1.047
1796	0.921
1797	1.011
1798	1.277
1799	1.177
1800	1.293
1801	0.756
1802	0.965
1803	0.904
1804	1.011
1805	1.115
1806	1.01
1807	1.011
1808	0.852
1809	1.106
1810	0.847
1811	1.074
1812	1.009
1813	0.854
1814	1.063
1815	0.863
1816	1.11
1817	1.043
1818	1.008
1819	0.993
1820	0.88
1821	0.96
1822	1.126
1823	0.737
1824	0.67
1825	0.917
1826	0.973
1827	0.775
1828	0.961
1829	1.105
1830	0.938
1831	0.919
1832	0.67
1833	1.198
1834	1.286
1835	1.095
1836	0.939
1837	0.986
1838	1.045
1839	1.233
1840	0.881
1841	1.024
1842	1.013
1843	1.318
1844	1.246
1845	1.14
1846	1.113
1847	0.931
1848	1.196
1849	0.844
1850	0.965
1851	1.047
1852	0.922
1853	1.061
1854	1.011
1855	0.938
1856	0.921
1857	1.259
1858	1.318
1859	1.235
1860	1.39
1861	1.018
1862	0.974
1863	1.141
1864	0.873
1865	0.87
1866	0.767
1867	0.975
1868	1.029
1869	0.885
1870	0.739
1871	0.646
1872	0.976
1873	1.124
1874	1.006
1875	1.049
1876	0.61
1877	0.687
1878	0.838
1879	1.081
1880	0.78
1881	0.968
1882	1.12
1883	1.132
1884	0.854
1885	0.986
1886	1.381
1887	1.179
1888	1.165
1889	1.023
1890	0.936
1891	0.864
1892	0.904
1893	0.918
1894	0.894
1895	1.197
1896	0.782
1897	1.014
1898	1.026
1899	0.782
1900	1.05
1901	1.101
1902	0.98
1903	0.897
1904	1.296
1905	1.348
1906	1.172
1907	1.086
1908	1.033
1909	0.933
1910	1.057
1911	1.06
1912	1.035
1913	1.241
1914	1.455
1915	0.999
1916	0.813
1917	0.943
1918	0.718
1919	0.817
1920	0.815
1921	0.904
1922	1.028
1923	0.981
1924	0.889
1925	0.799
1926	0.996
1927	0.894
1928	0.874
1929	0.977
1930	0.882
1931	0.789
1932	0.905
1933	0.885
1934	0.935
1935	1.151
1936	1.156
1937	0.885
1938	1.093
1939	1.251
1940	0.963
1941	1.322
1942	1.207
1943	1.139
1944	0.955
1945	0.827
1946	0.997
1947	0.894
1948	0.971
1949	1.197
1950	1.219
1951	1.238
1952	1.033
1953	0.608
1954	1.015
1955	1.106
1956	1.369
1957	1.086
1958	1.052
1959	0.962
1960	0.835
1961	0.726
1962	0.814
1963	0.735
1964	0.902
1965	0.924
1966	1.28
1967	1.11
1968	0.837
1969	0.864
1970	1.044
1971	1.085
1972	1.118
1973	1.001
1974	0.917
1975	1.052
1976	0.868
1977	0.868
1978	0.86
1979	1.088
1980	1.05
1981	0.743
1982	0.938
1983	0.703
1984	1.087
1985	1.044
1986	0.843
1987	0.882
1988	0.859
1989	0.41
1990	0.804
1991	0.342
1992	0.725
1993	0.603