# northamerica_usa_or064 - Mount Hood Low - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/4161
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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_or064 - Mount Hood 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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 Hood Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.33
#	Southernmost_Latitude: 45.33
#	Easternmost_Longitude: -121.67
#	Westernmost_Longitude: -121.67
#	Elevation: 1585 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or064B
#	Earliest_Year: 1744
#	Most_Recent_Year: 1992
#	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":"5.55447702235","T2":"18.6547994501","M1":"0.022191930217","M2":"0.313406788974"}}
#--------------------
# 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
1744	0.738
1745	0.765
1746	1.156
1747	1.187
1748	1.181
1749	1.139
1750	1.457
1751	1.152
1752	1.021
1753	0.879
1754	0.544
1755	0.845
1756	0.988
1757	0.97
1758	0.996
1759	1.089
1760	1.168
1761	1.112
1762	1.236
1763	1.272
1764	0.941
1765	1.113
1766	1.091
1767	1.201
1768	1.121
1769	0.96
1770	1.057
1771	1.071
1772	0.851
1773	0.924
1774	0.919
1775	0.785
1776	0.898
1777	0.992
1778	1.046
1779	0.992
1780	0.795
1781	0.699
1782	0.806
1783	0.653
1784	0.817
1785	0.689
1786	0.586
1787	0.556
1788	0.863
1789	0.892
1790	0.669
1791	1.009
1792	1.062
1793	1.088
1794	1.198
1795	1.141
1796	1.033
1797	0.64
1798	1.276
1799	1.129
1800	1.23
1801	0.811
1802	1.125
1803	0.887
1804	1.058
1805	1.148
1806	0.923
1807	0.836
1808	0.761
1809	0.897
1810	0.626
1811	0.898
1812	1.05
1813	0.845
1814	1.194
1815	0.928
1816	1.009
1817	1.096
1818	1.002
1819	0.933
1820	0.844
1821	0.97
1822	1.061
1823	0.82
1824	0.932
1825	0.986
1826	1.033
1827	0.895
1828	1.048
1829	0.922
1830	0.858
1831	1.031
1832	0.846
1833	0.999
1834	1.111
1835	1.03
1836	0.816
1837	0.923
1838	0.951
1839	1.04
1840	0.752
1841	0.848
1842	0.948
1843	1.151
1844	1.033
1845	1.132
1846	1.202
1847	0.957
1848	1.122
1849	0.793
1850	0.946
1851	0.877
1852	0.819
1853	0.942
1854	0.91
1855	0.764
1856	0.752
1857	1.226
1858	1.275
1859	1.095
1860	1.258
1861	1.18
1862	0.944
1863	1.3
1864	1.236
1865	0.924
1866	0.882
1867	1.149
1868	1.362
1869	1.083
1870	1.151
1871	1.107
1872	1.258
1873	1.209
1874	1.137
1875	1.117
1876	0.791
1877	0.834
1878	0.938
1879	1.076
1880	0.642
1881	0.861
1882	0.966
1883	1.214
1884	0.992
1885	0.842
1886	1.148
1887	1.032
1888	1.211
1889	0.975
1890	0.964
1891	0.932
1892	0.933
1893	0.966
1894	1.091
1895	1.354
1896	0.782
1897	1.088
1898	1.125
1899	0.799
1900	0.953
1901	1.043
1902	0.921
1903	0.847
1904	1.112
1905	0.748
1906	0.809
1907	0.939
1908	1.116
1909	1.022
1910	1.374
1911	1.193
1912	1.23
1913	1.25
1914	1.424
1915	0.971
1916	0.743
1917	0.933
1918	0.95
1919	1.272
1920	1.412
1921	1.566
1922	1.291
1923	1.215
1924	1.319
1925	1.2
1926	0.871
1927	1.226
1928	1.484
1929	1.16
1930	0.873
1931	0.801
1932	0.876
1933	0.829
1934	1.048
1935	1.082
1936	0.911
1937	0.762
1938	0.98
1939	1.114
1940	0.877
1941	0.822
1942	1.047
1943	1.1
1944	0.931
1945	0.866
1946	0.717
1947	0.683
1948	0.803
1949	0.993
1950	1.399
1951	1.738
1952	1.098
1953	0.739
1954	0.884
1955	0.93
1956	1.121
1957	1.082
1958	1.123
1959	0.986
1960	1.183
1961	0.882
1962	0.904
1963	0.88
1964	1.01
1965	1.236
1966	1.251
1967	1.029
1968	0.601
1969	0.747
1970	0.888
1971	0.662
1972	0.664
1973	0.747
1974	0.793
1975	1.055
1976	0.917
1977	0.892
1978	0.81
1979	0.884
1980	1.033
1981	1.008
1982	0.782
1983	0.706
1984	0.936
1985	0.994
1986	0.834
1987	0.99
1988	0.972
1989	0.674
1990	0.939
1991	0.501
1992	0.744