# northamerica_usa_or073 - Crater Lake East 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/4116
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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_or073 - Crater Lake East 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: Crater Lake East Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.83
#	Southernmost_Latitude: 42.83
#	Easternmost_Longitude: -122.0
#	Westernmost_Longitude: -122.0
#	Elevation: 1910 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or073B
#	Earliest_Year: 1756
#	Most_Recent_Year: 1992
#	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":"5.61822016505","T2":"15.2469178143","M1":"0.022735539468","M2":"0.433272143632"}}
#--------------------
# 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
1756	1.012
1757	0.712
1758	0.903
1759	0.874
1760	0.729
1761	0.955
1762	0.962
1763	0.936
1764	0.885
1765	1.06
1766	0.915
1767	1.205
1768	1.133
1769	0.997
1770	1.071
1771	1.06
1772	0.874
1773	0.966
1774	1.005
1775	1.018
1776	1.139
1777	0.988
1778	0.858
1779	0.908
1780	0.952
1781	0.819
1782	0.802
1783	0.916
1784	0.934
1785	0.802
1786	0.894
1787	0.735
1788	0.949
1789	0.922
1790	0.977
1791	1.221
1792	1.122
1793	1.088
1794	1.101
1795	0.911
1796	0.931
1797	1.04
1798	1.086
1799	1.047
1800	1.128
1801	0.844
1802	1.171
1803	1.158
1804	0.996
1805	1.088
1806	0.883
1807	1.14
1808	0.985
1809	1.171
1810	0.702
1811	1.048
1812	1.126
1813	1.028
1814	1.291
1815	1.064
1816	1.036
1817	0.974
1818	1.026
1819	0.727
1820	0.914
1821	1.017
1822	1.046
1823	0.834
1824	1.035
1825	1.1
1826	1.204
1827	0.964
1828	1.15
1829	1.127
1830	1.076
1831	0.971
1832	1.263
1833	1.151
1834	1.357
1835	1.101
1836	1.248
1837	1.48
1838	1.438
1839	1.272
1840	0.863
1841	1.208
1842	1.035
1843	1.172
1844	1.115
1845	1.234
1846	1.161
1847	0.979
1848	1.145
1849	0.92
1850	1.004
1851	1.214
1852	1.125
1853	1.117
1854	1.403
1855	0.987
1856	0.904
1857	1.181
1858	1.327
1859	1.049
1860	1.238
1861	1.128
1862	0.791
1863	1.579
1864	1.233
1865	0.961
1866	0.771
1867	1.044
1868	1.237
1869	1.031
1870	0.934
1871	0.746
1872	0.85
1873	1.217
1874	0.988
1875	1.012
1876	0.722
1877	1.212
1878	1.379
1879	1.468
1880	0.94
1881	1.452
1882	1.155
1883	1.082
1884	1.071
1885	1.369
1886	1.208
1887	0.998
1888	1.188
1889	1.091
1890	1.048
1891	1.219
1892	1.095
1893	1.072
1894	1.328
1895	1.415
1896	0.904
1897	1.209
1898	1.121
1899	0.863
1900	1.159
1901	1.266
1902	1.044
1903	0.995
1904	1.309
1905	1.235
1906	0.893
1907	1.088
1908	1.033
1909	0.842
1910	1.097
1911	0.945
1912	1.207
1913	1.435
1914	1.443
1915	1.224
1916	0.938
1917	0.954
1918	0.664
1919	0.936
1920	1.094
1921	1.082
1922	0.898
1923	0.898
1924	0.897
1925	0.786
1926	0.778
1927	0.754
1928	1.082
1929	0.922
1930	0.758
1931	0.93
1932	0.779
1933	0.677
1934	0.885
1935	0.818
1936	0.929
1937	0.682
1938	0.721
1939	1.055
1940	0.771
1941	0.77
1942	0.794
1943	0.9
1944	0.922
1945	0.795
1946	0.723
1947	0.959
1948	0.887
1949	0.922
1950	0.9
1951	0.984
1952	0.891
1953	0.754
1954	1.129
1955	1.096
1956	0.954
1957	0.887
1958	0.984
1959	0.866
1960	0.849
1961	0.761
1962	0.975
1963	1.183
1964	1.257
1965	1.083
1966	1.246
1967	0.897
1968	0.744
1969	0.99
1970	0.944
1971	0.823
1972	0.99
1973	1.074
1974	0.853
1975	0.978
1976	0.993
1977	0.799
1978	0.986
1979	1.172
1980	1.016
1981	0.781
1982	0.607
1983	0.731
1984	1.05
1985	0.745
1986	0.807
1987	0.814
1988	0.635
1989	0.726
1990	0.993
1991	0.714
1992	0.847