# northamerica_usa_or075 - Crater Lake East High - 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/4115
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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_or075 - Crater Lake East High - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# 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.
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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: Crater Lake East High
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.83
#	Southernmost_Latitude: 42.83
#	Easternmost_Longitude: -122.0
#	Westernmost_Longitude: -122.0
#	Elevation: 2300 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or075B
#	Earliest_Year: 1850
#	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":"5.85333013568","T2":"16.3584250494","M1":"0.0219127838415","M2":"0.271474450652"}}
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# Species
#	Species_Name: mountain hemlock
#	Species_Code: TSME
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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
1850	0.834
1851	0.984
1852	1.001
1853	0.711
1854	1.163
1855	1.124
1856	0.917
1857	0.937
1858	1.096
1859	0.934
1860	0.945
1861	0.776
1862	0.518
1863	1.174
1864	1.155
1865	1.031
1866	0.692
1867	1.012
1868	1.129
1869	1.14
1870	0.959
1871	0.871
1872	0.924
1873	1.093
1874	1.13
1875	1.225
1876	0.744
1877	1.262
1878	1.208
1879	1.284
1880	0.782
1881	1.286
1882	0.782
1883	0.962
1884	0.967
1885	1.045
1886	0.778
1887	0.789
1888	0.971
1889	1.027
1890	0.828
1891	0.991
1892	0.869
1893	0.743
1894	0.725
1895	1.024
1896	0.759
1897	1.127
1898	1.104
1899	0.647
1900	1.012
1901	1.07
1902	0.968
1903	1.088
1904	1.297
1905	1.443
1906	1.1
1907	1.064
1908	1.095
1909	0.919
1910	1.334
1911	0.954
1912	1.013
1913	1.059
1914	1.17
1915	1.105
1916	0.683
1917	0.791
1918	0.646
1919	0.742
1920	0.866
1921	0.754
1922	0.955
1923	0.972
1924	1.094
1925	0.913
1926	1.119
1927	0.791
1928	1.032
1929	0.95
1930	0.972
1931	1.148
1932	0.924
1933	0.892
1934	1.298
1935	1.042
1936	1.242
1937	0.873
1938	0.972
1939	1.376
1940	1.172
1941	1.052
1942	0.904
1943	0.928
1944	1.143
1945	1.091
1946	0.992
1947	1.156
1948	1.191
1949	1.033
1950	1.011
1951	0.999
1952	0.809
1953	0.741
1954	1.077
1955	1.181
1956	0.876
1957	1.158
1958	1.311
1959	1.1
1960	1.035
1961	0.959
1962	0.898
1963	1.2
1964	1.134
1965	0.952
1966	1.266
1967	1.155
1968	0.898
1969	1.089
1970	1.088
1971	0.73
1972	0.769
1973	1.144
1974	0.507
1975	1.011
1976	0.943
1977	1.247
1978	1.003
1979	1.103
1980	1.067
1981	0.994
1982	0.65
1983	0.571
1984	1.114
1985	0.757
1986	0.709
1987	0.815
1988	0.947
1989	0.91
1990	1.35
1991	0.759
1992	0.977