# northamerica_usa_wa119 - Mount Dana Low - 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/4158
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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_wa119 - Mount Dana Low - 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
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# 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: Mount Dana Low
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.85
#	Southernmost_Latitude: 47.85
#	Easternmost_Longitude: -123.48
#	Westernmost_Longitude: -123.48
#	Elevation: 1540 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa119B
#	Earliest_Year: 1850
#	Most_Recent_Year: 1990
#	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":"6.32782963954","T2":"18.1603627346","M1":"0.02286933275","M2":"0.343048085134"}}
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# Species
#	Species_Name: subalpine fir
#	Species_Code: ABLA
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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	0.77
1851	1.117
1852	0.84
1853	0.767
1854	0.906
1855	1.037
1856	0.87
1857	0.922
1858	1.022
1859	1.085
1860	1.227
1861	0.781
1862	1.026
1863	1.435
1864	0.886
1865	1.304
1866	0.932
1867	0.845
1868	1.033
1869	0.848
1870	0.701
1871	0.69
1872	0.907
1873	0.948
1874	0.923
1875	1.049
1876	0.5
1877	0.766
1878	0.838
1879	0.985
1880	0.589
1881	0.712
1882	0.894
1883	0.871
1884	0.78
1885	0.512
1886	1.21
1887	0.741
1888	0.718
1889	0.832
1890	0.918
1891	1.149
1892	1.071
1893	1.096
1894	1.032
1895	1.09
1896	0.847
1897	0.936
1898	1.086
1899	0.75
1900	0.887
1901	1.103
1902	0.983
1903	0.886
1904	1.27
1905	1.013
1906	0.877
1907	1.238
1908	1.168
1909	0.78
1910	1.158
1911	1.335
1912	1.224
1913	1.195
1914	1.24
1915	1.075
1916	0.616
1917	0.934
1918	0.996
1919	0.941
1920	0.906
1921	0.686
1922	1.026
1923	1.051
1924	0.952
1925	1.057
1926	0.991
1927	1.031
1928	1.353
1929	1.373
1930	1.342
1931	1.209
1932	1.079
1933	1.309
1934	0.809
1935	1.468
1936	1.07
1937	1.086
1938	1.119
1939	1.068
1940	1.191
1941	1.32
1942	1.363
1943	1.169
1944	1.531
1945	1.4
1946	1.024
1947	1.299
1948	1.377
1949	1.091
1950	1.104
1951	1.157
1952	1.035
1953	0.732
1954	0.731
1955	1.303
1956	0.949
1957	1.034
1958	1.204
1959	0.889
1960	1.204
1961	0.914
1962	0.914
1963	0.967
1964	1.071
1965	1.239
1966	1.004
1967	1.111
1968	0.966
1969	0.897
1970	1.133
1971	0.8
1972	0.808
1973	0.847
1974	0.38
1975	0.856
1976	0.695
1977	0.901
1978	0.652
1979	0.872
1980	0.85
1981	0.963
1982	0.436
1983	0.545
1984	1.023
1985	0.936
1986	0.525
1987	0.75
1988	0.686
1989	0.707
1990	0.746