# northamerica_usa_wa120 - Mount Dana Medium - 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/4159
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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_wa120 - Mount Dana Medium - 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
#--------------------
# 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 Medium
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.85
#	Southernmost_Latitude: 47.85
#	Easternmost_Longitude: -123.48
#	Westernmost_Longitude: -123.48
#	Elevation: 1675 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wa120B
#	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":"5.13892700345","T2":"17.7151596521","M1":"0.0225171782237","M2":"0.400908322465"}}
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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	0.719
1851	1.073
1852	0.952
1853	0.953
1854	0.812
1855	0.935
1856	0.806
1857	0.767
1858	0.814
1859	0.758
1860	0.932
1861	0.772
1862	0.731
1863	1.048
1864	0.741
1865	0.958
1866	0.662
1867	0.684
1868	0.998
1869	1.065
1870	1.1
1871	0.998
1872	1.029
1873	0.982
1874	1.016
1875	0.987
1876	0.776
1877	1.023
1878	1.025
1879	1.128
1880	0.753
1881	0.807
1882	0.927
1883	1.097
1884	1.006
1885	0.995
1886	1.302
1887	1.0
1888	1.07
1889	1.285
1890	1.373
1891	1.216
1892	1.075
1893	1.07
1894	0.945
1895	1.155
1896	0.904
1897	0.996
1898	1.082
1899	0.802
1900	0.922
1901	1.012
1902	0.931
1903	0.829
1904	1.196
1905	1.073
1906	1.033
1907	1.188
1908	1.02
1909	0.859
1910	1.133
1911	1.211
1912	1.168
1913	1.025
1914	1.092
1915	1.136
1916	0.724
1917	0.91
1918	0.941
1919	0.817
1920	0.985
1921	0.612
1922	0.931
1923	0.963
1924	0.978
1925	0.996
1926	1.035
1927	0.854
1928	1.079
1929	1.091
1930	1.112
1931	1.07
1932	0.98
1933	1.021
1934	0.866
1935	1.297
1936	1.097
1937	1.135
1938	1.095
1939	1.062
1940	1.055
1941	1.116
1942	1.086
1943	0.87
1944	1.05
1945	1.04
1946	0.867
1947	0.996
1948	1.136
1949	1.101
1950	1.09
1951	0.98
1952	0.968
1953	0.911
1954	0.899
1955	1.248
1956	0.894
1957	0.87
1958	1.039
1959	0.863
1960	1.095
1961	0.899
1962	1.002
1963	1.055
1964	1.064
1965	1.351
1966	1.102
1967	1.054
1968	0.963
1969	0.917
1970	1.102
1971	0.911
1972	0.892
1973	0.895
1974	0.741
1975	0.949
1976	0.886
1977	1.142
1978	0.881
1979	0.963
1980	1.02
1981	1.138
1982	0.7
1983	0.719
1984	1.075
1985	1.02
1986	0.891
1987	0.936
1988	0.839
1989	0.806
1990	0.933