# northamerica_usa_ak080 - Dalton Highway Mile Post 182 - 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/3881
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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_ak080 - Dalton Highway Mile Post 182 - 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
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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: Dalton Highway Mile Post 182
#	Location:
#	Country: United States
#	Northernmost_Latitude: 67.35
#	Southernmost_Latitude: 67.35
#	Easternmost_Longitude: -150.05
#	Westernmost_Longitude: -150.05
#	Elevation: 387 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak080B
#	Earliest_Year: 1876
#	Most_Recent_Year: 2003
#	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":"4.10755594225","T2":"15.5444190058","M1":"0.0232688848284","M2":"0.483878224942"}}
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# Species
#	Species_Name: black spruce
#	Species_Code: PCMA
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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
1876	0.713
1877	0.811
1878	0.866
1879	0.902
1880	0.709
1881	0.87
1882	0.816
1883	0.765
1884	0.774
1885	0.77
1886	0.691
1887	0.993
1888	0.912
1889	0.947
1890	0.836
1891	0.765
1892	0.677
1893	0.852
1894	1.028
1895	0.862
1896	0.726
1897	0.817
1898	0.543
1899	0.52
1900	0.575
1901	0.745
1902	0.778
1903	0.642
1904	0.604
1905	0.474
1906	0.508
1907	0.671
1908	0.674
1909	0.666
1910	0.704
1911	0.715
1912	0.786
1913	0.711
1914	0.707
1915	0.697
1916	0.893
1917	1.016
1918	0.961
1919	0.696
1920	1.061
1921	1.2
1922	0.831
1923	1.123
1924	0.791
1925	0.896
1926	0.917
1927	1.034
1928	0.959
1929	1.147
1930	0.994
1931	0.907
1932	1.189
1933	0.931
1934	1.011
1935	1.183
1936	1.409
1937	1.048
1938	1.115
1939	1.275
1940	0.986
1941	1.054
1942	1.391
1943	1.354
1944	1.317
1945	1.357
1946	1.154
1947	1.114
1948	0.961
1949	0.897
1950	1.103
1951	1.241
1952	1.494
1953	1.417
1954	1.258
1955	1.45
1956	1.075
1957	1.081
1958	1.238
1959	1.233
1960	1.376
1961	1.081
1962	0.969
1963	1.031
1964	1.076
1965	1.001
1966	0.837
1967	0.772
1968	0.885
1969	0.586
1970	0.664
1971	0.757
1972	0.663
1973	0.615
1974	0.744
1975	0.622
1976	0.71
1977	0.872
1978	0.856
1979	0.811
1980	1.136
1981	0.973
1982	1.217
1983	1.362
1984	1.629
1985	1.505
1986	1.285
1987	1.08
1988	0.995
1989	0.921
1990	1.017
1991	0.768
1992	0.755
1993	0.695
1994	0.571
1995	0.708
1996	0.787
1997	0.876
1998	0.812
1999	0.784
2000	0.746
2001	0.746
2002	0.629
2003	0.626