# northamerica_usa_ak040 - Nome Creek below treeline - 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/3892
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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_ak040 - Nome Creek below treeline - 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: Nome Creek below treeline
#	Location:
#	Country: United States
#	Northernmost_Latitude: 65.37
#	Southernmost_Latitude: 65.37
#	Easternmost_Longitude: -146.62
#	Westernmost_Longitude: -146.62
#	Elevation: 884 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak040B
#	Earliest_Year: 1852
#	Most_Recent_Year: 1998
#	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":"6.5118183317","T2":"16.8308847834","M1":"0.022727491894","M2":"0.385654918101"}}
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# Species
#	Species_Name: white spruce
#	Species_Code: PCGL
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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
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age	trsgi
1852	0.932
1853	1.187
1854	1.312
1855	1.241
1856	0.829
1857	0.688
1858	0.69
1859	1.024
1860	0.865
1861	1.1
1862	1.134
1863	0.928
1864	0.913
1865	1.028
1866	0.976
1867	1.028
1868	0.973
1869	0.843
1870	0.934
1871	0.944
1872	0.842
1873	1.101
1874	1.061
1875	1.018
1876	1.006
1877	1.22
1878	1.122
1879	1.121
1880	0.894
1881	1.084
1882	0.972
1883	0.879
1884	0.723
1885	0.97
1886	1.013
1887	0.607
1888	0.442
1889	0.481
1890	0.793
1891	0.936
1892	0.89
1893	0.735
1894	0.437
1895	0.502
1896	0.641
1897	0.692
1898	0.714
1899	0.735
1900	0.648
1901	0.514
1902	0.751
1903	0.826
1904	0.809
1905	0.825
1906	0.978
1907	0.999
1908	1.002
1909	1.005
1910	0.798
1911	0.929
1912	0.573
1913	1.047
1914	0.911
1915	0.99
1916	0.858
1917	1.244
1918	1.274
1919	0.725
1920	0.962
1921	0.856
1922	0.67
1923	1.092
1924	0.636
1925	0.829
1926	1.064
1927	1.227
1928	1.15
1929	1.553
1930	1.271
1931	1.224
1932	1.432
1933	1.16
1934	1.674
1935	1.839
1936	1.54
1937	1.137
1938	1.068
1939	1.459
1940	0.795
1941	1.318
1942	1.307
1943	1.393
1944	1.291
1945	1.432
1946	1.628
1947	1.219
1948	1.274
1949	0.797
1950	1.231
1951	0.872
1952	1.054
1953	0.971
1954	0.983
1955	1.036
1956	0.955
1957	0.882
1958	1.036
1959	0.996
1960	1.306
1961	1.13
1962	1.253
1963	0.855
1964	1.288
1965	1.131
1966	1.153
1967	1.169
1968	1.03
1969	0.784
1970	0.593
1971	1.277
1972	0.858
1973	0.621
1974	0.932
1975	0.963
1976	1.064
1977	1.118
1978	0.8
1979	1.119
1980	1.079
1981	0.907
1982	1.412
1983	1.062
1984	0.958
1985	1.003
1986	0.921
1987	0.725
1988	0.664
1989	0.767
1990	0.648
1991	0.594
1992	0.627
1993	0.357
1994	0.439
1995	0.514
1996	0.637
1997	0.67
1998	0.572