# northamerica_usa_ak051 - Nutirwik Creek Floodplain - 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/5260
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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_ak051 - Nutirwik Creek Floodplain - 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 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:
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#	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: Nutirwik Creek Floodplain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 67.15
#	Southernmost_Latitude: 67.15
#	Easternmost_Longitude: -149.13
#	Westernmost_Longitude: -149.13
#	Elevation: 100 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak051B
#	Earliest_Year: 1854
#	Most_Recent_Year: 2001
#	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":"5.63805779004","T2":"18.0933964293","M1":"0.0226541710234","M2":"0.318902305927"}}
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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
#
age	trsgi
1854	0.691
1855	0.708
1856	0.591
1857	0.48
1858	0.612
1859	0.713
1860	1.021
1861	1.089
1862	0.975
1863	0.963
1864	0.808
1865	1.025
1866	0.818
1867	0.829
1868	0.658
1869	0.443
1870	0.607
1871	0.617
1872	0.716
1873	0.809
1874	0.897
1875	0.939
1876	0.963
1877	0.986
1878	0.958
1879	1.113
1880	1.088
1881	1.243
1882	1.086
1883	0.877
1884	0.96
1885	1.231
1886	1.251
1887	0.983
1888	0.982
1889	1.198
1890	1.123
1891	1.249
1892	1.278
1893	1.272
1894	1.231
1895	1.554
1896	1.384
1897	1.29
1898	0.997
1899	0.87
1900	0.799
1901	1.033
1902	1.046
1903	0.94
1904	0.821
1905	0.801
1906	0.993
1907	1.029
1908	1.105
1909	1.156
1910	1.07
1911	1.178
1912	0.948
1913	1.082
1914	0.969
1915	0.991
1916	1.084
1917	1.304
1918	1.221
1919	0.792
1920	1.099
1921	1.238
1922	1.023
1923	1.593
1924	1.137
1925	1.122
1926	1.2
1927	1.104
1928	1.007
1929	1.104
1930	1.085
1931	0.941
1932	1.022
1933	0.899
1934	1.057
1935	1.173
1936	1.059
1937	0.998
1938	0.97
1939	1.231
1940	0.945
1941	1.069
1942	1.331
1943	1.173
1944	1.263
1945	1.021
1946	1.434
1947	1.062
1948	1.014
1949	0.887
1950	1.145
1951	0.942
1952	1.141
1953	1.028
1954	1.072
1955	1.014
1956	0.794
1957	0.792
1958	0.859
1959	0.792
1960	0.967
1961	0.842
1962	0.862
1963	0.724
1964	0.897
1965	0.779
1966	0.706
1967	0.733
1968	0.773
1969	0.536
1970	0.471
1971	0.717
1972	0.699
1973	0.479
1974	0.543
1975	0.598
1976	0.559
1977	0.706
1978	0.616
1979	0.709
1980	0.807
1981	0.706
1982	0.847
1983	0.809
1984	0.916
1985	0.949
1986	0.922
1987	0.821
1988	0.89
1989	0.928
1990	0.991
1991	1.073
1992	1.195
1993	0.871
1994	0.91
1995	1.075
1996	1.46
1997	1.482
1998	1.272
1999	1.379
2000	1.037
2001	1.379