# northamerica_usa_ak049 - North Fork Koyukuk - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/5258
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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
#--------------------
# Title
#	Study_Name: northamerica_usa_ak049 - North Fork Koyukuk - 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: North Fork Koyukuk
#	Location:
#	Country: United States
#	Northernmost_Latitude: 67.15
#	Southernmost_Latitude: 67.15
#	Easternmost_Longitude: -150.08
#	Westernmost_Longitude: -150.08
#	Elevation: 100 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak049B
#	Earliest_Year: 1750
#	Most_Recent_Year: 2001
#	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":"5.4657419375","T2":"17.0243750636","M1":"0.0233449983152","M2":"0.391996000411"}}
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# Species
#	Species_Name: white spruce
#	Species_Code: PCGL
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# Chronology:
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# Variables
#
# 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)
#
##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
1750	1.184
1751	1.026
1752	1.301
1753	1.545
1754	1.318
1755	0.994
1756	1.109
1757	0.968
1758	1.157
1759	1.28
1760	1.323
1761	1.608
1762	1.21
1763	0.994
1764	0.943
1765	0.753
1766	0.819
1767	0.906
1768	1.058
1769	1.016
1770	1.024
1771	0.782
1772	1.438
1773	1.466
1774	1.604
1775	1.171
1776	1.099
1777	1.078
1778	0.96
1779	0.99
1780	0.669
1781	0.77
1782	0.89
1783	0.922
1784	0.797
1785	0.67
1786	0.75
1787	0.745
1788	0.747
1789	0.746
1790	0.844
1791	0.914
1792	0.92
1793	0.969
1794	0.871
1795	0.977
1796	0.868
1797	0.747
1798	0.63
1799	0.692
1800	0.804
1801	0.755
1802	0.703
1803	0.674
1804	0.768
1805	0.825
1806	0.825
1807	0.835
1808	0.913
1809	0.837
1810	0.86
1811	0.73
1812	0.722
1813	0.782
1814	0.607
1815	0.753
1816	0.639
1817	0.808
1818	0.806
1819	0.611
1820	0.539
1821	0.492
1822	0.654
1823	0.724
1824	0.653
1825	0.648
1826	0.595
1827	0.615
1828	0.969
1829	0.831
1830	0.714
1831	0.757
1832	0.775
1833	0.633
1834	0.559
1835	0.508
1836	0.593
1837	0.714
1838	0.648
1839	0.653
1840	0.773
1841	0.686
1842	0.769
1843	0.714
1844	0.64
1845	0.669
1846	0.801
1847	0.931
1848	0.908
1849	0.778
1850	0.662
1851	0.82
1852	0.75
1853	0.992
1854	1.167
1855	1.118
1856	0.927
1857	1.042
1858	1.045
1859	1.055
1860	1.01
1861	0.979
1862	1.135
1863	1.097
1864	0.896
1865	1.12
1866	0.935
1867	1.044
1868	0.765
1869	0.639
1870	0.732
1871	0.604
1872	0.577
1873	0.748
1874	0.875
1875	0.895
1876	1.064
1877	1.144
1878	0.938
1879	1.237
1880	1.168
1881	1.186
1882	1.256
1883	0.936
1884	0.919
1885	1.293
1886	1.087
1887	0.949
1888	1.042
1889	1.006
1890	1.051
1891	1.248
1892	1.095
1893	1.051
1894	0.971
1895	1.178
1896	1.156
1897	1.241
1898	0.869
1899	0.743
1900	0.772
1901	0.93
1902	1.081
1903	1.055
1904	0.875
1905	0.881
1906	1.136
1907	1.109
1908	1.118
1909	1.13
1910	1.067
1911	1.121
1912	0.89
1913	1.132
1914	1.06
1915	1.011
1916	0.922
1917	1.187
1918	1.19
1919	0.706
1920	0.939
1921	1.078
1922	0.805
1923	1.5
1924	1.108
1925	1.072
1926	1.1
1927	0.98
1928	0.901
1929	1.083
1930	1.089
1931	0.836
1932	0.977
1933	0.78
1934	0.916
1935	1.103
1936	1.081
1937	1.097
1938	0.859
1939	1.096
1940	0.711
1941	1.078
1942	1.131
1943	1.291
1944	1.465
1945	1.18
1946	1.318
1947	0.99
1948	0.986
1949	0.835
1950	0.985
1951	0.895
1952	1.164
1953	0.99
1954	1.166
1955	1.114
1956	0.881
1957	0.992
1958	1.01
1959	0.95
1960	1.229
1961	1.089
1962	1.051
1963	1.002
1964	1.034
1965	0.976
1966	0.938
1967	1.067
1968	1.038
1969	0.634
1970	0.572
1971	0.844
1972	0.815
1973	0.541
1974	0.635
1975	0.772
1976	0.853
1977	1.009
1978	0.817
1979	0.933
1980	1.13
1981	0.808
1982	1.101
1983	1.011
1984	1.211
1985	1.046
1986	1.032
1987	0.776
1988	0.818
1989	0.862
1990	0.992
1991	0.897
1992	1.079
1993	0.719
1994	0.756
1995	0.834
1996	1.2
1997	1.109
1998	1.186
1999	1.163
2000	1.107
2001	1.05