# northamerica_usa_az531 - North Slope - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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.
#
#
# 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/3391
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_az531 - North Slope - Breitenmoser Tree Ring Chronology Data
#--------------------
# 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.
#--------------------
#	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 Slope
#	Location:
#	Country: United States
#	Northernmost_Latitude: 32.22
#	Southernmost_Latitude: 32.22
#	Easternmost_Longitude: -110.55
#	Westernmost_Longitude: -110.55
#	Elevation: 2441 m
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# Data_Collection
#	Collection_Name: northamerica_usa_az531B
#	Earliest_Year: 1723
#	Most_Recent_Year: 1987
#	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":"4.43960618541","T2":"17.0538544566","M1":"0.0232165357459","M2":"0.284984825454"}}
#--------------------
# Species
#	Species_Name: Douglas fir
#	Species_Code: PSME
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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
1723	1.167
1724	1.274
1725	0.677
1726	1.941
1727	0.898
1728	1.012
1729	0.827
1730	0.982
1731	0.854
1732	0.461
1733	0.619
1734	1.092
1735	0.64
1736	1.219
1737	0.892
1738	0.654
1739	0.593
1740	0.459
1741	0.957
1742	1.031
1743	1.34
1744	1.247
1745	1.594
1746	1.921
1747	1.859
1748	0.653
1749	1.091
1750	0.82
1751	0.847
1752	0.286
1753	0.53
1754	0.43
1755	0.561
1756	0.653
1757	0.705
1758	0.66
1759	0.88
1760	0.756
1761	0.861
1762	1.109
1763	0.682
1764	1.029
1765	1.078
1766	1.026
1767	0.919
1768	0.822
1769	0.961
1770	0.811
1771	1.018
1772	0.869
1773	0.856
1774	0.858
1775	0.872
1776	0.63
1777	0.721
1778	0.79
1779	0.56
1780	0.69
1781	0.796
1782	0.876
1783	0.989
1784	1.297
1785	0.844
1786	0.635
1787	0.904
1788	0.784
1789	0.754
1790	0.734
1791	0.882
1792	0.848
1793	1.134
1794	0.856
1795	1.297
1796	0.995
1797	0.932
1798	0.795
1799	1.167
1800	1.192
1801	1.145
1802	1.514
1803	1.187
1804	1.28
1805	1.134
1806	0.738
1807	0.97
1808	0.711
1809	0.872
1810	1.053
1811	0.941
1812	0.828
1813	0.681
1814	0.696
1815	1.187
1816	1.279
1817	0.872
1818	0.919
1819	0.345
1820	0.59
1821	0.913
1822	0.724
1823	0.553
1824	0.804
1825	0.731
1826	1.182
1827	1.111
1828	1.103
1829	1.043
1830	0.982
1831	1.306
1832	1.001
1833	1.053
1834	1.063
1835	1.436
1836	1.144
1837	1.493
1838	1.194
1839	1.264
1840	0.99
1841	0.746
1842	0.641
1843	0.947
1844	0.945
1845	0.794
1846	1.046
1847	0.418
1848	1.14
1849	1.121
1850	0.99
1851	0.949
1852	0.896
1853	0.779
1854	0.984
1855	0.797
1856	0.99
1857	0.66
1858	1.069
1859	1.139
1860	0.785
1861	0.746
1862	0.909
1863	0.535
1864	0.543
1865	0.816
1866	1.072
1867	0.929
1868	0.791
1869	0.934
1870	0.808
1871	0.815
1872	0.731
1873	0.685
1874	0.871
1875	0.835
1876	0.843
1877	1.026
1878	0.786
1879	0.796
1880	0.664
1881	0.768
1882	0.956
1883	1.09
1884	0.915
1885	0.852
1886	0.672
1887	0.765
1888	1.037
1889	1.037
1890	1.026
1891	1.004
1892	0.518
1893	0.627
1894	0.722
1895	0.757
1896	0.85
1897	0.918
1898	1.664
1899	1.363
1900	1.168
1901	1.267
1902	0.932
1903	1.078
1904	0.664
1905	1.231
1906	1.276
1907	1.584
1908	2.224
1909	1.804
1910	1.222
1911	1.734
1912	2.091
1913	1.762
1914	2.043
1915	1.583
1916	1.591
1917	1.648
1918	1.165
1919	1.733
1920	1.56
1921	1.107
1922	1.655
1923	1.17
1924	1.118
1925	0.626
1926	0.935
1927	1.509
1928	1.21
1929	0.837
1930	1.793
1931	1.284
1932	1.784
1933	1.387
1934	0.785
1935	1.459
1936	0.934
1937	0.967
1938	1.072
1939	0.631
1940	0.912
1941	1.01
1942	0.934
1943	0.584
1944	0.846
1945	0.675
1946	0.622
1947	0.703
1948	0.606
1949	0.941
1950	0.864
1951	0.753
1952	0.994
1953	0.805
1954	0.811
1955	0.603
1956	0.425
1957	0.673
1958	0.708
1959	0.531
1960	0.705
1961	0.451
1962	0.73
1963	0.655
1964	0.571
1965	0.811
1966	0.667
1967	0.952
1968	0.763
1969	0.997
1970	0.986
1971	0.546
1972	0.61
1973	0.972
1974	0.327
1975	0.864
1976	0.629
1977	0.589
1978	0.718
1979	0.968
1980	0.658
1981	0.74
1982	0.718
1983	0.827
1984	1.15
1985	0.835
1986	0.645
1987	0.89