ÃÂ¯ÃÂ»ÃÂ¿# northamerica_usa_ak031 - Four Twelve with Revisit - 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/3593
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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_ak031 - Four Twelve with Revisit - 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: Four Twelve with Revisit
#	Location:
#	Country: United States
#	Northernmost_Latitude: 67.93
#	Southernmost_Latitude: 67.93
#	Easternmost_Longitude: -162.3
#	Westernmost_Longitude: -162.3
#	Elevation: 126 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak031B
#	Earliest_Year: 1600
#	Most_Recent_Year: 1977
#	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":"5.23884667715","T2":"17.1932242718","M1":"0.0227509404647","M2":"0.404984016378"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1515	1.038
1516	1.107
1517	0.948
1518	1.296
1519	1.593
1520	1.002
1521	1.155
1522	1.047
1523	1.115
1524	0.782
1525	0.958
1526	0.78
1527	0.637
1528	0.553
1529	0.601
1530	1.096
1531	0.822
1532	0.83
1533	0.993
1534	0.885
1535	1.104
1536	1.021
1537	0.799
1538	1.009
1539	1.039
1540	0.884
1541	0.906
1542	0.88
1543	0.622
1544	1.063
1545	1.157
1546	0.887
1547	1.08
1548	0.864
1549	1.046
1550	0.795
1551	1.232
1552	1.035
1553	0.993
1554	1.093
1555	0.896
1556	0.961
1557	1.153
1558	1.018
1559	0.934
1560	0.746
1561	0.954
1562	0.969
1563	0.844
1564	1.069
1565	1.183
1566	1.3
1567	0.984
1568	1.056
1569	0.833
1570	0.914
1571	0.498
1572	0.604
1573	0.725
1574	0.699
1575	0.562
1576	0.672
1577	0.766
1578	0.912
1579	0.787
1580	0.76
1581	1.069
1582	1.144
1583	1.279
1584	1.345
1585	0.776
1586	1.012
1587	0.815
1588	0.872
1589	1.017
1590	1.456
1591	1.605
1592	1.442
1593	0.985
1594	1.259
1595	1.484
1596	1.686
1597	1.751
1598	1.48
1599	1.793
1600	1.488
1601	1.726
1602	1.141
1603	0.897
1604	1.574
1605	1.65
1606	1.587
1607	1.526
1608	1.379
1609	1.774
1610	1.644
1611	1.861
1612	1.961
1613	1.914
1614	1.753
1615	2.187
1616	2.115
1617	2.075
1618	2.269
1619	1.774
1620	1.59
1621	1.732
1622	1.411
1623	1.408
1624	1.179
1625	0.926
1626	1.179
1627	0.9
1628	1.071
1629	1.13
1630	0.96
1631	0.547
1632	1.425
1633	1.348
1634	1.407
1635	0.663
1636	1.237
1637	1.071
1638	1.382
1639	0.927
1640	0.478
1641	0.739
1642	0.528
1643	0.834
1644	0.855
1645	0.473
1646	0.719
1647	0.825
1648	0.911
1649	0.928
1650	1.289
1651	0.722
1652	0.416
1653	0.748
1654	0.799
1655	1.03
1656	1.017
1657	0.378
1658	0.883
1659	0.65
1660	0.812
1661	0.503
1662	0.512
1663	0.434
1664	0.364
1665	0.424
1666	0.783
1667	0.602
1668	0.548
1669	0.754
1670	0.493
1671	0.456
1672	0.441
1673	0.522
1674	0.367
1675	0.491
1676	0.472
1677	0.341
1678	0.567
1679	0.575
1680	0.397
1681	0.625
1682	0.716
1683	0.697
1684	0.571
1685	0.444
1686	0.436
1687	0.506
1688	0.608
1689	0.757
1690	0.579
1691	0.553
1692	0.618
1693	0.538
1694	0.71
1695	0.685
1696	0.657
1697	0.412
1698	0.602
1699	0.607
1700	0.89
1701	0.979
1702	0.975
1703	0.743
1704	0.858
1705	0.892
1706	0.925
1707	0.983
1708	1.387
1709	0.943
1710	1.083
1711	0.577
1712	0.97
1713	1.269
1714	1.233
1715	1.467
1716	1.121
1717	1.039
1718	1.09
1719	1.075
1720	1.448
1721	1.239
1722	1.511
1723	1.544
1724	1.535
1725	1.233
1726	1.561
1727	1.688
1728	0.888
1729	1.151
1730	1.2
1731	1.386
1732	1.253
1733	1.244
1734	1.117
1735	0.988
1736	1.129
1737	0.987
1738	1.124
1739	1.059
1740	1.069
1741	0.682
1742	0.357
1743	0.772
1744	0.467
1745	0.854
1746	0.694
1747	0.836
1748	1.205
1749	1.425
1750	1.38
1751	0.752
1752	0.968
1753	0.845
1754	0.629
1755	0.808
1756	1.105
1757	0.992
1758	1.395
1759	1.312
1760	1.119
1761	1.69
1762	0.847
1763	1.018
1764	1.07
1765	0.716
1766	0.984
1767	1.039
1768	1.123
1769	0.937
1770	1.199
1771	1.078
1772	1.719
1773	1.271
1774	1.429
1775	0.94
1776	1.135
1777	0.913
1778	1.076
1779	1.054
1780	0.5
1781	1.084
1782	0.793
1783	0.901
1784	1.022
1785	1.137
1786	1.019
1787	0.828
1788	0.905
1789	0.819
1790	0.955
1791	0.946
1792	1.042
1793	0.886
1794	1.052
1795	1.168
1796	1.096
1797	0.961
1798	1.092
1799	0.885
1800	0.984
1801	0.966
1802	1.069
1803	1.112
1804	1.012
1805	1.172
1806	1.11
1807	1.095
1808	1.373
1809	0.984
1810	1.232
1811	1.076
1812	1.08
1813	0.937
1814	0.778
1815	0.792
1816	0.59
1817	0.976
1818	0.931
1819	0.994
1820	1.376
1821	0.955
1822	0.617
1823	0.914
1824	0.844
1825	1.063
1826	0.711
1827	0.651
1828	0.74
1829	0.854
1830	0.919
1831	0.856
1832	0.792
1833	0.717
1834	0.808
1835	0.796
1836	0.691
1837	0.882
1838	0.711
1839	0.736
1840	0.731
1841	0.728
1842	0.677
1843	0.666
1844	0.795
1845	0.74
1846	0.643
1847	0.928
1848	0.995
1849	0.984
1850	0.789
1851	0.804
1852	1.141
1853	1.282
1854	1.134
1855	1.512
1856	0.893
1857	1.35
1858	1.172
1859	0.966
1860	0.852
1861	0.906
1862	0.883
1863	1.341
1864	0.977
1865	1.095
1866	0.943
1867	1.313
1868	1.039
1869	1.15
1870	1.033
1871	0.703
1872	0.844
1873	0.819
1874	0.799
1875	0.713
1876	1.003
1877	1.21
1878	0.919
1879	0.819
1880	0.947
1881	1.064
1882	1.007
1883	0.843
1884	0.805
1885	1.483
1886	0.979
1887	1.148
1888	1.048
1889	1.024
1890	0.956
1891	0.977
1892	0.938
1893	0.849
1894	1.015
1895	1.005
1896	0.816
1897	1.065
1898	0.866
1899	0.538
1900	0.987
1901	0.701
1902	0.915
1903	0.848
1904	0.938
1905	0.842
1906	1.062
1907	1.205
1908	1.086
1909	0.783
1910	0.79
1911	0.948
1912	0.685
1913	0.873
1914	0.799
1915	0.723
1916	0.931
1917	1.053
1918	1.197
1919	0.819
1920	1.029
1921	1.091
1922	0.505
1923	1.23
1924	1.087
1925	1.038
1926	1.067
1927	1.109
1928	1.159
1929	1.243
1930	1.09
1931	0.854
1932	0.972
1933	0.786
1934	0.864
1935	1.099
1936	0.904
1937	1.059
1938	0.867
1939	1.097
1940	0.852
1941	0.944
1942	0.999
1943	1.102
1944	1.203
1945	1.076
1946	1.058
1947	1.016
1948	0.932
1949	0.812
1950	0.924
1951	0.863
1952	1.14
1953	1.114
1954	1.236
1955	1.223
1956	0.992
1957	1.161
1958	1.244
1959	1.062
1960	1.221
1961	1.048
1962	1.016
1963	0.915
1964	0.958
1965	1.042
1966	0.855
1967	0.773
1968	0.713
1969	0.764
1970	0.845
1971	0.854
1972	0.771
1973	0.77
1974	0.751
1975	0.527
1976	0.73
1977	1.076