# northamerica_usa_ak025 - Tebenkof Glacier - 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.
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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/5249
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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_ak025 - Tebenkof Glacier - 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: Tebenkof Glacier
#	Location:
#	Country: United States
#	Northernmost_Latitude: 60.75
#	Southernmost_Latitude: 60.75
#	Easternmost_Longitude: -148.45
#	Westernmost_Longitude: -148.45
#	Elevation: 25 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak025B
#	Earliest_Year: 1690
#	Most_Recent_Year: 1991
#	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":"5.78071557088","T2":"18.8916656498","M1":"0.0219924522048","M2":"0.289448382216"}}
#--------------------
# Species
#	Species_Name: mountain hemlock
#	Species_Code: TSME
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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
1690	1.021
1691	1.363
1692	1.761
1693	1.209
1694	1.054
1695	1.029
1696	0.882
1697	0.687
1698	0.613
1699	0.652
1700	1.043
1701	1.355
1702	1.157
1703	1.404
1704	1.17
1705	1.289
1706	0.738
1707	1.092
1708	0.961
1709	1.34
1710	0.96
1711	0.861
1712	1.313
1713	1.373
1714	0.972
1715	1.216
1716	0.556
1717	0.776
1718	1.298
1719	1.514
1720	1.088
1721	1.07
1722	1.087
1723	1.193
1724	1.231
1725	1.218
1726	1.006
1727	0.918
1728	1.163
1729	1.263
1730	1.017
1731	1.215
1732	1.301
1733	1.36
1734	1.004
1735	1.02
1736	0.979
1737	1.17
1738	1.011
1739	1.262
1740	0.866
1741	0.935
1742	1.021
1743	0.801
1744	0.234
1745	0.773
1746	0.761
1747	0.989
1748	1.088
1749	1.448
1750	1.279
1751	1.123
1752	0.822
1753	0.729
1754	0.49
1755	0.666
1756	0.504
1757	0.757
1758	0.9
1759	0.876
1760	1.159
1761	1.039
1762	1.428
1763	1.375
1764	1.006
1765	1.396
1766	1.096
1767	1.086
1768	0.759
1769	0.688
1770	0.638
1771	0.536
1772	1.012
1773	1.253
1774	1.407
1775	1.237
1776	0.81
1777	1.049
1778	0.603
1779	0.85
1780	1.141
1781	1.052
1782	1.136
1783	1.015
1784	1.054
1785	0.992
1786	0.864
1787	0.77
1788	0.624
1789	0.915
1790	0.607
1791	0.863
1792	0.82
1793	0.791
1794	0.737
1795	0.997
1796	0.799
1797	1.127
1798	0.888
1799	1.029
1800	0.672
1801	1.114
1802	0.985
1803	0.883
1804	0.586
1805	0.74
1806	0.996
1807	1.237
1808	1.142
1809	0.822
1810	0.918
1811	0.833
1812	1.172
1813	1.216
1814	0.854
1815	1.084
1816	1.263
1817	1.302
1818	1.287
1819	1.188
1820	1.45
1821	1.353
1822	1.609
1823	1.485
1824	1.177
1825	1.093
1826	0.701
1827	0.838
1828	1.381
1829	1.641
1830	0.976
1831	0.65
1832	1.097
1833	1.228
1834	1.279
1835	0.982
1836	0.91
1837	0.577
1838	1.213
1839	1.477
1840	1.321
1841	1.144
1842	1.028
1843	0.942
1844	1.258
1845	1.127
1846	0.899
1847	0.681
1848	0.538
1849	0.627
1850	0.682
1851	1.07
1852	0.98
1853	0.953
1854	0.701
1855	0.922
1856	0.648
1857	0.761
1858	0.674
1859	0.712
1860	0.491
1861	0.853
1862	0.892
1863	0.654
1864	0.845
1865	0.845
1866	1.03
1867	1.274
1868	1.065
1869	0.397
1870	0.776
1871	0.674
1872	0.834
1873	1.025
1874	0.888
1875	0.765
1876	0.454
1877	0.321
1878	0.443
1879	0.427
1880	0.363
1881	0.456
1882	0.354
1883	0.543
1884	1.114
1885	1.107
1886	1.076
1887	0.564
1888	0.742
1889	0.667
1890	0.649
1891	0.716
1892	1.136
1893	1.012
1894	0.327
1895	0.485
1896	0.704
1897	0.609
1898	0.681
1899	0.619
1900	0.859
1901	1.023
1902	0.971
1903	0.584
1904	0.522
1905	0.77
1906	0.918
1907	0.626
1908	0.644
1909	0.84
1910	0.726
1911	1.118
1912	0.989
1913	0.911
1914	1.086
1915	1.295
1916	1.274
1917	1.519
1918	1.454
1919	1.354
1920	1.494
1921	1.352
1922	1.1
1923	1.11
1924	1.617
1925	1.438
1926	1.352
1927	0.836
1928	0.481
1929	0.817
1930	1.255
1931	1.337
1932	1.199
1933	1.453
1934	1.343
1935	1.439
1936	1.266
1937	0.781
1938	0.591
1939	1.087
1940	1.074
1941	1.086
1942	1.629
1943	1.586
1944	1.065
1945	1.181
1946	1.184
1947	1.482
1948	1.235
1949	1.076
1950	1.361
1951	1.069
1952	1.048
1953	1.283
1954	1.013
1955	0.482
1956	0.467
1957	1.218
1958	0.869
1959	0.99
1960	1.052
1961	0.98
1962	1.047
1963	1.132
1964	1.18
1965	0.942
1966	1.178
1967	1.258
1968	1.217
1969	0.952
1970	1.039
1971	0.681
1972	1.015
1973	0.687
1974	1.154
1975	0.673
1976	1.28
1977	0.813
1978	0.763
1979	0.962
1980	0.762
1981	1.247
1982	1.028
1983	1.183
1984	1.124
1985	0.925
1986	0.852
1987	0.567
1988	0.655
1989	0.682
1990	0.703
1991	0.712