# northamerica_usa_ak027 - Turnagain Pass - 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/3614
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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_ak027 - Turnagain Pass - 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 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.
#--------------------
#	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: Turnagain Pass
#	Location:
#	Country: United States
#	Northernmost_Latitude: 60.82
#	Southernmost_Latitude: 60.82
#	Easternmost_Longitude: -149.17
#	Westernmost_Longitude: -149.17
#	Elevation: 400 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ak027B
#	Earliest_Year: 1734
#	Most_Recent_Year: 1990
#	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":"5.01975832031","T2":"19.2789526506","M1":"0.0221632763992","M2":"0.276491128329"}}
#--------------------
# 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
1734	0.909
1735	1.09
1736	1.033
1737	0.95
1738	0.859
1739	0.917
1740	0.867
1741	0.645
1742	0.751
1743	0.752
1744	0.556
1745	0.922
1746	0.961
1747	1.262
1748	1.275
1749	1.371
1750	1.427
1751	1.169
1752	0.682
1753	0.809
1754	0.568
1755	0.51
1756	0.561
1757	0.502
1758	0.639
1759	0.715
1760	0.881
1761	0.991
1762	0.996
1763	1.254
1764	1.248
1765	1.227
1766	1.009
1767	1.11
1768	0.891
1769	0.766
1770	0.876
1771	0.976
1772	1.014
1773	0.812
1774	1.0
1775	0.658
1776	0.83
1777	0.994
1778	0.719
1779	0.784
1780	0.831
1781	1.012
1782	1.12
1783	1.379
1784	1.426
1785	1.36
1786	1.071
1787	0.853
1788	0.591
1789	0.687
1790	0.617
1791	0.854
1792	1.112
1793	1.276
1794	1.365
1795	1.804
1796	1.707
1797	1.769
1798	1.262
1799	1.314
1800	0.724
1801	0.834
1802	0.947
1803	0.98
1804	1.174
1805	1.099
1806	0.876
1807	0.87
1808	0.969
1809	0.811
1810	0.693
1811	0.665
1812	0.473
1813	0.654
1814	0.598
1815	0.91
1816	1.078
1817	0.902
1818	1.106
1819	0.947
1820	1.079
1821	0.764
1822	1.195
1823	1.16
1824	1.377
1825	1.555
1826	1.278
1827	0.888
1828	1.353
1829	1.303
1830	0.703
1831	0.64
1832	0.879
1833	1.05
1834	0.873
1835	0.954
1836	1.08
1837	0.91
1838	1.174
1839	1.208
1840	1.002
1841	1.156
1842	0.753
1843	0.915
1844	1.076
1845	1.071
1846	1.017
1847	1.027
1848	0.871
1849	0.656
1850	0.787
1851	0.885
1852	1.145
1853	1.058
1854	0.819
1855	0.882
1856	0.764
1857	0.869
1858	0.708
1859	0.659
1860	0.901
1861	1.003
1862	0.864
1863	0.857
1864	1.244
1865	1.214
1866	1.26
1867	1.211
1868	1.013
1869	0.953
1870	0.998
1871	0.748
1872	1.07
1873	0.854
1874	1.023
1875	1.065
1876	0.599
1877	0.472
1878	0.437
1879	0.442
1880	0.469
1881	0.622
1882	0.776
1883	0.932
1884	1.296
1885	1.149
1886	1.173
1887	0.698
1888	0.606
1889	0.823
1890	0.832
1891	1.232
1892	1.419
1893	1.568
1894	0.792
1895	0.936
1896	0.908
1897	0.762
1898	0.902
1899	1.125
1900	1.09
1901	0.967
1902	1.041
1903	0.953
1904	0.951
1905	1.397
1906	1.294
1907	1.005
1908	1.029
1909	1.155
1910	1.02
1911	1.187
1912	0.829
1913	0.98
1914	1.223
1915	1.716
1916	1.247
1917	1.246
1918	1.316
1919	1.048
1920	1.185
1921	1.245
1922	1.094
1923	1.143
1924	1.29
1925	1.178
1926	1.456
1927	0.831
1928	0.647
1929	0.542
1930	0.993
1931	0.968
1932	1.145
1933	1.196
1934	1.241
1935	1.122
1936	0.813
1937	0.574
1938	0.533
1939	0.591
1940	0.583
1941	0.951
1942	1.165
1943	1.261
1944	0.601
1945	0.829
1946	1.011
1947	1.341
1948	1.114
1949	1.078
1950	1.075
1951	1.105
1952	0.865
1953	1.118
1954	0.774
1955	0.642
1956	0.773
1957	1.118
1958	0.841
1959	0.882
1960	0.798
1961	0.913
1962	0.922
1963	1.056
1964	0.823
1965	0.824
1966	0.694
1967	0.813
1968	1.092
1969	1.159
1970	1.045
1971	0.954
1972	0.65
1973	0.61
1974	1.131
1975	0.912
1976	1.04
1977	0.874
1978	0.794
1979	0.917
1980	0.853
1981	1.381
1982	1.148
1983	1.202
1984	1.28
1985	1.177
1986	0.962
1987	0.581
1988	0.722
1989	0.778
1990	1.098