# northamerica_usa_ak086 - Fish Trap - 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/5561
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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_ak086 - Fish Trap - 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: Fish Trap
#	Location:
#	Country: United States
#	Northernmost_Latitude: 60.48
#	Southernmost_Latitude: 60.48
#	Easternmost_Longitude: -154.33
#	Westernmost_Longitude: -154.33
#	Elevation: 550 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak086B
#	Earliest_Year: 1702
#	Most_Recent_Year: 2003
#	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":"5.0513910025","T2":"18.5944403982","M1":"0.0223625961532","M2":"0.326827861084"}}
#--------------------
# 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
1702	0.953
1703	1.02
1704	0.824
1705	0.895
1706	0.703
1707	1.004
1708	0.788
1709	0.74
1710	0.76
1711	0.779
1712	1.01
1713	0.986
1714	1.008
1715	1.298
1716	1.153
1717	1.027
1718	1.073
1719	1.035
1720	1.462
1721	1.135
1722	1.15
1723	1.128
1724	0.972
1725	1.051
1726	0.965
1727	0.785
1728	0.682
1729	0.725
1730	0.708
1731	0.67
1732	0.968
1733	1.064
1734	1.124
1735	0.893
1736	0.709
1737	0.857
1738	0.893
1739	0.796
1740	0.717
1741	0.923
1742	0.876
1743	1.075
1744	0.784
1745	1.038
1746	0.736
1747	0.898
1748	0.855
1749	0.95
1750	1.086
1751	0.908
1752	1.192
1753	0.976
1754	0.766
1755	0.709
1756	0.794
1757	0.629
1758	0.835
1759	0.921
1760	1.201
1761	1.008
1762	1.034
1763	1.064
1764	1.02
1765	1.297
1766	1.411
1767	1.43
1768	1.29
1769	1.264
1770	1.116
1771	1.073
1772	1.048
1773	1.084
1774	1.068
1775	1.103
1776	0.921
1777	0.978
1778	0.886
1779	0.965
1780	0.677
1781	1.015
1782	0.843
1783	1.074
1784	0.751
1785	1.05
1786	0.938
1787	0.952
1788	0.954
1789	0.812
1790	0.814
1791	0.866
1792	0.901
1793	0.984
1794	1.312
1795	1.366
1796	1.282
1797	1.257
1798	0.658
1799	0.628
1800	0.837
1801	0.803
1802	0.855
1803	0.906
1804	0.595
1805	0.92
1806	0.798
1807	0.768
1808	0.947
1809	0.616
1810	0.543
1811	0.539
1812	0.627
1813	0.704
1814	0.629
1815	0.635
1816	0.698
1817	0.805
1818	0.878
1819	1.252
1820	1.264
1821	1.359
1822	1.237
1823	1.274
1824	0.933
1825	0.9
1826	0.933
1827	1.12
1828	1.04
1829	1.04
1830	1.246
1831	1.193
1832	1.413
1833	1.163
1834	1.129
1835	0.857
1836	1.018
1837	0.982
1838	1.335
1839	1.0
1840	1.113
1841	1.024
1842	0.955
1843	1.318
1844	1.466
1845	1.154
1846	1.034
1847	0.938
1848	1.255
1849	0.985
1850	0.994
1851	0.845
1852	1.305
1853	1.167
1854	0.931
1855	0.943
1856	0.684
1857	0.942
1858	1.044
1859	1.291
1860	1.082
1861	1.068
1862	0.987
1863	1.251
1864	1.625
1865	1.277
1866	0.95
1867	1.161
1868	0.824
1869	0.819
1870	1.001
1871	0.807
1872	0.96
1873	1.054
1874	0.907
1875	0.906
1876	0.949
1877	0.688
1878	0.676
1879	0.761
1880	0.799
1881	0.732
1882	0.845
1883	0.656
1884	0.739
1885	0.818
1886	0.938
1887	1.11
1888	1.096
1889	1.117
1890	1.196
1891	0.998
1892	1.147
1893	0.968
1894	1.021
1895	0.753
1896	0.998
1897	1.14
1898	1.039
1899	0.974
1900	0.838
1901	0.792
1902	0.733
1903	0.729
1904	0.699
1905	0.898
1906	0.886
1907	0.881
1908	0.753
1909	0.793
1910	0.681
1911	0.97
1912	0.563
1913	0.857
1914	0.664
1915	1.06
1916	1.304
1917	1.482
1918	1.345
1919	0.963
1920	1.143
1921	0.936
1922	0.712
1923	0.666
1924	0.632
1925	0.743
1926	0.617
1927	0.796
1928	0.772
1929	0.579
1930	0.504
1931	0.287
1932	0.367
1933	0.503
1934	0.731
1935	0.86
1936	0.803
1937	0.868
1938	0.733
1939	0.885
1940	0.619
1941	0.821
1942	0.977
1943	1.375
1944	1.235
1945	1.167
1946	1.133
1947	1.412
1948	1.579
1949	1.356
1950	1.346
1951	1.28
1952	1.237
1953	1.451
1954	1.217
1955	1.198
1956	1.245
1957	1.28
1958	0.936
1959	1.195
1960	1.101
1961	0.964
1962	0.762
1963	0.82
1964	1.136
1965	0.833
1966	1.027
1967	1.209
1968	1.123
1969	1.373
1970	1.217
1971	1.444
1972	1.237
1973	0.825
1974	1.035
1975	1.057
1976	1.011
1977	0.872
1978	0.701
1979	0.941
1980	1.048
1981	0.885
1982	0.993
1983	0.696
1984	0.89
1985	1.002
1986	0.809
1987	0.648
1988	1.078
1989	0.765
1990	0.956
1991	1.039
1992	1.221
1993	1.056
1994	1.394
1995	1.387
1996	1.373
1997	1.497
1998	0.924
1999	1.234
2000	0.998
2001	0.997
2002	1.202
2003	1.033