# northamerica_usa_ak008 - Moose Pass Seward - 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/4537
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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_ak008 - Moose Pass Seward - 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.
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#	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: Moose Pass Seward
#	Location:
#	Country: United States
#	Northernmost_Latitude: 60.5
#	Southernmost_Latitude: 60.5
#	Easternmost_Longitude: -149.5
#	Westernmost_Longitude: -149.5
#	Elevation: 100 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ak008B
#	Earliest_Year: 1753
#	Most_Recent_Year: 1983
#	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":"5.60901194764","T2":"18.7966417128","M1":"0.0224426302688","M2":"0.311690507967"}}
#--------------------
# Species
#	Species_Name: Sitka spruce
#	Species_Code: PCSI
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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
1753	0.979
1754	0.676
1755	0.799
1756	0.752
1757	0.642
1758	0.661
1759	0.652
1760	0.534
1761	0.8
1762	0.662
1763	0.677
1764	0.77
1765	0.916
1766	0.931
1767	1.052
1768	0.821
1769	0.655
1770	0.659
1771	0.754
1772	1.057
1773	1.032
1774	1.079
1775	0.956
1776	1.332
1777	1.416
1778	0.941
1779	0.812
1780	0.92
1781	0.818
1782	1.196
1783	0.853
1784	1.15
1785	1.077
1786	1.109
1787	1.003
1788	1.023
1789	1.028
1790	0.951
1791	0.873
1792	0.973
1793	0.838
1794	0.984
1795	1.214
1796	1.131
1797	1.688
1798	1.139
1799	1.1
1800	0.931
1801	1.121
1802	1.263
1803	1.008
1804	1.097
1805	0.965
1806	1.022
1807	1.173
1808	1.281
1809	0.939
1810	0.97
1811	0.881
1812	1.063
1813	0.934
1814	0.615
1815	0.807
1816	1.035
1817	0.838
1818	0.912
1819	1.155
1820	1.197
1821	1.067
1822	0.995
1823	1.252
1824	0.949
1825	0.901
1826	0.862
1827	0.938
1828	1.044
1829	1.385
1830	1.07
1831	0.945
1832	1.482
1833	1.219
1834	0.978
1835	1.187
1836	1.037
1837	0.501
1838	1.04
1839	0.919
1840	1.177
1841	1.296
1842	0.981
1843	0.989
1844	1.104
1845	1.153
1846	0.95
1847	1.014
1848	0.878
1849	0.858
1850	0.955
1851	0.952
1852	0.991
1853	0.954
1854	1.004
1855	0.969
1856	0.628
1857	0.887
1858	0.741
1859	0.848
1860	0.969
1861	0.966
1862	0.898
1863	0.89
1864	0.838
1865	0.917
1866	0.962
1867	1.012
1868	0.788
1869	0.438
1870	0.62
1871	0.42
1872	0.731
1873	0.856
1874	1.007
1875	0.8
1876	0.703
1877	0.49
1878	0.461
1879	0.511
1880	0.623
1881	0.889
1882	0.769
1883	0.831
1884	1.248
1885	0.887
1886	0.925
1887	0.921
1888	1.265
1889	0.861
1890	1.363
1891	1.878
1892	1.916
1893	1.587
1894	1.266
1895	1.214
1896	1.355
1897	1.342
1898	0.911
1899	1.313
1900	1.183
1901	1.132
1902	1.164
1903	1.038
1904	0.9
1905	1.242
1906	0.953
1907	1.015
1908	1.249
1909	1.333
1910	1.125
1911	1.061
1912	0.839
1913	1.073
1914	1.214
1915	1.726
1916	1.236
1917	1.555
1918	1.719
1919	1.301
1920	1.293
1921	1.348
1922	0.883
1923	1.024
1924	0.992
1925	0.973
1926	0.896
1927	0.393
1928	0.437
1929	0.712
1930	0.94
1931	1.126
1932	1.11
1933	1.216
1934	1.126
1935	1.059
1936	1.055
1937	0.528
1938	0.483
1939	0.638
1940	0.782
1941	0.65
1942	0.934
1943	0.887
1944	1.09
1945	1.167
1946	1.238
1947	1.336
1948	1.39
1949	1.202
1950	1.137
1951	0.97
1952	0.786
1953	0.849
1954	0.745
1955	0.627
1956	0.806
1957	0.968
1958	0.702
1959	1.012
1960	1.071
1961	0.943
1962	0.886
1963	0.895
1964	0.949
1965	0.736
1966	0.821
1967	0.901
1968	1.041
1969	0.999
1970	0.723
1971	0.796
1972	0.658
1973	0.518
1974	0.7
1975	0.679
1976	0.88
1977	0.765
1978	0.451
1979	0.829
1980	0.76
1981	1.168
1982	0.92
1983	0.927