# northamerica_usa_pa008 - Longfellow Trail - 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/2993
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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_pa008 - Longfellow Trail - 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: Longfellow Trail
#	Location:
#	Country: United States
#	Northernmost_Latitude: 41.33
#	Southernmost_Latitude: 41.33
#	Easternmost_Longitude: -79.2
#	Westernmost_Longitude: -79.2
#	Elevation: 400 m
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# Data_Collection
#	Collection_Name: northamerica_usa_pa008B
#	Earliest_Year: 1692
#	Most_Recent_Year: 1981
#	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":"4.7963518712","T2":"13.9687793375","M1":"0.0220796181273","M2":"0.327373653436"}}
#--------------------
# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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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
1692	1.226
1693	0.776
1694	1.176
1695	0.987
1696	0.974
1697	0.862
1698	0.885
1699	0.832
1700	1.025
1701	0.945
1702	0.754
1703	0.897
1704	0.881
1705	1.164
1706	1.278
1707	1.133
1708	0.737
1709	0.852
1710	0.861
1711	1.048
1712	1.297
1713	1.423
1714	1.198
1715	1.126
1716	1.095
1717	1.011
1718	1.008
1719	1.162
1720	1.077
1721	0.967
1722	1.017
1723	0.962
1724	1.017
1725	0.867
1726	0.799
1727	0.87
1728	0.94
1729	1.145
1730	1.047
1731	1.166
1732	1.056
1733	0.949
1734	1.15
1735	0.928
1736	0.906
1737	0.957
1738	1.044
1739	1.231
1740	1.082
1741	0.823
1742	0.769
1743	0.694
1744	0.912
1745	1.208
1746	0.813
1747	1.178
1748	0.849
1749	1.044
1750	1.054
1751	0.877
1752	0.822
1753	0.923
1754	1.025
1755	0.588
1756	1.012
1757	0.705
1758	0.888
1759	0.884
1760	0.921
1761	1.109
1762	0.841
1763	1.004
1764	1.112
1765	1.294
1766	0.937
1767	0.843
1768	1.022
1769	0.929
1770	0.982
1771	1.079
1772	0.811
1773	0.896
1774	1.037
1775	0.871
1776	0.933
1777	0.963
1778	0.922
1779	0.978
1780	0.8
1781	1.011
1782	0.933
1783	1.029
1784	1.052
1785	0.878
1786	1.102
1787	1.061
1788	0.985
1789	0.752
1790	0.767
1791	0.889
1792	0.876
1793	1.08
1794	1.171
1795	1.067
1796	1.078
1797	1.081
1798	0.942
1799	0.883
1800	1.027
1801	1.207
1802	1.117
1803	0.848
1804	0.923
1805	0.825
1806	0.85
1807	0.915
1808	0.829
1809	1.029
1810	1.298
1811	1.07
1812	1.047
1813	0.883
1814	0.921
1815	0.826
1816	0.893
1817	0.979
1818	0.651
1819	0.939
1820	0.87
1821	0.987
1822	0.806
1823	0.766
1824	0.783
1825	0.762
1826	0.734
1827	1.005
1828	1.116
1829	0.995
1830	1.281
1831	1.115
1832	1.058
1833	1.161
1834	1.133
1835	0.968
1836	0.859
1837	0.892
1838	0.758
1839	0.662
1840	0.687
1841	0.706
1842	0.959
1843	0.797
1844	1.077
1845	0.87
1846	0.986
1847	0.873
1848	0.948
1849	0.832
1850	1.192
1851	1.329
1852	1.034
1853	0.949
1854	0.909
1855	1.211
1856	0.761
1857	1.101
1858	1.058
1859	1.311
1860	1.128
1861	0.855
1862	0.889
1863	0.92
1864	0.784
1865	0.994
1866	0.876
1867	0.974
1868	0.957
1869	1.123
1870	0.908
1871	1.008
1872	1.235
1873	1.088
1874	0.974
1875	1.028
1876	0.836
1877	0.802
1878	1.177
1879	1.169
1880	1.114
1881	1.013
1882	1.153
1883	1.174
1884	1.41
1885	1.25
1886	1.283
1887	0.995
1888	1.414
1889	1.325
1890	1.035
1891	0.879
1892	1.099
1893	1.31
1894	1.244
1895	1.329
1896	1.498
1897	1.438
1898	1.574
1899	1.564
1900	1.317
1901	1.29
1902	1.598
1903	1.397
1904	0.821
1905	1.165
1906	1.069
1907	0.772
1908	0.832
1909	0.818
1910	0.83
1911	0.842
1912	1.042
1913	1.087
1914	0.903
1915	1.16
1916	0.67
1917	0.661
1918	0.607
1919	0.592
1920	0.501
1921	0.78
1922	0.791
1923	0.809
1924	1.101
1925	1.178
1926	0.966
1927	0.948
1928	0.794
1929	0.988
1930	0.862
1931	1.067
1932	1.117
1933	1.079
1934	0.925
1935	1.181
1936	1.079
1937	1.167
1938	0.93
1939	0.779
1940	0.88
1941	0.905
1942	1.138
1943	0.613
1944	0.659
1945	0.936
1946	0.75
1947	0.805
1948	0.819
1949	0.901
1950	1.011
1951	0.808
1952	0.62
1953	0.871
1954	0.97
1955	1.011
1956	0.985
1957	1.072
1958	0.799
1959	0.585
1960	0.671
1961	0.88
1962	0.766
1963	1.006
1964	0.997
1965	0.802
1966	0.628
1967	0.701
1968	0.746
1969	0.673
1970	0.585
1971	0.639
1972	0.659
1973	0.804
1974	1.098
1975	1.374
1976	1.629
1977	1.698
1978	1.145
1979	1.078
1980	1.292
1981	1.18