# northamerica_usa_nh005 - Rattlesnake Mountain and Town Pound, Rumney - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		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/8503
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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_nh005 - Rattlesnake Mountain and Town Pound, Rumney - 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: Rattlesnake Mountain and Town Pound, Rumney
#	Location:
#	Country: United States
#	Northernmost_Latitude: 43.8
#	Southernmost_Latitude: 43.8
#	Easternmost_Longitude: -71.83
#	Westernmost_Longitude: -71.83
#	Elevation: 300 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nh005B
#	Earliest_Year: 1780
#	Most_Recent_Year: 2008
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"3.12870946572","T2":"13.8717299929","M1":"0.0229472722947","M2":"0.602818243203"}}
#--------------------
# Species
#	Species_Name: red pine
#	Species_Code: PIRE
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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
1780	0.839
1781	0.84
1782	0.98
1783	1.085
1784	0.858
1785	0.922
1786	1.22
1787	1.329
1788	1.582
1789	1.119
1790	1.077
1791	0.807
1792	0.806
1793	0.765
1794	0.915
1795	1.001
1796	0.935
1797	1.014
1798	0.684
1799	0.749
1800	0.76
1801	0.879
1802	0.944
1803	0.887
1804	0.851
1805	1.137
1806	0.796
1807	1.157
1808	1.176
1809	1.265
1810	0.981
1811	1.049
1812	1.373
1813	1.355
1814	1.316
1815	1.288
1816	1.081
1817	1.125
1818	0.935
1819	0.893
1820	0.914
1821	0.844
1822	0.862
1823	0.96
1824	1.067
1825	1.223
1826	0.675
1827	0.992
1828	0.948
1829	0.949
1830	0.939
1831	1.138
1832	0.835
1833	1.053
1834	1.086
1835	1.118
1836	0.943
1837	0.862
1838	0.916
1839	1.259
1840	0.848
1841	0.819
1842	1.188
1843	1.232
1844	1.286
1845	1.06
1846	1.105
1847	0.736
1848	1.158
1849	0.82
1850	1.085
1851	1.212
1852	0.759
1853	0.828
1854	0.622
1855	0.948
1856	0.918
1857	1.159
1858	1.186
1859	0.896
1860	0.967
1861	1.385
1862	1.024
1863	1.019
1864	0.777
1865	0.961
1866	0.862
1867	0.817
1868	0.705
1869	0.83
1870	0.518
1871	0.627
1872	0.818
1873	0.718
1874	0.636
1875	0.556
1876	0.362
1877	0.329
1878	0.567
1879	0.6
1880	0.989
1881	1.018
1882	0.954
1883	0.979
1884	0.75
1885	0.991
1886	0.867
1887	0.815
1888	0.831
1889	0.987
1890	1.072
1891	1.278
1892	1.358
1893	0.91
1894	1.131
1895	0.963
1896	0.806
1897	1.022
1898	1.058
1899	0.932
1900	0.714
1901	0.899
1902	1.172
1903	0.91
1904	1.085
1905	1.257
1906	1.198
1907	0.984
1908	0.853
1909	0.997
1910	1.01
1911	0.695
1912	1.008
1913	1.058
1914	1.074
1915	1.302
1916	1.463
1917	1.399
1918	1.424
1919	1.007
1920	0.998
1921	0.906
1922	1.23
1923	0.721
1924	0.977
1925	1.198
1926	0.885
1927	1.21
1928	1.281
1929	1.329
1930	1.235
1931	1.441
1932	0.962
1933	0.665
1934	1.054
1935	1.034
1936	0.833
1937	1.191
1938	1.135
1939	0.901
1940	0.949
1941	0.913
1942	0.987
1943	0.902
1944	0.986
1945	1.394
1946	1.434
1947	1.079
1948	0.839
1949	0.743
1950	0.76
1951	0.845
1952	0.933
1953	0.854
1954	1.011
1955	0.926
1956	1.022
1957	1.061
1958	1.062
1959	0.885
1960	1.014
1961	1.009
1962	0.884
1963	0.958
1964	0.562
1965	0.733
1966	0.807
1967	1.064
1968	1.464
1969	1.164
1970	0.787
1971	0.673
1972	0.891
1973	0.929
1974	1.05
1975	0.731
1976	0.955
1977	0.91
1978	0.665
1979	0.749
1980	0.884
1981	0.84
1982	0.933
1983	0.913
1984	1.305
1985	0.915
1986	1.152
1987	1.225
1988	0.889
1989	1.294
1990	1.227
1991	0.907
1992	1.243
1993	1.096
1994	1.255
1995	1.088
1996	1.317
1997	0.905
1998	1.182
1999	0.729
2000	1.225
2001	0.883
2002	1.061
2003	0.893
2004	1.019
2005	0.848
2006	1.191
2007	1.023
2008	0.865