# northamerica_usa_ia032 - Merritt Forest State Preserve - 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/3173
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
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# Title
#	Study_Name: northamerica_usa_ia032 - Merritt Forest State Preserve - Breitenmoser Tree Ring Chronology Data
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# 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: Merritt Forest State Preserve
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.7
#	Southernmost_Latitude: 42.7
#	Easternmost_Longitude: -91.13
#	Westernmost_Longitude: -91.13
#	Elevation: 330 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ia032B
#	Earliest_Year: 1758
#	Most_Recent_Year: 1980
#	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":"4.70667522466","T2":"16.1541908635","M1":"0.0226253420082","M2":"0.544751583913"}}
#--------------------
# Species
#	Species_Name: white oak
#	Species_Code: QUAL
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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
1758	1.047
1759	0.364
1760	0.812
1761	0.468
1762	0.675
1763	0.431
1764	0.811
1765	0.985
1766	1.485
1767	1.174
1768	1.342
1769	1.314
1770	0.857
1771	0.768
1772	0.658
1773	0.896
1774	0.972
1775	1.191
1776	0.906
1777	0.915
1778	0.768
1779	0.991
1780	0.887
1781	0.997
1782	0.822
1783	0.867
1784	0.859
1785	0.606
1786	0.755
1787	1.044
1788	1.018
1789	0.894
1790	0.743
1791	0.626
1792	0.823
1793	1.04
1794	1.178
1795	0.788
1796	0.73
1797	1.048
1798	0.867
1799	0.758
1800	0.432
1801	0.765
1802	1.027
1803	0.684
1804	0.987
1805	0.825
1806	0.724
1807	0.914
1808	0.47
1809	0.785
1810	0.872
1811	0.793
1812	0.768
1813	0.574
1814	0.918
1815	0.804
1816	0.58
1817	1.104
1818	0.772
1819	1.111
1820	0.662
1821	0.882
1822	1.198
1823	1.14
1824	1.163
1825	1.406
1826	1.527
1827	1.633
1828	1.225
1829	1.096
1830	1.436
1831	1.226
1832	1.359
1833	1.41
1834	1.145
1835	1.039
1836	0.952
1837	0.938
1838	0.734
1839	0.789
1840	1.097
1841	1.207
1842	0.879
1843	0.963
1844	1.047
1845	1.16
1846	0.934
1847	0.913
1848	1.082
1849	0.95
1850	1.106
1851	1.271
1852	0.831
1853	1.045
1854	1.037
1855	0.942
1856	0.945
1857	0.944
1858	1.098
1859	1.227
1860	0.981
1861	1.394
1862	1.385
1863	1.171
1864	1.163
1865	1.047
1866	1.119
1867	1.146
1868	0.891
1869	1.232
1870	0.843
1871	0.952
1872	1.107
1873	0.944
1874	0.902
1875	1.058
1876	1.181
1877	1.1
1878	1.166
1879	1.215
1880	1.34
1881	1.044
1882	1.078
1883	0.869
1884	0.959
1885	1.224
1886	0.726
1887	0.639
1888	0.811
1889	1.212
1890	1.077
1891	0.948
1892	1.157
1893	0.843
1894	0.597
1895	0.41
1896	0.91
1897	1.067
1898	0.851
1899	0.771
1900	0.803
1901	0.826
1902	1.34
1903	1.486
1904	0.975
1905	1.07
1906	1.083
1907	1.445
1908	1.323
1909	1.104
1910	0.64
1911	0.869
1912	1.081
1913	0.856
1914	0.917
1915	1.105
1916	1.005
1917	0.995
1918	0.933
1919	1.013
1920	0.961
1921	0.993
1922	1.112
1923	0.932
1924	1.132
1925	1.012
1926	0.964
1927	0.972
1928	0.931
1929	0.917
1930	1.018
1931	0.641
1932	0.918
1933	0.956
1934	0.549
1935	1.099
1936	0.689
1937	0.957
1938	1.0
1939	0.792
1940	0.82
1941	0.861
1942	0.952
1943	0.886
1944	1.008
1945	1.025
1946	0.935
1947	1.254
1948	0.829
1949	1.063
1950	1.029
1951	1.095
1952	0.82
1953	1.098
1954	1.06
1955	0.878
1956	0.704
1957	0.959
1958	0.947
1959	0.925
1960	0.761
1961	0.989
1962	0.986
1963	0.872
1964	1.015
1965	0.948
1966	1.048
1967	0.836
1968	0.964
1969	1.074
1970	0.801
1971	1.102
1972	1.048
1973	1.034
1974	1.039
1975	0.859
1976	0.842
1977	0.718
1978	1.117
1979	0.897
1980	0.933