# northamerica_usa_mo015 - Wegener Woods - 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/4954
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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_mo015 - Wegener Woods - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Wegener Woods
#	Location:
#	Country: United States
#	Northernmost_Latitude: 38.65
#	Southernmost_Latitude: 38.65
#	Easternmost_Longitude: -91.5
#	Westernmost_Longitude: -91.5
#	Elevation: 180 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mo015B
#	Earliest_Year: 1710
#	Most_Recent_Year: 1982
#	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":"5.26499061908","T2":"17.7385271088","M1":"0.0227104942274","M2":"0.544664860035"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1710	0.617
1711	0.756
1712	0.761
1713	0.614
1714	0.889
1715	1.003
1716	1.298
1717	1.033
1718	1.303
1719	0.667
1720	0.895
1721	0.376
1722	0.793
1723	0.838
1724	0.489
1725	0.684
1726	0.633
1727	0.739
1728	0.532
1729	0.735
1730	0.739
1731	0.535
1732	0.917
1733	0.854
1734	1.2
1735	0.717
1736	0.542
1737	0.999
1738	1.201
1739	0.986
1740	1.01
1741	0.934
1742	0.762
1743	0.65
1744	0.826
1745	1.015
1746	0.67
1747	0.835
1748	0.893
1749	0.824
1750	0.965
1751	0.648
1752	0.899
1753	0.561
1754	0.794
1755	1.078
1756	1.32
1757	0.923
1758	0.905
1759	1.232
1760	0.601
1761	0.919
1762	0.747
1763	1.219
1764	1.286
1765	1.282
1766	1.426
1767	0.961
1768	1.406
1769	1.627
1770	1.363
1771	1.079
1772	0.95
1773	0.897
1774	0.428
1775	1.211
1776	1.252
1777	1.057
1778	1.204
1779	1.187
1780	0.953
1781	1.386
1782	1.338
1783	1.195
1784	1.292
1785	1.061
1786	1.061
1787	0.91
1788	1.057
1789	1.037
1790	1.134
1791	1.038
1792	0.896
1793	1.035
1794	0.999
1795	0.934
1796	1.148
1797	1.222
1798	1.161
1799	0.749
1800	0.803
1801	0.941
1802	1.026
1803	0.492
1804	0.472
1805	0.643
1806	0.904
1807	1.213
1808	1.004
1809	0.846
1810	1.1
1811	1.025
1812	0.97
1813	0.94
1814	1.262
1815	0.512
1816	0.755
1817	1.038
1818	1.273
1819	1.211
1820	1.175
1821	0.961
1822	0.855
1823	0.748
1824	0.858
1825	1.028
1826	0.75
1827	1.463
1828	1.029
1829	0.661
1830	1.051
1831	0.934
1832	0.933
1833	1.151
1834	0.712
1835	1.253
1836	1.162
1837	1.345
1838	1.076
1839	1.158
1840	1.091
1841	0.9
1842	1.128
1843	0.973
1844	1.217
1845	0.975
1846	0.898
1847	0.875
1848	1.053
1849	1.109
1850	1.01
1851	0.854
1852	1.085
1853	0.911
1854	1.101
1855	1.135
1856	1.023
1857	0.853
1858	0.932
1859	0.995
1860	0.918
1861	1.005
1862	1.105
1863	0.882
1864	0.881
1865	1.194
1866	1.077
1867	0.943
1868	0.884
1869	1.296
1870	1.0
1871	0.993
1872	1.006
1873	0.999
1874	0.82
1875	1.11
1876	1.044
1877	0.861
1878	0.884
1879	0.753
1880	0.997
1881	0.758
1882	1.221
1883	1.236
1884	1.15
1885	0.935
1886	1.11
1887	0.799
1888	0.969
1889	1.549
1890	0.952
1891	0.942
1892	1.099
1893	1.046
1894	0.702
1895	0.811
1896	0.671
1897	1.208
1898	1.239
1899	0.808
1900	1.015
1901	0.796
1902	0.903
1903	1.171
1904	1.421
1905	1.011
1906	1.18
1907	1.374
1908	1.18
1909	1.201
1910	0.94
1911	0.921
1912	1.344
1913	0.821
1914	0.711
1915	1.362
1916	1.047
1917	0.76
1918	0.722
1919	1.046
1920	0.925
1921	0.838
1922	0.885
1923	1.007
1924	1.199
1925	0.906
1926	1.113
1927	1.08
1928	1.269
1929	1.019
1930	0.851
1931	0.708
1932	0.859
1933	0.945
1934	0.783
1935	1.02
1936	0.597
1937	1.08
1938	1.208
1939	0.981
1940	0.899
1941	0.889
1942	1.055
1943	0.793
1944	0.831
1945	1.113
1946	0.919
1947	1.035
1948	1.071
1949	1.145
1950	1.043
1951	1.187
1952	0.868
1953	0.962
1954	0.673
1955	1.028
1956	0.789
1957	0.944
1958	0.963
1959	0.864
1960	0.948
1961	1.079
1962	1.049
1963	0.724
1964	0.85
1965	0.701
1966	0.822
1967	0.912
1968	0.898
1969	1.032
1970	0.939
1971	0.876
1972	0.735
1973	1.275
1974	1.076
1975	0.913
1976	0.988
1977	0.824
1978	1.028
1979	0.794
1980	0.672
1981	1.018
1982	1.223