# northamerica_usa_ia021 - Saylorville Dam - 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/3181
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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_ia021 - Saylorville Dam - 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: Saylorville Dam
#	Location:
#	Country: United States
#	Northernmost_Latitude: 41.72
#	Southernmost_Latitude: 41.72
#	Easternmost_Longitude: -93.7
#	Westernmost_Longitude: -93.7
#	Elevation: 320 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ia021B
#	Earliest_Year: 1710
#	Most_Recent_Year: 1981
#	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":"4.08605767169","T2":"15.7289871333","M1":"0.022714493514","M2":"0.554543164333"}}
#--------------------
# 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	0.826
1711	1.039
1712	1.15
1713	1.127
1714	0.964
1715	1.036
1716	0.926
1717	1.008
1718	0.71
1719	0.941
1720	1.108
1721	0.708
1722	1.276
1723	1.222
1724	0.611
1725	0.707
1726	1.034
1727	1.061
1728	0.788
1729	0.972
1730	0.943
1731	0.801
1732	0.999
1733	0.92
1734	0.742
1735	0.724
1736	0.586
1737	0.675
1738	0.727
1739	0.708
1740	0.692
1741	0.926
1742	0.563
1743	0.543
1744	0.669
1745	1.199
1746	0.988
1747	0.889
1748	0.724
1749	0.854
1750	1.072
1751	0.945
1752	0.737
1753	0.733
1754	0.972
1755	0.899
1756	0.721
1757	0.862
1758	0.926
1759	0.935
1760	0.858
1761	1.207
1762	1.03
1763	0.882
1764	0.967
1765	0.815
1766	1.191
1767	0.835
1768	1.029
1769	0.902
1770	0.845
1771	0.607
1772	0.626
1773	0.675
1774	0.991
1775	1.081
1776	0.852
1777	1.057
1778	0.751
1779	0.766
1780	1.051
1781	1.662
1782	1.34
1783	0.852
1784	1.12
1785	1.25
1786	1.303
1787	1.246
1788	1.026
1789	1.173
1790	0.988
1791	0.843
1792	1.123
1793	1.102
1794	1.128
1795	1.097
1796	0.738
1797	0.884
1798	0.79
1799	0.838
1800	0.475
1801	1.165
1802	1.536
1803	0.898
1804	1.166
1805	1.275
1806	1.087
1807	1.182
1808	0.934
1809	0.805
1810	0.894
1811	1.052
1812	0.798
1813	0.986
1814	1.183
1815	1.045
1816	0.678
1817	0.942
1818	0.801
1819	0.769
1820	0.559
1821	0.662
1822	0.857
1823	0.636
1824	0.851
1825	0.791
1826	0.86
1827	0.791
1828	1.037
1829	0.743
1830	0.959
1831	1.092
1832	1.21
1833	1.382
1834	1.076
1835	1.006
1836	0.998
1837	1.179
1838	0.823
1839	0.895
1840	0.855
1841	0.999
1842	1.021
1843	1.036
1844	1.163
1845	1.035
1846	1.009
1847	1.102
1848	1.046
1849	1.155
1850	0.933
1851	1.186
1852	1.042
1853	1.142
1854	1.284
1855	1.063
1856	1.056
1857	0.902
1858	1.213
1859	1.205
1860	0.841
1861	0.931
1862	1.13
1863	0.963
1864	0.916
1865	0.944
1866	1.113
1867	1.125
1868	1.001
1869	1.347
1870	0.927
1871	1.059
1872	1.258
1873	1.043
1874	0.902
1875	1.114
1876	1.06
1877	1.146
1878	1.107
1879	1.096
1880	0.898
1881	1.189
1882	1.235
1883	1.16
1884	1.104
1885	1.135
1886	0.941
1887	0.763
1888	1.129
1889	1.15
1890	0.9
1891	0.878
1892	1.22
1893	1.037
1894	0.576
1895	0.714
1896	0.996
1897	1.192
1898	1.119
1899	0.902
1900	0.844
1901	0.918
1902	1.254
1903	1.342
1904	1.085
1905	1.119
1906	1.029
1907	1.33
1908	1.268
1909	1.27
1910	0.783
1911	0.713
1912	1.067
1913	1.062
1914	0.826
1915	1.308
1916	1.199
1917	1.087
1918	0.809
1919	1.05
1920	1.135
1921	1.017
1922	1.191
1923	1.147
1924	1.239
1925	0.808
1926	0.941
1927	1.096
1928	1.264
1929	0.894
1930	0.959
1931	0.663
1932	1.183
1933	0.917
1934	0.625
1935	1.155
1936	0.877
1937	0.872
1938	0.85
1939	0.727
1940	0.684
1941	0.98
1942	1.128
1943	1.064
1944	1.139
1945	1.24
1946	1.002
1947	1.065
1948	0.746
1949	0.995
1950	0.979
1951	1.057
1952	1.038
1953	0.997
1954	0.826
1955	0.927
1956	0.574
1957	0.866
1958	0.861
1959	0.931
1960	0.928
1961	0.964
1962	0.981
1963	0.733
1964	1.087
1965	1.035
1966	1.016
1967	0.797
1968	0.727
1969	1.028
1970	0.851
1971	0.823
1972	0.836
1973	1.075
1974	1.048
1975	1.025
1976	1.06
1977	0.595
1978	1.058
1979	1.107
1980	0.915
1981	0.703