# northamerica_usa_or035 - Lookout Mountain - 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.
#
#
# 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/5235
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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_or035 - Lookout Mountain - 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: Lookout Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 45.83
#	Southernmost_Latitude: 45.83
#	Easternmost_Longitude: -117.8
#	Westernmost_Longitude: -117.8
#	Elevation: 1372 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_or035B
#	Earliest_Year: 1688
#	Most_Recent_Year: 1990
#	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":"4.95868631267","T2":"16.2971358472","M1":"0.0223165440902","M2":"0.487558649078"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1688	1.043
1689	0.96
1690	1.161
1691	1.155
1692	1.255
1693	1.103
1694	1.158
1695	0.823
1696	0.781
1697	0.939
1698	0.835
1699	0.897
1700	0.935
1701	0.827
1702	1.013
1703	1.145
1704	1.119
1705	0.957
1706	0.898
1707	0.924
1708	0.745
1709	0.73
1710	0.869
1711	0.908
1712	1.044
1713	0.966
1714	1.034
1715	1.047
1716	1.152
1717	0.78
1718	0.725
1719	0.753
1720	0.781
1721	0.767
1722	0.785
1723	1.075
1724	0.885
1725	0.878
1726	0.962
1727	1.286
1728	0.817
1729	0.874
1730	0.869
1731	0.934
1732	1.02
1733	1.221
1734	0.801
1735	0.889
1736	0.952
1737	0.831
1738	0.977
1739	0.774
1740	0.656
1741	0.719
1742	0.828
1743	0.952
1744	1.013
1745	1.173
1746	1.247
1747	1.232
1748	1.245
1749	1.113
1750	1.74
1751	1.42
1752	1.349
1753	0.997
1754	0.697
1755	0.978
1756	0.706
1757	0.69
1758	0.763
1759	0.817
1760	0.889
1761	1.39
1762	1.135
1763	1.312
1764	1.064
1765	1.056
1766	1.272
1767	1.172
1768	0.909
1769	0.915
1770	1.19
1771	1.251
1772	1.108
1773	1.301
1774	1.107
1775	1.077
1776	1.001
1777	1.045
1778	1.134
1779	1.072
1780	1.067
1781	0.904
1782	0.952
1783	1.016
1784	0.845
1785	1.008
1786	1.037
1787	0.659
1788	0.801
1789	0.852
1790	0.837
1791	1.194
1792	1.008
1793	1.157
1794	1.195
1795	1.184
1796	1.267
1797	0.693
1798	0.828
1799	0.944
1800	1.198
1801	1.1
1802	1.224
1803	1.13
1804	1.1
1805	1.22
1806	1.136
1807	0.907
1808	1.014
1809	0.983
1810	0.761
1811	0.866
1812	1.158
1813	0.98
1814	1.416
1815	1.264
1816	1.161
1817	0.901
1818	1.109
1819	1.245
1820	1.014
1821	0.932
1822	1.051
1823	0.677
1824	0.937
1825	1.203
1826	1.122
1827	1.024
1828	1.074
1829	1.123
1830	0.97
1831	0.853
1832	0.951
1833	1.116
1834	0.92
1835	1.012
1836	0.736
1837	0.869
1838	0.993
1839	0.732
1840	0.567
1841	0.858
1842	0.854
1843	0.918
1844	1.009
1845	1.193
1846	1.086
1847	0.868
1848	0.92
1849	0.742
1850	0.867
1851	0.867
1852	0.922
1853	0.96
1854	1.014
1855	1.676
1856	1.369
1857	1.479
1858	1.455
1859	1.115
1860	0.757
1861	1.139
1862	1.112
1863	1.367
1864	1.322
1865	1.102
1866	1.255
1867	1.001
1868	0.891
1869	0.949
1870	0.801
1871	0.913
1872	0.961
1873	1.016
1874	1.078
1875	0.883
1876	0.937
1877	1.375
1878	1.273
1879	0.988
1880	0.778
1881	0.99
1882	0.909
1883	0.617
1884	0.668
1885	0.986
1886	0.649
1887	0.63
1888	0.954
1889	0.7
1890	0.544
1891	0.875
1892	0.844
1893	0.678
1894	0.805
1895	0.83
1896	0.713
1897	0.878
1898	0.859
1899	0.603
1900	1.124
1901	1.248
1902	1.06
1903	1.072
1904	1.349
1905	1.039
1906	1.053
1907	1.522
1908	1.549
1909	1.304
1910	1.103
1911	0.912
1912	0.937
1913	1.317
1914	1.211
1915	1.161
1916	1.054
1917	0.982
1918	0.996
1919	1.147
1920	0.999
1921	1.218
1922	1.214
1923	1.022
1924	1.012
1925	0.949
1926	0.993
1927	1.158
1928	1.255
1929	1.172
1930	1.14
1931	1.097
1932	0.886
1933	0.889
1934	1.131
1935	0.911
1936	0.69
1937	0.859
1938	1.081
1939	0.983
1940	0.993
1941	1.47
1942	1.743
1943	1.222
1944	1.046
1945	0.942
1946	1.12
1947	1.146
1948	0.84
1949	0.834
1950	0.872
1951	0.838
1952	0.963
1953	0.861
1954	0.966
1955	1.17
1956	0.913
1957	0.941
1958	0.918
1959	0.973
1960	1.192
1961	1.195
1962	0.838
1963	0.875
1964	0.61
1965	0.581
1966	0.701
1967	0.69
1968	0.547
1969	0.707
1970	0.798
1971	0.671
1972	0.524
1973	0.638
1974	0.428
1975	0.628
1976	0.815
1977	0.832
1978	0.641
1979	0.716
1980	0.813
1981	0.985
1982	0.938
1983	1.029
1984	0.811
1985	0.713
1986	0.835
1987	0.844
1988	0.717
1989	0.678
1990	1.296