# northamerica_usa_id001 - Lake Coeur d'Alene - 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/2899
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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
#--------------------
# Title
#	Study_Name: northamerica_usa_id001 - Lake Coeur d'Alene - 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: Lake Coeur d'Alene
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.63
#	Southernmost_Latitude: 47.63
#	Easternmost_Longitude: -116.47
#	Westernmost_Longitude: -116.47
#	Elevation: 960 m
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# Data_Collection
#	Collection_Name: northamerica_usa_id001B
#	Earliest_Year: 1750
#	Most_Recent_Year: 1976
#	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":"3.5348682265","T2":"13.2544643451","M1":"0.0228983127337","M2":"0.59108230989"}}
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# 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
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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
1750	1.302
1751	1.157
1752	1.328
1753	0.885
1754	0.89
1755	1.029
1756	0.824
1757	0.808
1758	0.857
1759	0.878
1760	0.98
1761	1.247
1762	1.246
1763	1.168
1764	1.086
1765	1.297
1766	1.185
1767	0.891
1768	0.95
1769	0.896
1770	1.053
1771	1.065
1772	1.036
1773	1.007
1774	0.991
1775	0.901
1776	0.86
1777	0.92
1778	0.985
1779	1.044
1780	1.184
1781	0.956
1782	0.967
1783	0.926
1784	0.89
1785	0.84
1786	0.843
1787	0.7
1788	0.829
1789	0.896
1790	0.831
1791	1.088
1792	1.003
1793	1.272
1794	1.072
1795	1.082
1796	0.938
1797	0.834
1798	0.897
1799	0.946
1800	1.007
1801	0.967
1802	0.962
1803	1.008
1804	1.014
1805	0.859
1806	0.846
1807	0.72
1808	0.718
1809	0.752
1810	0.728
1811	0.76
1812	1.123
1813	1.136
1814	1.624
1815	1.298
1816	1.116
1817	0.842
1818	1.049
1819	1.085
1820	1.046
1821	1.132
1822	1.132
1823	0.893
1824	1.17
1825	1.227
1826	1.061
1827	1.061
1828	1.034
1829	0.934
1830	1.0
1831	0.888
1832	1.146
1833	1.077
1834	0.821
1835	0.864
1836	0.903
1837	0.785
1838	0.961
1839	0.78
1840	0.649
1841	0.761
1842	0.795
1843	0.685
1844	0.825
1845	0.962
1846	0.931
1847	0.693
1848	0.827
1849	0.615
1850	0.674
1851	0.699
1852	0.696
1853	0.741
1854	0.757
1855	0.941
1856	0.856
1857	1.22
1858	1.156
1859	0.941
1860	1.147
1861	1.2
1862	0.8
1863	0.846
1864	0.957
1865	0.842
1866	1.174
1867	1.013
1868	0.91
1869	0.702
1870	0.9
1871	0.866
1872	0.919
1873	1.057
1874	0.868
1875	0.886
1876	1.265
1877	1.669
1878	1.723
1879	1.53
1880	1.317
1881	1.367
1882	1.096
1883	0.839
1884	1.104
1885	1.182
1886	1.088
1887	0.984
1888	1.123
1889	0.87
1890	0.642
1891	0.955
1892	1.083
1893	0.905
1894	1.167
1895	1.212
1896	0.803
1897	0.265
1898	0.488
1899	0.676
1900	1.087
1901	0.902
1902	1.192
1903	1.27
1904	1.234
1905	1.116
1906	1.162
1907	1.197
1908	1.354
1909	1.243
1910	1.03
1911	0.954
1912	0.924
1913	1.191
1914	1.184
1915	1.032
1916	1.148
1917	0.825
1918	0.829
1919	1.0
1920	1.009
1921	1.311
1922	0.847
1923	0.771
1924	0.852
1925	0.68
1926	0.723
1927	0.951
1928	1.103
1929	0.764
1930	0.667
1931	0.676
1932	0.728
1933	0.763
1934	1.087
1935	0.772
1936	0.424
1937	0.577
1938	0.83
1939	0.766
1940	0.877
1941	0.999
1942	1.35
1943	1.082
1944	0.982
1945	1.178
1946	1.331
1947	1.227
1948	1.178
1949	1.018
1950	0.97
1951	1.168
1952	1.051
1953	0.994
1954	1.167
1955	1.133
1956	1.007
1957	1.074
1958	0.842
1959	0.726
1960	1.188
1961	1.047
1962	1.009
1963	1.132
1964	0.775
1965	0.933
1966	1.081
1967	0.896
1968	1.067
1969	1.135
1970	0.744
1971	1.039
1972	1.328
1973	0.954
1974	0.683
1975	0.94
1976	1.261