# northamerica_usa_mn014 - Coddington Lake - 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/4969
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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_mn014 - Coddington Lake - 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: Coddington Lake
#	Location:
#	Country: United States
#	Northernmost_Latitude: 47.77
#	Southernmost_Latitude: 47.77
#	Easternmost_Longitude: -94.08
#	Westernmost_Longitude: -94.08
#	Elevation: 402 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mn014B
#	Earliest_Year: 1789
#	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":"4.21838535858","T2":"14.6366890603","M1":"0.0224840437532","M2":"0.551811421581"}}
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# Species
#	Species_Name: red pine
#	Species_Code: PIRE
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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)
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##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
1789	1.062
1790	1.098
1791	1.037
1792	0.981
1793	1.138
1794	0.995
1795	0.896
1796	0.829
1797	0.933
1798	0.924
1799	0.773
1800	0.424
1801	0.479
1802	0.729
1803	0.81
1804	0.878
1805	0.971
1806	0.981
1807	1.292
1808	1.215
1809	1.088
1810	1.108
1811	1.103
1812	0.93
1813	1.143
1814	1.14
1815	1.006
1816	1.004
1817	0.98
1818	1.063
1819	1.024
1820	1.089
1821	0.855
1822	1.022
1823	1.013
1824	0.928
1825	0.957
1826	0.698
1827	0.849
1828	1.068
1829	0.999
1830	0.867
1831	0.783
1832	0.809
1833	1.014
1834	1.073
1835	0.805
1836	0.79
1837	0.79
1838	0.767
1839	0.825
1840	0.756
1841	0.793
1842	1.064
1843	0.911
1844	0.892
1845	0.947
1846	0.93
1847	0.868
1848	1.038
1849	0.938
1850	0.876
1851	0.87
1852	0.845
1853	0.835
1854	0.842
1855	0.841
1856	0.983
1857	0.94
1858	0.846
1859	0.825
1860	1.081
1861	1.165
1862	0.958
1863	0.866
1864	0.803
1865	1.088
1866	1.243
1867	1.354
1868	1.284
1869	1.157
1870	1.492
1871	1.188
1872	1.458
1873	1.654
1874	1.238
1875	0.787
1876	0.837
1877	0.935
1878	0.894
1879	0.749
1880	0.883
1881	0.9
1882	0.755
1883	0.785
1884	0.803
1885	1.125
1886	1.005
1887	1.367
1888	1.206
1889	1.64
1890	1.304
1891	1.442
1892	1.383
1893	1.249
1894	1.543
1895	1.575
1896	1.451
1897	1.543
1898	1.408
1899	1.238
1900	1.308
1901	0.79
1902	1.12
1903	1.105
1904	0.993
1905	1.202
1906	1.199
1907	0.963
1908	0.953
1909	0.903
1910	0.597
1911	0.696
1912	0.865
1913	0.909
1914	1.051
1915	1.166
1916	1.377
1917	1.109
1918	1.186
1919	1.156
1920	0.991
1921	0.918
1922	0.913
1923	0.84
1924	0.765
1925	0.885
1926	1.009
1927	0.843
1928	0.965
1929	1.095
1930	1.003
1931	0.79
1932	0.933
1933	0.686
1934	0.802
1935	0.993
1936	0.662
1937	0.604
1938	0.623
1939	0.599
1940	0.63
1941	0.639
1942	0.736
1943	0.625
1944	0.752
1945	1.012
1946	0.974
1947	0.882
1948	0.803
1949	0.804
1950	0.914
1951	0.996
1952	1.128
1953	1.009
1954	0.977
1955	1.071
1956	0.967
1957	0.819
1958	0.962
1959	1.108
1960	0.934
1961	0.846
1962	0.917
1963	0.95
1964	0.759
1965	1.062
1966	1.059
1967	1.109
1968	1.024
1969	1.109
1970	0.967
1971	1.01
1972	0.994
1973	0.935
1974	0.884
1975	1.028
1976	1.256
1977	0.917
1978	0.991
1979	0.94
1980	0.921
1981	0.963
1982	0.835