# northamerica_usa_mn023 - Coddington Lake Recollection - 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/3306
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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
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# Title
#	Study_Name: northamerica_usa_mn023 - Coddington Lake Recollection - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# 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 Recollection
#	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_mn023B
#	Earliest_Year: 1792
#	Most_Recent_Year: 1988
#	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":"3.55744497319","T2":"15.8419252735","M1":"0.0222779814821","M2":"0.538669770621"}}
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# Species
#	Species_Name: red oak
#	Species_Code: QURU
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# Chronology:
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# Variables
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# 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
1792	0.958
1793	0.874
1794	0.956
1795	1.16
1796	1.142
1797	1.358
1798	1.429
1799	1.359
1800	1.488
1801	1.57
1802	1.531
1803	1.435
1804	1.347
1805	1.233
1806	1.521
1807	1.552
1808	1.285
1809	1.235
1810	1.124
1811	1.129
1812	1.282
1813	1.249
1814	1.018
1815	1.176
1816	1.092
1817	1.289
1818	0.961
1819	0.965
1820	0.822
1821	0.802
1822	0.982
1823	1.017
1824	1.139
1825	0.919
1826	0.853
1827	0.948
1828	1.148
1829	1.095
1830	1.201
1831	0.951
1832	0.93
1833	0.87
1834	1.022
1835	0.737
1836	0.688
1837	0.773
1838	0.555
1839	0.458
1840	0.622
1841	0.759
1842	0.543
1843	0.732
1844	0.549
1845	0.666
1846	0.61
1847	0.528
1848	0.332
1849	0.479
1850	0.794
1851	1.012
1852	1.148
1853	0.965
1854	0.842
1855	0.864
1856	0.605
1857	0.982
1858	1.001
1859	1.184
1860	1.346
1861	1.406
1862	1.095
1863	0.876
1864	1.129
1865	1.266
1866	1.437
1867	1.375
1868	1.251
1869	1.167
1870	1.454
1871	1.382
1872	1.419
1873	1.426
1874	1.212
1875	1.342
1876	1.379
1877	1.418
1878	1.263
1879	1.354
1880	1.504
1881	1.51
1882	1.288
1883	1.163
1884	1.003
1885	1.089
1886	1.0
1887	1.095
1888	1.063
1889	0.671
1890	0.748
1891	0.732
1892	0.922
1893	0.761
1894	0.898
1895	0.702
1896	0.875
1897	0.595
1898	0.816
1899	0.768
1900	0.551
1901	0.812
1902	0.544
1903	0.551
1904	0.632
1905	0.633
1906	0.485
1907	0.599
1908	0.441
1909	0.48
1910	0.405
1911	0.484
1912	0.643
1913	0.643
1914	0.676
1915	0.666
1916	0.663
1917	0.53
1918	0.652
1919	0.558
1920	0.601
1921	0.558
1922	0.68
1923	0.69
1924	0.632
1925	0.739
1926	0.695
1927	0.699
1928	0.766
1929	0.829
1930	0.846
1931	0.69
1932	0.898
1933	0.851
1934	0.871
1935	1.02
1936	0.688
1937	0.513
1938	0.492
1939	0.784
1940	1.103
1941	1.001
1942	1.401
1943	1.271
1944	1.52
1945	1.474
1946	1.016
1947	1.546
1948	1.174
1949	1.706
1950	1.739
1951	1.368
1952	1.405
1953	0.978
1954	1.259
1955	1.528
1956	1.314
1957	1.826
1958	1.534
1959	1.612
1960	1.531
1961	1.155
1962	0.978
1963	1.21
1964	1.123
1965	1.3
1966	1.081
1967	1.095
1968	1.192
1969	1.146
1970	1.065
1971	1.014
1972	1.152
1973	1.306
1974	1.048
1975	0.982
1976	1.037
1977	1.033
1978	1.079
1979	1.015
1980	0.896
1981	1.039
1982	1.024
1983	0.873
1984	0.661
1985	0.783
1986	0.786
1987	0.759
1988	0.732