# northamerica_usa_il001 - Sandwich - 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/3179
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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_il001 - Sandwich - 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: Sandwich
#	Location:
#	Country: United States
#	Northernmost_Latitude: 41.65
#	Southernmost_Latitude: 41.65
#	Easternmost_Longitude: -88.58
#	Westernmost_Longitude: -88.58
#	Elevation: 200 m
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# Data_Collection
#	Collection_Name: northamerica_usa_il001B
#	Earliest_Year: 1853
#	Most_Recent_Year: 1980
#	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":"5.21828596488","T2":"17.0404078241","M1":"0.0227212586625","M2":"0.531532567363"}}
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# Species
#	Species_Name: white oak
#	Species_Code: QUAL
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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
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age	trsgi
1853	1.072
1854	1.045
1855	1.139
1856	0.953
1857	0.979
1858	1.221
1859	1.29
1860	1.016
1861	1.144
1862	1.401
1863	1.115
1864	1.181
1865	1.175
1866	1.103
1867	1.31
1868	0.977
1869	1.639
1870	1.066
1871	1.025
1872	0.838
1873	0.94
1874	0.907
1875	0.843
1876	1.181
1877	1.091
1878	1.033
1879	1.15
1880	1.206
1881	0.997
1882	1.238
1883	1.099
1884	1.25
1885	1.216
1886	0.883
1887	0.66
1888	0.822
1889	1.059
1890	1.08
1891	1.077
1892	1.379
1893	0.947
1894	0.772
1895	0.567
1896	1.14
1897	1.229
1898	1.086
1899	0.882
1900	0.597
1901	0.546
1902	1.067
1903	1.214
1904	0.97
1905	0.835
1906	0.644
1907	1.104
1908	1.132
1909	1.084
1910	0.754
1911	0.636
1912	1.172
1913	0.864
1914	0.797
1915	1.138
1916	1.128
1917	0.888
1918	0.686
1919	0.777
1920	0.873
1921	0.825
1922	0.95
1923	0.861
1924	1.192
1925	0.723
1926	0.741
1927	0.712
1928	0.936
1929	0.874
1930	0.796
1931	0.979
1932	1.08
1933	1.115
1934	0.583
1935	1.128
1936	0.784
1937	0.932
1938	1.011
1939	0.921
1940	0.777
1941	0.835
1942	0.841
1943	0.938
1944	0.856
1945	1.138
1946	0.839
1947	1.146
1948	1.008
1949	1.063
1950	1.175
1951	1.295
1952	1.158
1953	1.028
1954	1.107
1955	1.199
1956	0.963
1957	1.154
1958	1.357
1959	1.126
1960	1.438
1961	1.096
1962	0.992
1963	0.913
1964	0.937
1965	1.0
1966	0.884
1967	0.851
1968	0.858
1969	1.271
1970	1.076
1971	0.893
1972	1.032
1973	1.139
1974	1.089
1975	0.97
1976	0.873
1977	0.69
1978	1.123
1979	1.029
1980	1.086