# northamerica_usa_wi005 - Devil's Lake State Park - 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/2968
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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_wi005 - Devil's Lake State Park - 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: Devil's Lake State Park
#	Location:
#	Country: United States
#	Northernmost_Latitude: 43.42
#	Southernmost_Latitude: 43.42
#	Easternmost_Longitude: -89.72
#	Westernmost_Longitude: -89.72
#	Elevation: 250 m
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# Data_Collection
#	Collection_Name: northamerica_usa_wi005B
#	Earliest_Year: 1704
#	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":"4.02869665495","T2":"14.0719600727","M1":"0.0229839354836","M2":"0.573539701532"}}
#--------------------
# Species
#	Species_Name: eastern white pine
#	Species_Code: PIST
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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
1704	1.196
1705	0.821
1706	0.62
1707	0.869
1708	0.583
1709	0.638
1710	0.812
1711	0.914
1712	1.001
1713	1.482
1714	1.313
1715	1.584
1716	1.238
1717	0.715
1718	0.772
1719	0.823
1720	0.993
1721	0.597
1722	1.337
1723	0.996
1724	0.445
1725	1.563
1726	1.291
1727	1.292
1728	1.104
1729	0.663
1730	0.804
1731	0.724
1732	1.402
1733	0.985
1734	0.869
1735	0.987
1736	0.553
1737	1.282
1738	1.425
1739	1.276
1740	1.422
1741	1.185
1742	0.817
1743	1.036
1744	0.981
1745	1.174
1746	0.817
1747	1.185
1748	0.786
1749	0.675
1750	1.066
1751	1.081
1752	0.811
1753	0.781
1754	0.942
1755	0.613
1756	0.854
1757	0.732
1758	1.097
1759	1.152
1760	1.206
1761	1.406
1762	1.327
1763	1.288
1764	1.596
1765	1.631
1766	1.415
1767	1.459
1768	1.107
1769	1.166
1770	1.121
1771	1.291
1772	0.729
1773	0.951
1774	1.01
1775	1.104
1776	0.77
1777	1.304
1778	1.164
1779	0.771
1780	0.757
1781	0.986
1782	1.016
1783	1.007
1784	1.235
1785	1.162
1786	1.058
1787	1.749
1788	1.446
1789	0.971
1790	1.052
1791	0.943
1792	0.669
1793	1.083
1794	0.984
1795	0.934
1796	1.201
1797	0.984
1798	0.573
1799	0.741
1800	0.472
1801	0.75
1802	0.818
1803	0.633
1804	0.69
1805	0.774
1806	0.808
1807	0.829
1808	0.536
1809	0.917
1810	0.873
1811	0.983
1812	0.897
1813	0.944
1814	1.159
1815	1.104
1816	0.867
1817	1.025
1818	0.734
1819	1.144
1820	0.664
1821	0.697
1822	0.939
1823	1.065
1824	1.082
1825	1.067
1826	0.992
1827	0.961
1828	1.268
1829	1.044
1830	1.133
1831	0.889
1832	1.262
1833	1.275
1834	1.631
1835	1.59
1836	1.115
1837	1.229
1838	1.077
1839	1.233
1840	1.088
1841	0.746
1842	1.264
1843	0.786
1844	1.089
1845	1.013
1846	0.802
1847	0.844
1848	0.772
1849	0.855
1850	0.718
1851	1.321
1852	0.897
1853	1.244
1854	1.329
1855	1.089
1856	0.979
1857	1.19
1858	1.125
1859	1.179
1860	1.103
1861	0.865
1862	1.237
1863	1.061
1864	0.791
1865	1.137
1866	0.966
1867	1.047
1868	0.7
1869	1.093
1870	0.75
1871	0.939
1872	0.885
1873	0.656
1874	0.547
1875	0.666
1876	0.541
1877	0.958
1878	1.045
1879	0.869
1880	0.989
1881	0.831
1882	1.163
1883	1.21
1884	1.414
1885	1.431
1886	1.027
1887	0.68
1888	0.612
1889	0.914
1890	0.62
1891	0.879
1892	0.594
1893	0.574
1894	0.795
1895	0.536
1896	0.815
1897	0.515
1898	0.602
1899	0.937
1900	0.904
1901	1.007
1902	1.309
1903	1.167
1904	0.957
1905	1.212
1906	0.971
1907	0.908
1908	1.28
1909	0.912
1910	0.868
1911	0.461
1912	0.966
1913	1.195
1914	0.78
1915	0.968
1916	1.015
1917	1.121
1918	1.303
1919	0.617
1920	0.654
1921	0.617
1922	0.724
1923	0.446
1924	0.648
1925	0.776
1926	0.897
1927	1.122
1928	0.95
1929	1.308
1930	0.924
1931	0.553
1932	0.783
1933	0.629
1934	0.683
1935	1.0
1936	0.546
1937	0.624
1938	0.598
1939	0.51
1940	0.68
1941	0.714
1942	0.7
1943	0.657
1944	0.682
1945	1.394
1946	1.086
1947	1.151
1948	1.053
1949	1.079
1950	1.405
1951	1.009
1952	0.906
1953	1.037
1954	1.117
1955	1.136
1956	0.75
1957	0.884
1958	1.137
1959	0.999
1960	1.283
1961	0.927
1962	1.311
1963	1.133
1964	1.189
1965	1.235
1966	1.176
1967	1.434
1968	1.602
1969	1.248
1970	0.742
1971	0.816
1972	0.854
1973	1.219
1974	1.659
1975	1.501
1976	1.163
1977	1.297
1978	1.105
1979	1.074
1980	1.168
1981	1.347
1982	1.116