# northamerica_usa_mn021 - Seagull Lake - 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/3280
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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_mn021 - Seagull Lake - 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
#------------------
# Site_Information
#	Site_Name: Seagull Lake
#	Location:
#	Country: United States
#	Northernmost_Latitude: 48.12
#	Southernmost_Latitude: 48.12
#	Easternmost_Longitude: -90.92
#	Westernmost_Longitude: -90.92
#	Elevation: 1460 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mn021B
#	Earliest_Year: 1681
#	Most_Recent_Year: 1971
#	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":"2.96728017612","T2":"13.6959498647","M1":"0.0232583272725","M2":"0.579608798801"}}
#--------------------
# Species
#	Species_Name: red pine
#	Species_Code: PIRE
#--------------------
# Chronology:
#
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#
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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
1681	1.027
1682	0.68
1683	0.718
1684	0.713
1685	0.841
1686	1.064
1687	1.263
1688	1.076
1689	1.066
1690	1.029
1691	0.836
1692	0.7
1693	0.859
1694	1.23
1695	1.425
1696	1.225
1697	1.041
1698	1.195
1699	1.147
1700	1.28
1701	1.136
1702	1.194
1703	1.491
1704	1.409
1705	1.503
1706	1.452
1707	1.323
1708	1.304
1709	1.305
1710	1.303
1711	1.416
1712	1.302
1713	1.174
1714	1.129
1715	1.292
1716	1.377
1717	0.924
1718	0.845
1719	1.025
1720	1.079
1721	0.929
1722	1.088
1723	1.188
1724	0.901
1725	0.966
1726	1.09
1727	1.182
1728	1.006
1729	1.234
1730	1.124
1731	1.069
1732	1.105
1733	1.11
1734	1.074
1735	1.012
1736	0.686
1737	0.871
1738	0.952
1739	0.452
1740	0.843
1741	0.562
1742	0.459
1743	0.546
1744	0.571
1745	0.716
1746	1.0
1747	1.0
1748	1.144
1749	0.987
1750	0.871
1751	0.82
1752	0.946
1753	0.868
1754	0.753
1755	0.704
1756	0.986
1757	0.797
1758	0.843
1759	0.805
1760	0.607
1761	0.547
1762	0.991
1763	0.709
1764	0.817
1765	0.871
1766	0.889
1767	1.197
1768	0.804
1769	0.88
1770	0.812
1771	0.687
1772	0.97
1773	0.765
1774	0.723
1775	0.808
1776	0.539
1777	0.738
1778	1.103
1779	1.038
1780	0.618
1781	0.825
1782	0.767
1783	0.897
1784	1.035
1785	0.863
1786	0.636
1787	0.928
1788	0.761
1789	0.914
1790	0.774
1791	0.596
1792	0.682
1793	0.9
1794	0.719
1795	0.636
1796	0.877
1797	0.893
1798	0.779
1799	0.93
1800	0.821
1801	1.269
1802	1.477
1803	1.251
1804	0.601
1805	1.168
1806	1.141
1807	1.049
1808	0.93
1809	0.995
1810	1.064
1811	0.939
1812	0.639
1813	0.874
1814	1.213
1815	1.012
1816	0.754
1817	0.746
1818	0.577
1819	0.962
1820	0.839
1821	0.451
1822	1.052
1823	0.981
1824	1.027
1825	1.012
1826	0.927
1827	1.063
1828	1.286
1829	0.821
1830	0.996
1831	0.977
1832	1.009
1833	0.992
1834	1.514
1835	1.409
1836	1.353
1837	1.184
1838	1.363
1839	1.057
1840	0.935
1841	1.219
1842	1.417
1843	1.109
1844	1.3
1845	1.289
1846	0.939
1847	1.265
1848	1.573
1849	1.395
1850	1.544
1851	1.456
1852	1.157
1853	0.932
1854	1.406
1855	0.956
1856	1.291
1857	1.271
1858	1.413
1859	1.344
1860	1.194
1861	1.26
1862	0.628
1863	0.893
1864	0.639
1865	0.951
1866	0.622
1867	0.966
1868	0.817
1869	0.867
1870	1.089
1871	0.662
1872	1.068
1873	1.352
1874	0.97
1875	0.545
1876	0.982
1877	1.16
1878	1.035
1879	0.835
1880	0.793
1881	0.846
1882	0.8
1883	0.629
1884	0.738
1885	0.788
1886	0.518
1887	0.977
1888	1.029
1889	0.962
1890	0.933
1891	1.019
1892	0.903
1893	0.544
1894	0.664
1895	1.115
1896	0.897
1897	0.838
1898	1.19
1899	1.292
1900	1.058
1901	1.289
1902	1.366
1903	1.004
1904	1.062
1905	1.527
1906	1.22
1907	0.944
1908	1.187
1909	0.785
1910	0.331
1911	0.599
1912	0.685
1913	0.764
1914	0.722
1915	1.06
1916	1.115
1917	1.353
1918	1.26
1919	0.82
1920	1.258
1921	0.833
1922	1.04
1923	0.703
1924	0.701
1925	1.012
1926	1.243
1927	1.032
1928	1.337
1929	0.905
1930	1.013
1931	0.96
1932	0.968
1933	0.955
1934	0.635
1935	0.907
1936	0.658
1937	0.658
1938	0.898
1939	0.628
1940	0.687
1941	0.707
1942	0.983
1943	0.721
1944	1.086
1945	1.152
1946	0.964
1947	1.178
1948	0.784
1949	1.024
1950	0.997
1951	1.045
1952	1.224
1953	1.307
1954	0.991
1955	1.191
1956	1.151
1957	0.97
1958	0.904
1959	0.854
1960	0.878
1961	0.695
1962	1.159
1963	1.212
1964	0.956
1965	1.407
1966	1.177
1967	1.34
1968	1.334
1969	1.358
1970	1.134
1971	1.168