# northamerica_usa_mi005 - Cranbrook Institute - 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.
#
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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/2965
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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_mi005 - Cranbrook Institute - 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: Cranbrook Institute
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.67
#	Southernmost_Latitude: 42.67
#	Easternmost_Longitude: -83.42
#	Westernmost_Longitude: -83.42
#	Elevation: 200 m
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# Data_Collection
#	Collection_Name: northamerica_usa_mi005B
#	Earliest_Year: 1693
#	Most_Recent_Year: 1983
#	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":"5.3545886323","T2":"17.117312446","M1":"0.0224352380988","M2":"0.484646819435"}}
#--------------------
# Species
#	Species_Name: white oak
#	Species_Code: QUAL
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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
#
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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
1693	1.104
1694	1.607
1695	1.179
1696	1.291
1697	1.081
1698	0.897
1699	0.8
1700	0.847
1701	1.363
1702	1.112
1703	1.063
1704	1.115
1705	1.049
1706	1.177
1707	1.592
1708	1.255
1709	1.282
1710	1.206
1711	1.11
1712	0.924
1713	0.843
1714	0.892
1715	1.146
1716	0.888
1717	0.937
1718	0.823
1719	0.8
1720	0.674
1721	0.578
1722	0.497
1723	0.578
1724	0.552
1725	0.882
1726	0.544
1727	0.658
1728	0.538
1729	0.664
1730	0.687
1731	0.831
1732	0.899
1733	0.776
1734	0.945
1735	0.731
1736	0.795
1737	0.973
1738	1.093
1739	0.949
1740	0.909
1741	0.892
1742	0.704
1743	0.709
1744	0.768
1745	1.077
1746	0.869
1747	0.878
1748	0.772
1749	0.68
1750	1.108
1751	0.861
1752	0.919
1753	0.76
1754	0.888
1755	0.829
1756	1.158
1757	0.709
1758	1.011
1759	0.883
1760	1.035
1761	1.068
1762	0.745
1763	0.939
1764	1.001
1765	0.959
1766	1.079
1767	0.84
1768	1.003
1769	0.88
1770	0.625
1771	0.816
1772	0.9
1773	1.043
1774	0.896
1775	1.121
1776	1.1
1777	1.167
1778	0.952
1779	0.981
1780	0.942
1781	1.343
1782	0.994
1783	1.026
1784	0.78
1785	0.545
1786	0.744
1787	0.901
1788	0.932
1789	1.076
1790	0.992
1791	1.031
1792	0.805
1793	1.106
1794	1.196
1795	0.963
1796	0.961
1797	1.165
1798	1.033
1799	0.825
1800	0.788
1801	1.175
1802	1.248
1803	0.841
1804	1.245
1805	1.212
1806	0.985
1807	1.159
1808	1.102
1809	0.978
1810	0.946
1811	1.145
1812	1.261
1813	1.187
1814	1.147
1815	1.145
1816	0.91
1817	0.797
1818	0.661
1819	0.878
1820	0.613
1821	0.705
1822	0.939
1823	0.988
1824	1.191
1825	0.912
1826	1.168
1827	1.321
1828	1.279
1829	1.019
1830	1.221
1831	1.073
1832	0.988
1833	1.037
1834	1.065
1835	0.973
1836	1.02
1837	0.889
1838	0.715
1839	0.582
1840	1.12
1841	0.97
1842	0.849
1843	0.87
1844	0.891
1845	0.786
1846	0.83
1847	1.131
1848	1.198
1849	1.03
1850	1.156
1851	1.199
1852	1.137
1853	1.071
1854	1.038
1855	1.218
1856	1.071
1857	1.101
1858	1.03
1859	1.475
1860	1.295
1861	1.174
1862	1.253
1863	1.479
1864	1.292
1865	1.087
1866	1.345
1867	1.195
1868	1.172
1869	1.306
1870	1.063
1871	1.181
1872	1.042
1873	1.314
1874	1.316
1875	1.056
1876	1.057
1877	1.034
1878	1.203
1879	1.378
1880	1.424
1881	1.271
1882	1.309
1883	1.416
1884	1.064
1885	1.2
1886	0.998
1887	0.93
1888	0.981
1889	1.057
1890	1.022
1891	1.044
1892	0.939
1893	1.014
1894	0.772
1895	0.596
1896	1.007
1897	1.093
1898	1.024
1899	0.999
1900	1.189
1901	1.074
1902	1.526
1903	1.716
1904	1.347
1905	1.071
1906	1.157
1907	0.988
1908	1.067
1909	0.922
1910	0.814
1911	0.883
1912	1.144
1913	1.08
1914	0.993
1915	1.023
1916	0.965
1917	1.086
1918	0.922
1919	1.044
1920	1.138
1921	0.887
1922	0.965
1923	0.952
1924	1.034
1925	0.88
1926	0.799
1927	1.0
1928	0.904
1929	0.903
1930	0.859
1931	0.776
1932	0.989
1933	0.976
1934	0.728
1935	0.953
1936	0.82
1937	1.084
1938	0.891
1939	1.064
1940	0.947
1941	0.864
1942	0.912
1943	0.979
1944	0.877
1945	0.735
1946	0.876
1947	0.916
1948	0.86
1949	0.937
1950	1.033
1951	0.994
1952	0.779
1953	0.852
1954	0.853
1955	0.878
1956	0.932
1957	0.963
1958	0.834
1959	0.877
1960	0.801
1961	0.858
1962	0.84
1963	1.026
1964	0.919
1965	0.84
1966	0.771
1967	0.745
1968	0.783
1969	0.846
1970	0.71
1971	0.763
1972	0.689
1973	0.838
1974	0.77
1975	0.963
1976	0.744
1977	0.688
1978	0.932
1979	0.862
1980	0.947
1981	0.654
1982	0.898
1983	0.894