# northamerica_usa_or059 - Calimus Butte - 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/4774
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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_or059 - Calimus Butte - 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: Calimus Butte
#	Location:
#	Country: United States
#	Northernmost_Latitude: 42.63
#	Southernmost_Latitude: 42.63
#	Easternmost_Longitude: -121.53
#	Westernmost_Longitude: -121.53
#	Elevation: 2020 m
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# Data_Collection
#	Collection_Name: northamerica_usa_or059B
#	Earliest_Year: 1733
#	Most_Recent_Year: 1995
#	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":"5.35353328353","T2":"17.1331388532","M1":"0.0224011417366","M2":"0.427087641345"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1733	1.123
1734	1.101
1735	1.443
1736	1.176
1737	1.057
1738	1.277
1739	0.993
1740	0.979
1741	1.043
1742	0.795
1743	0.439
1744	0.243
1745	0.49
1746	0.722
1747	0.824
1748	0.937
1749	0.891
1750	1.07
1751	1.072
1752	0.943
1753	0.665
1754	0.709
1755	0.698
1756	0.628
1757	0.665
1758	0.751
1759	0.805
1760	0.921
1761	0.978
1762	0.999
1763	0.861
1764	0.929
1765	1.026
1766	1.015
1767	0.991
1768	1.048
1769	0.946
1770	1.01
1771	1.027
1772	1.089
1773	1.119
1774	0.94
1775	0.943
1776	1.167
1777	1.103
1778	0.894
1779	0.763
1780	0.898
1781	0.995
1782	0.964
1783	1.047
1784	1.266
1785	1.121
1786	1.309
1787	1.139
1788	1.111
1789	1.368
1790	1.179
1791	1.767
1792	1.388
1793	1.477
1794	1.554
1795	1.362
1796	1.211
1797	1.217
1798	1.5
1799	1.357
1800	1.246
1801	0.579
1802	0.079
1803	0.239
1804	0.641
1805	0.757
1806	0.722
1807	0.778
1808	0.904
1809	0.993
1810	0.725
1811	0.839
1812	1.313
1813	1.149
1814	1.44
1815	1.259
1816	0.98
1817	0.917
1818	1.08
1819	1.005
1820	0.946
1821	0.937
1822	1.143
1823	0.987
1824	1.055
1825	0.826
1826	0.878
1827	0.817
1828	0.899
1829	0.941
1830	0.788
1831	0.85
1832	1.039
1833	0.982
1834	1.207
1835	0.819
1836	0.933
1837	1.217
1838	1.145
1839	1.165
1840	1.017
1841	1.287
1842	0.933
1843	1.047
1844	0.567
1845	0.343
1846	0.591
1847	0.546
1848	0.672
1849	0.597
1850	0.543
1851	0.619
1852	0.77
1853	0.637
1854	0.898
1855	1.034
1856	0.713
1857	0.847
1858	0.785
1859	0.762
1860	1.058
1861	1.077
1862	0.769
1863	0.966
1864	0.795
1865	0.799
1866	1.083
1867	0.996
1868	0.916
1869	1.006
1870	1.02
1871	0.9
1872	0.934
1873	1.012
1874	0.988
1875	1.284
1876	0.861
1877	1.202
1878	1.197
1879	1.042
1880	0.856
1881	1.076
1882	0.899
1883	0.792
1884	0.815
1885	0.953
1886	0.861
1887	0.948
1888	1.126
1889	1.14
1890	0.784
1891	0.888
1892	0.867
1893	0.872
1894	1.078
1895	0.915
1896	0.771
1897	0.851
1898	0.921
1899	0.657
1900	0.889
1901	1.101
1902	0.948
1903	0.927
1904	1.031
1905	0.984
1906	0.996
1907	1.056
1908	1.145
1909	1.053
1910	0.95
1911	0.863
1912	0.956
1913	1.147
1914	0.971
1915	1.034
1916	0.84
1917	0.818
1918	0.823
1919	0.896
1920	0.785
1921	0.863
1922	0.632
1923	0.55
1924	0.452
1925	0.436
1926	0.691
1927	0.454
1928	0.671
1929	0.63
1930	0.686
1931	0.598
1932	0.604
1933	0.648
1934	0.858
1935	0.655
1936	0.837
1937	0.959
1938	1.027
1939	0.998
1940	0.981
1941	0.938
1942	1.067
1943	0.877
1944	1.049
1945	0.853
1946	1.127
1947	1.189
1948	1.071
1949	1.015
1950	1.167
1951	1.232
1952	0.927
1953	0.945
1954	1.193
1955	1.59
1956	1.268
1957	1.254
1958	1.227
1959	1.424
1960	1.399
1961	1.128
1962	1.23
1963	1.141
1964	1.317
1965	1.324
1966	1.612
1967	1.077
1968	1.049
1969	1.405
1970	1.105
1971	0.842
1972	0.964
1973	0.981
1974	0.889
1975	0.958
1976	1.147
1977	1.17
1978	1.028
1979	1.215
1980	1.403
1981	1.291
1982	1.134
1983	1.324
1984	1.23
1985	1.151
1986	1.104
1987	0.939
1988	1.089
1989	1.005
1990	1.304
1991	0.867
1992	0.757
1993	0.841
1994	0.962
1995	0.756