# northamerica_usa_ca520 - Likely Mountain - 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/3540
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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_ca520 - Likely Mountain - 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: Likely Mountain
#	Location:
#	Country: United States
#	Northernmost_Latitude: 41.15
#	Southernmost_Latitude: 41.15
#	Easternmost_Longitude: -120.57
#	Westernmost_Longitude: -120.57
#	Elevation: 1811 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ca520B
#	Earliest_Year: 1705
#	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":"3.62908957968","T2":"15.210123533","M1":"0.0236163730188","M2":"0.535585897629"}}
#--------------------
# Species
#	Species_Name: Jeffrey pine
#	Species_Code: PIJE
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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
1705	1.323
1706	0.791
1707	1.013
1708	0.899
1709	0.869
1710	0.842
1711	0.88
1712	0.992
1713	1.186
1714	0.827
1715	1.404
1716	1.207
1717	1.129
1718	1.182
1719	0.718
1720	1.151
1721	0.77
1722	1.102
1723	0.953
1724	1.32
1725	1.198
1726	1.213
1727	1.096
1728	1.121
1729	0.429
1730	1.104
1731	1.344
1732	1.406
1733	0.992
1734	1.284
1735	1.075
1736	1.527
1737	0.915
1738	1.078
1739	0.495
1740	0.48
1741	0.73
1742	0.928
1743	1.117
1744	1.26
1745	1.475
1746	1.375
1747	1.512
1748	0.907
1749	1.319
1750	0.714
1751	1.17
1752	1.357
1753	0.919
1754	0.869
1755	1.107
1756	0.972
1757	0.9
1758	1.032
1759	0.816
1760	1.091
1761	1.109
1762	0.784
1763	0.845
1764	0.816
1765	0.928
1766	1.089
1767	0.842
1768	1.125
1769	1.122
1770	0.579
1771	0.685
1772	0.759
1773	0.871
1774	0.934
1775	0.985
1776	0.551
1777	0.334
1778	0.671
1779	0.848
1780	0.59
1781	0.731
1782	0.599
1783	0.45
1784	0.795
1785	1.005
1786	0.889
1787	0.733
1788	0.61
1789	1.066
1790	1.131
1791	1.334
1792	1.298
1793	0.911
1794	0.819
1795	0.662
1796	0.792
1797	0.896
1798	0.807
1799	1.197
1800	0.79
1801	1.118
1802	1.17
1803	1.31
1804	1.233
1805	1.379
1806	1.251
1807	1.101
1808	1.114
1809	1.366
1810	1.303
1811	1.447
1812	1.019
1813	1.13
1814	1.058
1815	1.11
1816	1.03
1817	1.161
1818	1.118
1819	1.197
1820	1.24
1821	1.255
1822	0.903
1823	0.77
1824	1.031
1825	1.266
1826	1.355
1827	1.08
1828	1.162
1829	0.953
1830	1.163
1831	0.906
1832	1.505
1833	0.963
1834	1.1
1835	1.181
1836	1.254
1837	1.0
1838	1.146
1839	0.647
1840	0.837
1841	0.495
1842	0.77
1843	0.639
1844	0.731
1845	0.949
1846	0.566
1847	0.752
1848	0.783
1849	0.693
1850	0.813
1851	1.016
1852	1.144
1853	1.198
1854	1.1
1855	1.301
1856	0.947
1857	0.953
1858	0.927
1859	0.635
1860	1.015
1861	1.414
1862	1.02
1863	1.077
1864	0.849
1865	0.87
1866	1.375
1867	1.089
1868	1.196
1869	1.127
1870	1.083
1871	0.752
1872	1.02
1873	0.97
1874	0.754
1875	1.044
1876	0.992
1877	1.198
1878	1.193
1879	0.961
1880	0.735
1881	1.225
1882	0.879
1883	0.79
1884	1.108
1885	1.414
1886	1.031
1887	0.899
1888	0.689
1889	0.341
1890	0.685
1891	0.947
1892	0.809
1893	0.954
1894	1.222
1895	1.151
1896	1.164
1897	1.299
1898	1.277
1899	1.045
1900	1.662
1901	1.674
1902	1.039
1903	0.893
1904	1.209
1905	1.132
1906	1.008
1907	1.723
1908	1.468
1909	1.403
1910	1.251
1911	1.192
1912	0.7
1913	1.259
1914	1.26
1915	0.868
1916	0.981
1917	0.764
1918	0.674
1919	0.734
1920	0.584
1921	1.041
1922	0.809
1923	0.857
1924	0.414
1925	0.687
1926	0.624
1927	0.726
1928	0.8
1929	0.526
1930	0.647
1931	0.308
1932	0.577
1933	0.211
1934	0.197
1935	0.357
1936	0.422
1937	0.305
1938	0.864
1939	0.553
1940	0.772
1941	0.912
1942	1.092
1943	1.224
1944	0.892
1945	0.995
1946	1.182
1947	0.779
1948	0.931
1949	0.905
1950	0.865
1951	1.095
1952	0.891
1953	1.234
1954	1.144
1955	0.861
1956	1.105
1957	1.367
1958	1.453
1959	0.735
1960	0.84
1961	0.53
1962	0.895
1963	1.035
1964	1.145
1965	1.188
1966	1.2
1967	1.042
1968	0.755
1969	1.372
1970	1.238
1971	1.173
1972	1.379
1973	1.05
1974	1.062
1975	1.245
1976	0.837
1977	0.906
1978	1.28
1979	0.782
1980	1.504