# northamerica_usa_ca552 - San Bernardino Mountains Q - Breitenmoser Tree Ring Chronology Data
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#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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/4189
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_ca552 - San Bernardino Mountains Q - 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.
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#	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: San Bernardino Mountains Q
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.1
#	Southernmost_Latitude: 34.1
#	Easternmost_Longitude: -116.97
#	Westernmost_Longitude: -116.97
#	Elevation: 1600 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ca552B
#	Earliest_Year: 1764
#	Most_Recent_Year: 1988
#	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":"3.96010962642","T2":"16.7746690325","M1":"0.0230784876929","M2":"0.451909598593"}}
#--------------------
# Species
#	Species_Name: bigcone Douglas fir
#	Species_Code: PSMA
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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
1764	1.173
1765	0.391
1766	1.194
1767	1.249
1768	1.354
1769	1.45
1770	1.181
1771	1.404
1772	0.873
1773	0.732
1774	0.903
1775	1.129
1776	1.207
1777	0.307
1778	0.687
1779	0.548
1780	0.711
1781	0.744
1782	0.227
1783	0.786
1784	0.667
1785	0.684
1786	0.875
1787	1.368
1788	0.622
1789	0.819
1790	0.917
1791	1.355
1792	1.155
1793	1.521
1794	0.598
1795	0.821
1796	1.208
1797	1.483
1798	1.09
1799	1.187
1800	0.797
1801	0.977
1802	1.276
1803	0.954
1804	1.344
1805	1.177
1806	0.969
1807	0.797
1808	1.17
1809	0.286
1810	1.002
1811	1.067
1812	0.421
1813	0.829
1814	0.732
1815	0.861
1816	1.144
1817	0.723
1818	1.168
1819	1.248
1820	0.418
1821	0.95
1822	0.43
1823	0.544
1824	0.452
1825	0.763
1826	1.01
1827	0.893
1828	1.176
1829	0.479
1830	1.066
1831	1.071
1832	1.296
1833	1.192
1834	0.921
1835	0.929
1836	1.204
1837	1.187
1838	1.364
1839	1.595
1840	1.425
1841	0.433
1842	0.831
1843	0.622
1844	0.778
1845	0.522
1846	1.038
1847	0.703
1848	0.7
1849	0.68
1850	0.985
1851	0.795
1852	1.042
1853	1.561
1854	1.363
1855	1.493
1856	0.857
1857	-0.053
1858	1.208
1859	1.159
1860	1.041
1861	1.018
1862	1.384
1863	0.848
1864	1.021
1865	1.166
1866	1.516
1867	1.263
1868	1.994
1869	1.571
1870	1.063
1871	1.179
1872	0.887
1873	0.884
1874	0.951
1875	0.612
1876	0.903
1877	0.74
1878	0.894
1879	0.145
1880	0.815
1881	0.819
1882	0.6
1883	0.604
1884	1.117
1885	0.825
1886	1.357
1887	1.115
1888	1.339
1889	1.163
1890	1.41
1891	1.694
1892	1.427
1893	1.155
1894	0.709
1895	1.028
1896	0.446
1897	0.72
1898	0.628
1899	0.322
1900	0.755
1901	1.037
1902	0.805
1903	0.875
1904	0.736
1905	1.097
1906	1.516
1907	1.29
1908	1.487
1909	1.649
1910	1.256
1911	0.921
1912	0.821
1913	0.794
1914	1.3
1915	1.294
1916	1.595
1917	1.779
1918	0.856
1919	0.872
1920	1.447
1921	1.471
1922	1.205
1923	1.037
1924	1.149
1925	0.866
1926	1.022
1927	0.886
1928	0.614
1929	0.818
1930	0.789
1931	0.899
1932	0.996
1933	0.596
1934	0.365
1935	0.973
1936	0.779
1937	0.945
1938	1.208
1939	1.084
1940	1.295
1941	1.413
1942	0.933
1943	1.242
1944	1.211
1945	1.37
1946	1.289
1947	0.924
1948	0.675
1949	0.508
1950	0.652
1951	0.278
1952	0.682
1953	0.72
1954	0.797
1955	0.815
1956	1.063
1957	0.819
1958	1.165
1959	0.404
1960	0.63
1961	-0.059
1962	0.581
1963	0.3
1964	0.814
1965	0.781
1966	0.823
1967	1.105
1968	0.861
1969	0.984
1970	0.812
1971	0.566
1972	0.157
1973	0.742
1974	0.724
1975	0.965
1976	0.572
1977	0.948
1978	0.942
1979	1.211
1980	1.523
1981	0.68
1982	1.127
1983	2.267
1984	0.972
1985	1.528
1986	1.588
1987	1.169
1988	0.847