# northamerica_usa_ca537 - San Bernardino Mountains B - 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/4174
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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
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# Title
#	Study_Name: northamerica_usa_ca537 - San Bernardino Mountains B - Breitenmoser Tree Ring Chronology Data
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# Investigators
#	Investigators:  Breitenmoser, P.; Bronnimann, S.; Frank, D.
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# 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 B
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.27
#	Southernmost_Latitude: 34.27
#	Easternmost_Longitude: -117.33
#	Westernmost_Longitude: -117.33
#	Elevation: 1400 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ca537B
#	Earliest_Year: 1867
#	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":"3.61565315513","T2":"15.4723945499","M1":"0.022750601524","M2":"0.444730968964"}}
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# Species
#	Species_Name: bigcone Douglas fir
#	Species_Code: PSMA
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# Chronology:
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# Variables
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# 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)
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##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
1867	1.082
1868	1.428
1869	1.014
1870	0.853
1871	0.752
1872	0.791
1873	0.936
1874	0.791
1875	0.627
1876	0.758
1877	0.603
1878	0.874
1879	0.817
1880	0.923
1881	1.044
1882	1.003
1883	1.053
1884	1.635
1885	0.943
1886	1.434
1887	1.082
1888	1.137
1889	0.986
1890	1.001
1891	1.534
1892	0.913
1893	0.965
1894	0.947
1895	1.007
1896	0.75
1897	0.816
1898	0.602
1899	0.392
1900	0.608
1901	0.763
1902	0.732
1903	0.69
1904	0.733
1905	0.99
1906	1.398
1907	1.276
1908	1.309
1909	1.269
1910	0.856
1911	0.856
1912	1.064
1913	1.179
1914	1.383
1915	1.314
1916	1.542
1917	1.428
1918	0.854
1919	0.927
1920	1.168
1921	1.296
1922	0.955
1923	1.107
1924	1.273
1925	1.018
1926	1.017
1927	1.032
1928	0.992
1929	1.124
1930	0.961
1931	0.816
1932	0.86
1933	0.928
1934	0.483
1935	0.877
1936	0.859
1937	0.889
1938	1.23
1939	1.505
1940	1.372
1941	1.209
1942	1.173
1943	1.099
1944	1.401
1945	1.431
1946	1.468
1947	1.513
1948	1.134
1949	0.745
1950	0.84
1951	0.265
1952	0.777
1953	0.744
1954	0.756
1955	1.146
1956	1.091
1957	1.1
1958	1.37
1959	0.781
1960	0.421
1961	0.008
1962	0.427
1963	0.317
1964	0.621
1965	0.784
1966	0.915
1967	0.984
1968	0.769
1969	0.979
1970	0.792
1971	0.588
1972	0.261
1973	0.698
1974	0.761
1975	1.013
1976	0.993
1977	1.361
1978	0.926
1979	0.997
1980	1.461
1981	0.803
1982	1.031
1983	1.835
1984	0.708
1985	1.415
1986	1.502
1987	0.712
1988	1.16