# northamerica_usa_ca599 - Torrey Pine State Reserve - 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/2764
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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_ca599 - Torrey Pine State Reserve - Breitenmoser Tree Ring Chronology Data
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# 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: Torrey Pine State Reserve
#	Location:
#	Country: United States
#	Northernmost_Latitude: 32.92
#	Southernmost_Latitude: 32.92
#	Easternmost_Longitude: -117.25
#	Westernmost_Longitude: -117.25
#	Elevation: 100 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ca599B
#	Earliest_Year: 1865
#	Most_Recent_Year: 1994
#	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":"4.95346068868","T2":"16.7206374694","M1":"0.022803004902","M2":"0.433818344554"}}
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# Species
#	Species_Name: Torrey pine
#	Species_Code: PITO
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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
1865	0.517
1866	0.853
1867	2.603
1868	2.308
1869	1.721
1870	0.843
1871	0.778
1872	0.532
1873	0.564
1874	0.865
1875	0.764
1876	0.921
1877	0.356
1878	0.927
1879	0.639
1880	1.0
1881	0.748
1882	0.744
1883	0.163
1884	1.789
1885	1.011
1886	1.101
1887	0.684
1888	0.694
1889	1.245
1890	1.076
1891	0.849
1892	0.824
1893	1.03
1894	0.728
1895	1.071
1896	0.701
1897	0.96
1898	0.468
1899	0.548
1900	0.275
1901	0.605
1902	0.26
1903	1.287
1904	0.225
1905	0.974
1906	1.881
1907	1.473
1908	0.819
1909	1.355
1910	1.259
1911	0.885
1912	0.664
1913	0.187
1914	0.94
1915	2.107
1916	1.554
1917	1.13
1918	0.786
1919	0.947
1920	0.444
1921	0.487
1922	1.4
1923	0.789
1924	0.262
1925	0.317
1926	1.159
1927	1.214
1928	0.537
1929	0.749
1930	0.557
1931	0.757
1932	1.829
1933	2.207
1934	0.515
1935	1.528
1936	1.317
1937	1.408
1938	1.144
1939	1.103
1940	0.927
1941	2.2
1942	2.344
1943	2.214
1944	1.556
1945	1.094
1946	0.95
1947	0.545
1948	0.222
1949	0.546
1950	0.578
1951	0.32
1952	1.861
1953	0.679
1954	0.771
1955	0.547
1956	0.313
1957	0.533
1958	2.0
1959	0.814
1960	0.508
1961	0.075
1962	0.862
1963	0.393
1964	0.266
1965	0.464
1966	0.934
1967	1.277
1968	0.535
1969	0.703
1970	0.347
1971	0.429
1972	0.176
1973	0.989
1974	0.71
1975	0.684
1976	0.666
1977	0.811
1978	2.097
1979	2.075
1980	2.204
1981	1.025
1982	1.175
1983	2.469
1984	0.421
1985	0.854
1986	1.14
1987	0.33
1988	1.429
1989	0.353
1990	0.303
1991	0.606
1992	0.782
1993	1.083
1994	0.688