# asia_indo001 - Bigin - 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/3046
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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: asia_indo001 - Bigin - 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
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# 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:
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#	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: Bigin
#	Location:
#	Country: Indonesia
#	Northernmost_Latitude: -7.25
#	Southernmost_Latitude: -7.25
#	Easternmost_Longitude: 111.83
#	Westernmost_Longitude: 111.83
#	Elevation: 75 m
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# Data_Collection
#	Collection_Name: asia_indo001B
#	Earliest_Year: 1849
#	Most_Recent_Year: 1995
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]"}}{"VSLite_parameters":{"T1":"4.93492154941","T2":"16.853080781","M1":"0.0228041252911","M2":"0.105269165607"}}
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# Species
#	Species_Name: teak
#	Species_Code: TEGR
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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
1849	1.055
1850	0.967
1851	1.177
1852	1.026
1853	1.285
1854	1.453
1855	0.487
1856	0.644
1857	0.682
1858	1.298
1859	1.08
1860	0.66
1861	1.59
1862	0.867
1863	1.176
1864	1.112
1865	0.979
1866	1.12
1867	1.248
1868	0.558
1869	1.045
1870	1.086
1871	0.813
1872	0.869
1873	0.466
1874	0.784
1875	0.954
1876	0.432
1877	0.534
1878	0.713
1879	1.339
1880	0.986
1881	0.998
1882	0.416
1883	0.455
1884	0.802
1885	0.801
1886	0.88
1887	0.817
1888	0.506
1889	0.565
1890	0.769
1891	0.265
1892	0.805
1893	0.783
1894	0.664
1895	0.633
1896	0.501
1897	0.797
1898	0.619
1899	0.708
1900	1.275
1901	0.666
1902	0.496
1903	0.591
1904	1.24
1905	1.041
1906	0.882
1907	1.095
1908	1.185
1909	1.228
1910	1.51
1911	1.41
1912	1.694
1913	1.535
1914	1.419
1915	1.32
1916	1.563
1917	1.863
1918	0.96
1919	1.281
1920	1.782
1921	1.194
1922	1.302
1923	1.254
1924	1.253
1925	1.189
1926	1.079
1927	1.12
1928	1.343
1929	0.824
1930	1.202
1931	1.421
1932	1.13
1933	1.157
1934	1.063
1935	0.835
1936	1.027
1937	1.123
1938	0.789
1939	0.833
1940	0.751
1941	0.698
1942	1.546
1943	0.835
1944	0.816
1945	0.96
1946	0.513
1947	0.777
1948	0.561
1949	0.597
1950	0.906
1951	0.883
1952	0.79
1953	1.424
1954	1.311
1955	1.37
1956	0.907
1957	0.617
1958	1.375
1959	0.833
1960	0.887
1961	0.75
1962	0.7
1963	0.314
1964	0.476
1965	0.419
1966	0.413
1967	0.494
1968	0.851
1969	1.053
1970	0.962
1971	0.98
1972	0.716
1973	1.015
1974	0.928
1975	1.391
1976	0.554
1977	0.903
1978	1.25
1979	0.902
1980	0.743
1981	1.064
1982	0.909
1983	1.253
1984	1.326
1985	1.248
1986	1.517
1987	0.64
1988	0.806
1989	0.714
1990	0.552
1991	0.535
1992	1.06
1993	0.461
1994	0.548
1995	0.677