# northamerica_mexico_mexi024 - Cerro Potosi - 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/4827
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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_mexico_mexi024 - Cerro Potosi - 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
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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: Cerro Potosi
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 24.83
#	Southernmost_Latitude: 24.83
#	Easternmost_Longitude: -100.07
#	Westernmost_Longitude: -100.07
#	Elevation: 2500 m
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# Data_Collection
#	Collection_Name: northamerica_mexico_mexi024B
#	Earliest_Year: 1875
#	Most_Recent_Year: 1995
#	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":"4.57349677419","T2":"16.6868974933","M1":"0.0227651939481","M2":"0.422431625661"}}
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# Species
#	Species_Name: Douglas fir
#	Species_Code: PSME
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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
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age	trsgi
1875	0.502
1876	0.624
1877	0.722
1878	0.931
1879	0.695
1880	0.498
1881	1.013
1882	0.878
1883	1.109
1884	0.983
1885	1.292
1886	1.333
1887	0.947
1888	0.926
1889	0.945
1890	0.472
1891	0.859
1892	0.686
1893	0.832
1894	1.001
1895	1.374
1896	0.805
1897	1.577
1898	1.187
1899	0.93
1900	1.295
1901	1.143
1902	0.626
1903	1.489
1904	1.275
1905	1.663
1906	1.464
1907	0.651
1908	1.035
1909	0.619
1910	0.649
1911	0.754
1912	1.054
1913	1.683
1914	1.377
1915	0.891
1916	0.604
1917	0.292
1918	0.52
1919	1.233
1920	0.562
1921	0.588
1922	0.491
1923	0.947
1924	0.952
1925	0.857
1926	1.647
1927	0.726
1928	0.641
1929	0.357
1930	1.198
1931	1.486
1932	0.449
1933	0.88
1934	1.156
1935	0.964
1936	1.25
1937	1.197
1938	1.123
1939	1.362
1940	1.569
1941	2.013
1942	1.886
1943	1.13
1944	1.156
1945	0.557
1946	1.163
1947	0.917
1948	0.992
1949	1.193
1950	0.382
1951	0.598
1952	0.62
1953	0.221
1954	0.888
1955	0.588
1956	0.645
1957	0.49
1958	0.936
1959	1.6
1960	0.758
1961	0.752
1962	0.349
1963	0.534
1964	1.61
1965	0.801
1966	2.276
1967	1.244
1968	1.679
1969	0.847
1970	1.053
1971	0.791
1972	1.247
1973	1.231
1974	0.647
1975	0.656
1976	1.076
1977	1.22
1978	0.709
1979	1.241
1980	0.405
1981	1.276
1982	0.285
1983	0.67
1984	1.088
1985	0.974
1986	0.78
1987	1.684
1988	1.078
1989	0.423
1990	1.165
1991	0.732
1992	1.498
1993	0.917
1994	0.729
1995	0.629