# northamerica_mexico_mexi026 - El Malpaso - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
#-----------------------------------------------------------------------
# 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/4846
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_mexico_mexi026 - El Malpaso - 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.
#--------------------
#	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: El Malpaso
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 20.4
#	Southernmost_Latitude: 20.4
#	Easternmost_Longitude: -98.47
#	Westernmost_Longitude: -98.47
#	Elevation: 2580 m
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# Data_Collection
#	Collection_Name: northamerica_mexico_mexi026B
#	Earliest_Year: 1749
#	Most_Recent_Year: 1998
#	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":"5.20368059178","T2":"16.4446573459","M1":"0.0224768409335","M2":"0.564729826238"}}
#--------------------
# Species
#	Species_Name: Douglas fir
#	Species_Code: PSME
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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
1749	1.254
1750	0.867
1751	0.938
1752	1.254
1753	0.857
1754	0.974
1755	0.672
1756	1.4
1757	1.258
1758	1.445
1759	0.957
1760	0.5
1761	0.089
1762	0.543
1763	0.487
1764	0.308
1765	0.933
1766	1.07
1767	1.181
1768	1.076
1769	1.616
1770	1.823
1771	0.602
1772	0.445
1773	0.712
1774	1.366
1775	1.143
1776	0.902
1777	1.165
1778	1.032
1779	0.716
1780	0.71
1781	0.941
1782	1.262
1783	1.328
1784	1.429
1785	0.921
1786	0.83
1787	0.812
1788	1.108
1789	0.822
1790	0.671
1791	0.778
1792	1.094
1793	0.679
1794	0.62
1795	0.867
1796	0.939
1797	0.622
1798	0.671
1799	0.795
1800	0.881
1801	0.78
1802	1.343
1803	0.776
1804	0.782
1805	0.648
1806	0.745
1807	0.595
1808	0.481
1809	0.991
1810	0.871
1811	0.755
1812	0.697
1813	0.93
1814	0.536
1815	1.354
1816	1.452
1817	1.034
1818	1.105
1819	0.923
1820	0.975
1821	1.173
1822	1.018
1823	1.395
1824	1.391
1825	1.015
1826	1.258
1827	1.385
1828	1.03
1829	1.466
1830	1.263
1831	0.96
1832	1.168
1833	1.187
1834	1.114
1835	1.25
1836	0.98
1837	0.958
1838	0.777
1839	0.571
1840	1.087
1841	1.248
1842	1.113
1843	0.928
1844	1.186
1845	1.457
1846	1.044
1847	1.097
1848	1.248
1849	1.064
1850	1.188
1851	1.143
1852	1.378
1853	1.216
1854	1.133
1855	1.25
1856	1.021
1857	1.13
1858	0.754
1859	1.109
1860	0.835
1861	1.045
1862	0.758
1863	0.963
1864	1.008
1865	1.142
1866	1.067
1867	1.012
1868	0.772
1869	1.02
1870	1.104
1871	0.909
1872	0.928
1873	0.973
1874	1.167
1875	0.649
1876	1.0
1877	1.045
1878	0.698
1879	0.871
1880	0.743
1881	0.813
1882	0.652
1883	1.024
1884	0.585
1885	0.814
1886	0.946
1887	1.141
1888	1.29
1889	1.286
1890	1.094
1891	1.568
1892	1.4
1893	1.702
1894	0.983
1895	0.503
1896	0.498
1897	0.59
1898	0.883
1899	0.895
1900	0.868
1901	0.884
1902	0.95
1903	1.011
1904	1.183
1905	1.173
1906	1.039
1907	1.265
1908	1.048
1909	0.511
1910	1.128
1911	0.893
1912	0.988
1913	1.066
1914	1.086
1915	0.74
1916	0.796
1917	0.841
1918	0.923
1919	0.936
1920	1.1
1921	0.833
1922	0.749
1923	1.063
1924	0.837
1925	1.203
1926	1.197
1927	1.08
1928	0.822
1929	0.913
1930	0.928
1931	1.071
1932	0.721
1933	0.46
1934	0.77
1935	0.893
1936	0.576
1937	0.809
1938	0.778
1939	0.568
1940	0.463
1941	0.845
1942	0.736
1943	0.665
1944	0.737
1945	0.647
1946	0.905
1947	1.204
1948	1.339
1949	0.668
1950	1.408
1951	1.391
1952	1.714
1953	1.226
1954	0.913
1955	0.968
1956	1.572
1957	0.748
1958	0.816
1959	1.32
1960	0.836
1961	0.912
1962	0.854
1963	0.819
1964	0.734
1965	0.984
1966	1.249
1967	1.137
1968	1.267
1969	0.968
1970	0.95
1971	0.869
1972	1.052
1973	0.961
1974	1.245
1975	1.284
1976	1.387
1977	0.851
1978	1.198
1979	0.959
1980	0.899
1981	0.974
1982	0.489
1983	0.775
1984	0.933
1985	1.042
1986	0.929
1987	0.863
1988	0.931
1989	1.005
1990	1.037
1991	0.807
1992	1.557
1993	1.093
1994	1.027
1995	0.777
1996	0.927
1997	0.816
1998	0.625