# northamerica_mexico_mexi014 - Sierra del Carmen Madera Canyon - 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/4991
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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_mexi014 - Sierra del Carmen Madera Canyon - 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: Sierra del Carmen Madera Canyon
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 28.93
#	Southernmost_Latitude: 28.93
#	Easternmost_Longitude: -102.62
#	Westernmost_Longitude: -102.62
#	Elevation: 2030 m
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# Data_Collection
#	Collection_Name: northamerica_mexico_mexi014B
#	Earliest_Year: 1693
#	Most_Recent_Year: 1971
#	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":"4.27186097571","T2":"16.5639775156","M1":"0.0230342271307","M2":"0.451265471258"}}
#--------------------
# 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
1693	1.055
1694	1.188
1695	1.254
1696	0.63
1697	1.169
1698	1.001
1699	1.497
1700	1.401
1701	1.071
1702	0.627
1703	0.954
1704	0.678
1705	0.747
1706	1.158
1707	0.83
1708	1.049
1709	0.898
1710	1.149
1711	1.006
1712	1.668
1713	1.036
1714	1.051
1715	0.921
1716	0.622
1717	1.017
1718	1.361
1719	1.228
1720	1.027
1721	1.633
1722	1.139
1723	1.337
1724	0.96
1725	0.831
1726	1.401
1727	1.062
1728	1.021
1729	0.945
1730	0.927
1731	0.89
1732	1.147
1733	0.654
1734	1.513
1735	1.801
1736	0.979
1737	1.233
1738	1.015
1739	0.674
1740	1.044
1741	0.702
1742	0.459
1743	0.652
1744	1.037
1745	1.163
1746	1.289
1747	1.456
1748	0.961
1749	0.95
1750	0.718
1751	0.809
1752	0.239
1753	0.786
1754	0.393
1755	0.696
1756	0.97
1757	0.867
1758	0.897
1759	1.39
1760	1.291
1761	1.191
1762	0.809
1763	0.218
1764	0.321
1765	0.667
1766	0.974
1767	0.725
1768	0.983
1769	1.302
1770	1.507
1771	1.164
1772	0.536
1773	1.047
1774	0.267
1775	0.887
1776	0.923
1777	0.979
1778	0.5
1779	1.414
1780	1.542
1781	1.392
1782	0.934
1783	1.709
1784	1.515
1785	0.729
1786	0.554
1787	0.383
1788	0.79
1789	0.31
1790	0.464
1791	0.818
1792	0.994
1793	1.215
1794	1.298
1795	1.077
1796	0.531
1797	0.79
1798	0.405
1799	0.593
1800	0.868
1801	0.214
1802	0.979
1803	0.714
1804	0.584
1805	0.386
1806	0.622
1807	0.907
1808	0.81
1809	1.022
1810	0.934
1811	0.805
1812	0.442
1813	0.828
1814	0.882
1815	1.369
1816	1.367
1817	1.017
1818	1.238
1819	0.749
1820	0.896
1821	1.197
1822	0.867
1823	0.672
1824	1.474
1825	1.401
1826	1.371
1827	1.741
1828	1.265
1829	1.502
1830	1.091
1831	0.679
1832	1.159
1833	1.301
1834	1.146
1835	1.146
1836	0.954
1837	1.203
1838	0.861
1839	1.092
1840	0.815
1841	1.079
1842	1.047
1843	1.179
1844	1.255
1845	1.362
1846	1.379
1847	0.778
1848	1.422
1849	1.103
1850	1.393
1851	1.519
1852	1.429
1853	1.57
1854	1.286
1855	1.211
1856	1.256
1857	0.853
1858	1.471
1859	0.772
1860	0.66
1861	0.723
1862	0.223
1863	0.873
1864	0.698
1865	0.955
1866	0.96
1867	0.893
1868	0.702
1869	1.436
1870	1.175
1871	0.739
1872	1.011
1873	0.877
1874	0.609
1875	0.803
1876	0.899
1877	0.703
1878	1.035
1879	0.42
1880	0.808
1881	0.969
1882	1.157
1883	0.951
1884	0.727
1885	1.154
1886	0.594
1887	0.63
1888	0.898
1889	1.099
1890	0.623
1891	0.898
1892	0.35
1893	0.456
1894	0.409
1895	0.847
1896	0.894
1897	1.394
1898	1.217
1899	0.983
1900	1.341
1901	0.98
1902	0.759
1903	1.324
1904	0.695
1905	1.152
1906	1.231
1907	0.691
1908	0.997
1909	0.567
1910	0.616
1911	1.058
1912	0.922
1913	1.429
1914	1.405
1915	1.473
1916	0.566
1917	0.665
1918	0.998
1919	1.569
1920	1.484
1921	1.275
1922	0.763
1923	1.381
1924	0.938
1925	0.97
1926	1.175
1927	1.093
1928	1.18
1929	0.782
1930	1.312
1931	1.556
1932	0.604
1933	0.93
1934	0.985
1935	0.925
1936	1.209
1937	1.135
1938	1.115
1939	1.152
1940	1.935
1941	1.883
1942	1.061
1943	0.89
1944	1.103
1945	0.693
1946	1.061
1947	0.918
1948	0.555
1949	1.283
1950	0.898
1951	0.656
1952	0.372
1953	0.1
1954	0.562
1955	0.422
1956	0.491
1957	0.73
1958	0.885
1959	1.207
1960	0.616
1961	1.019
1962	0.641
1963	0.456
1964	0.841
1965	0.783
1966	1.049
1967	0.613
1968	1.375
1969	0.733
1970	1.008
1971	0.746