# northamerica_mexico_mexi036 - Rio Verde - 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.
#
#
# Online_Resource:
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# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/4936
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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_mexi036 - Rio Verde - 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: Rio Verde
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 21.68
#	Southernmost_Latitude: 21.68
#	Easternmost_Longitude: -99.78
#	Westernmost_Longitude: -99.78
#	Elevation: 820 m
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# Data_Collection
#	Collection_Name: northamerica_mexico_mexi036B
#	Earliest_Year: 1700
#	Most_Recent_Year: 1996
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"M", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]"}}{"VSLite_parameters":{"T1":"5.07407018382","T2":"16.5861874872","M1":"0.0219554378147","M2":"0.521149284135"}}
#--------------------
# Species
#	Species_Name: Montezuma cypress
#	Species_Code: TAMU
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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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1700	0.615
1701	0.694
1702	0.774
1703	1.34
1704	1.206
1705	1.106
1706	0.85
1707	0.86
1708	0.933
1709	1.243
1710	1.102
1711	1.068
1712	1.294
1713	1.119
1714	1.198
1715	1.257
1716	1.26
1717	0.939
1718	1.148
1719	0.79
1720	0.688
1721	0.818
1722	0.751
1723	0.686
1724	0.888
1725	0.94
1726	1.041
1727	1.071
1728	1.228
1729	0.845
1730	0.917
1731	0.813
1732	0.65
1733	0.693
1734	0.733
1735	0.939
1736	0.981
1737	0.971
1738	1.008
1739	0.568
1740	0.758
1741	0.545
1742	0.35
1743	0.73
1744	0.859
1745	1.014
1746	1.084
1747	0.608
1748	0.795
1749	0.744
1750	0.733
1751	0.644
1752	0.833
1753	0.788
1754	1.08
1755	0.987
1756	0.894
1757	0.702
1758	0.77
1759	0.925
1760	0.857
1761	0.846
1762	0.69
1763	0.778
1764	0.679
1765	0.853
1766	0.658
1767	0.69
1768	1.012
1769	0.917
1770	0.89
1771	0.878
1772	0.984
1773	1.16
1774	1.031
1775	0.941
1776	0.927
1777	0.71
1778	0.612
1779	0.817
1780	0.639
1781	0.741
1782	0.814
1783	0.916
1784	0.802
1785	0.55
1786	0.622
1787	0.491
1788	0.827
1789	0.525
1790	0.687
1791	0.961
1792	0.964
1793	0.651
1794	0.67
1795	0.807
1796	0.616
1797	0.54
1798	0.773
1799	0.574
1800	0.921
1801	0.964
1802	1.28
1803	1.206
1804	0.931
1805	0.777
1806	0.806
1807	0.884
1808	0.618
1809	1.321
1810	0.68
1811	0.647
1812	0.684
1813	0.538
1814	0.51
1815	0.608
1816	0.572
1817	0.59
1818	0.494
1819	0.415
1820	0.729
1821	0.988
1822	1.231
1823	0.797
1824	1.319
1825	1.423
1826	1.475
1827	1.556
1828	0.749
1829	1.409
1830	0.628
1831	1.627
1832	0.876
1833	0.975
1834	0.802
1835	0.963
1836	0.94
1837	0.938
1838	0.725
1839	0.93
1840	1.308
1841	1.045
1842	1.133
1843	0.928
1844	1.057
1845	1.092
1846	1.783
1847	1.435
1848	1.258
1849	1.14
1850	1.158
1851	0.954
1852	0.553
1853	0.524
1854	0.455
1855	0.652
1856	0.552
1857	0.646
1858	0.691
1859	0.551
1860	0.657
1861	0.765
1862	0.5
1863	0.768
1864	0.666
1865	1.144
1866	0.641
1867	0.901
1868	0.617
1869	1.146
1870	0.612
1871	0.544
1872	0.772
1873	0.59
1874	0.744
1875	0.5
1876	0.566
1877	0.821
1878	0.841
1879	0.853
1880	0.643
1881	1.142
1882	0.782
1883	1.21
1884	1.055
1885	1.271
1886	1.606
1887	1.654
1888	1.637
1889	1.219
1890	0.729
1891	0.999
1892	0.838
1893	1.021
1894	1.193
1895	1.247
1896	0.887
1897	1.327
1898	0.886
1899	1.44
1900	0.97
1901	1.058
1902	0.975
1903	1.758
1904	1.212
1905	1.566
1906	1.405
1907	1.3
1908	1.393
1909	0.866
1910	1.546
1911	1.141
1912	1.16
1913	1.452
1914	1.294
1915	0.998
1916	1.05
1917	0.793
1918	1.267
1919	0.971
1920	0.819
1921	0.826
1922	0.746
1923	0.983
1924	0.886
1925	1.074
1926	1.018
1927	0.474
1928	0.895
1929	0.643
1930	1.082
1931	1.239
1932	0.801
1933	0.93
1934	0.982
1935	0.626
1936	0.776
1937	0.641
1938	0.524
1939	0.586
1940	0.8
1941	1.299
1942	0.794
1943	1.106
1944	1.034
1945	0.939
1946	1.093
1947	0.984
1948	1.115
1949	0.9
1950	0.767
1951	0.894
1952	0.93
1953	0.638
1954	1.05
1955	0.696
1956	0.606
1957	0.584
1958	1.385
1959	1.054
1960	0.773
1961	1.008
1962	1.04
1963	1.068
1964	0.899
1965	0.87
1966	1.209
1967	1.219
1968	1.504
1969	0.968
1970	1.337
1971	0.838
1972	0.939
1973	0.921
1974	0.684
1975	0.844
1976	0.989
1977	0.782
1978	1.15
1979	1.21
1980	1.042
1981	1.357
1982	0.915
1983	1.126
1984	1.138
1985	1.27
1986	1.127
1987	1.137
1988	0.992
1989	0.766
1990	1.002
1991	0.922
1992	1.378
1993	0.744
1994	1.051
1995	0.747
1996	0.959