ÃÂ¯ÃÂ»ÃÂ¿# northamerica_mexico_mexi044 - Cerro la Pena - Breitenmoser Tree Ring Chronology Data
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#		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/8546
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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_mexi044 - Cerro la Pena - 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
#------------------
# Site_Information
#	Site_Name: Cerro la Pena
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 17.17
#	Southernmost_Latitude: 17.17
#	Easternmost_Longitude: -96.63
#	Westernmost_Longitude: -96.63
#	Elevation: 2550 m
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# Data_Collection
#	Collection_Name: northamerica_mexico_mexi044B
#	Earliest_Year: 1561
#	Most_Recent_Year: 2000
#	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":"4.98308967164","T2":"11.6222778818","M1":"0.0226034555565","M2":"0.116514035759"}}
#--------------------
# Species
#	Species_Name: Douglas fir
#	Species_Code: PSME
#--------------------
# 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
1561	0.691
1562	0.639
1563	0.919
1564	0.878
1565	1.364
1566	1.03
1567	0.928
1568	0.392
1569	0.346
1570	0.553
1571	0.839
1572	0.476
1573	0.554
1574	0.669
1575	0.846
1576	0.805
1577	1.07
1578	1.224
1579	1.709
1580	0.912
1581	1.079
1582	0.875
1583	0.618
1584	0.573
1585	0.712
1586	1.082
1587	1.238
1588	0.817
1589	0.94
1590	1.061
1591	0.995
1592	1.036
1593	1.102
1594	0.961
1595	1.472
1596	1.12
1597	0.597
1598	0.828
1599	0.746
1600	1.162
1601	1.467
1602	1.286
1603	1.129
1604	1.451
1605	1.381
1606	1
1607	1.077
1608	1.457
1609	1.593
1610	2.045
1611	1.645
1612	1.326
1613	0.722
1614	0.96
1615	0.888
1616	0.837
1617	0.835
1618	0.857
1619	1.005
1620	1.115
1621	1.004
1622	1.162
1623	1.015
1624	0.945
1625	0.749
1626	0.631
1627	0.639
1628	0.556
1629	0.577
1630	0.606
1631	0.565
1632	0.807
1633	0.731
1634	0.802
1635	0.667
1636	0.87
1637	0.972
1638	0.766
1639	0.884
1640	0.985
1641	0.971
1642	1.221
1643	1.23
1644	1.038
1645	1.213
1646	0.896
1647	1.058
1648	1.178
1649	0.994
1650	1.595
1651	1.742
1652	1.466
1653	1.216
1654	1.049
1655	0.755
1656	0.952
1657	1.114
1658	1.092
1659	1.057
1660	1.313
1661	0.999
1662	1.444
1663	0.879
1664	1.18
1665	0.908
1666	0.691
1667	0.778
1668	0.775
1669	0.72
1670	0.745
1671	0.98
1672	0.862
1673	1.229
1674	0.947
1675	0.916
1676	1.174
1677	0.961
1678	0.836
1679	0.83
1680	0.885
1681	1.14
1682	0.764
1683	0.792
1684	0.67
1685	0.819
1686	0.819
1687	1.016
1688	1.057
1689	0.923
1690	1.125
1691	1.397
1692	1.315
1693	1.007
1694	1.164
1695	0.736
1696	0.739
1697	1.134
1698	0.822
1699	0.849
1700	0.912
1701	0.88
1702	0.87
1703	1.001
1704	1.155
1705	0.836
1706	0.999
1707	1.397
1708	1.049
1709	0.901
1710	0.797
1711	1.076
1712	1.321
1713	1.086
1714	0.85
1715	0.966
1716	0.943
1717	0.983
1718	1.034
1719	1.26
1720	0.871
1721	1.177
1722	1.21
1723	1.456
1724	1.202
1725	0.939
1726	1
1727	0.888
1728	1.195
1729	0.944
1730	0.915
1731	0.863
1732	1.112
1733	0.879
1734	0.659
1735	0.854
1736	0.962
1737	1.076
1738	1.434
1739	1.079
1740	1.089
1741	1.151
1742	0.726
1743	0.944
1744	0.77
1745	0.77
1746	0.432
1747	0.525
1748	0.843
1749	0.962
1750	0.764
1751	1.02
1752	1.203
1753	1.087
1754	1.281
1755	1.01
1756	1.197
1757	1.053
1758	0.901
1759	1.121
1760	1.209
1761	0.745
1762	0.889
1763	1.03
1764	0.764
1765	0.88
1766	0.645
1767	0.846
1768	1.171
1769	1.585
1770	1.264
1771	0.815
1772	0.9
1773	0.988
1774	0.97
1775	1.146
1776	1.096
1777	1.345
1778	1.32
1779	1.251
1780	0.649
1781	1.033
1782	1.206
1783	0.827
1784	1.274
1785	0.737
1786	0.678
1787	0.835
1788	0.816
1789	0.826
1790	0.929
1791	0.871
1792	1.03
1793	0.896
1794	1.395
1795	1.179
1796	1.011
1797	0.925
1798	0.791
1799	0.793
1800	0.919
1801	0.827
1802	1.091
1803	1.511
1804	0.393
1805	0.837
1806	0.94
1807	0.689
1808	0.471
1809	0.773
1810	0.898
1811	0.711
1812	1.364
1813	1.276
1814	0.937
1815	1.118
1816	1.245
1817	0.97
1818	0.948
1819	0.868
1820	0.92
1821	1.023
1822	0.922
1823	0.792
1824	0.872
1825	0.78
1826	1.159
1827	1.161
1828	1.487
1829	0.938
1830	1.469
1831	1.056
1832	1.627
1833	1.117
1834	1.257
1835	1.162
1836	0.58
1837	0.711
1838	0.643
1839	0.447
1840	0.889
1841	0.548
1842	1.158
1843	0.932
1844	0.947
1845	1.009
1846	0.985
1847	1.479
1848	1.65
1849	1.426
1850	1.28
1851	1.384
1852	1.756
1853	1.309
1854	1.044
1855	1.141
1856	1.413
1857	1.807
1858	1.26
1859	1.027
1860	1.096
1861	0.998
1862	0.741
1863	1.242
1864	0.955
1865	0.889
1866	1.247
1867	0.945
1868	0.688
1869	1.297
1870	0.739
1871	0.761
1872	0.908
1873	0.874
1874	0.849
1875	0.362
1876	0.774
1877	0.679
1878	0.182
1879	0.919
1880	0.869
1881	1.026
1882	0.916
1883	0.872
1884	0.74
1885	0.508
1886	1.112
1887	1.245
1888	1.031
1889	0.92
1890	1.295
1891	0.744
1892	1.044
1893	1.329
1894	0.948
1895	0.557
1896	0.255
1897	0.537
1898	0.89
1899	0.742
1900	0.63
1901	0.698
1902	0.585
1903	0.853
1904	1.077
1905	1.241
1906	1.172
1907	1.566
1908	0.973
1909	0.863
1910	1.09
1911	1.362
1912	1.133
1913	1.64
1914	1.493
1915	1.376
1916	1.476
1917	1.146
1918	1.054
1919	0.746
1920	0.889
1921	1.108
1922	0.922
1923	0.718
1924	1.204
1925	1.362
1926	1.227
1927	0.96
1928	0.944
1929	0.734
1930	0.629
1931	0.792
1932	0.6
1933	0.367
1934	0.661
1935	0.931
1936	0.86
1937	1.023
1938	1.259
1939	1.179
1940	0.639
1941	0.743
1942	0.851
1943	0.794
1944	0.872
1945	0.201
1946	0.635
1947	0.797
1948	1.166
1949	0.846
1950	1.111
1951	0.874
1952	1.311
1953	1.105
1954	1.439
1955	1.019
1956	1.327
1957	1.1
1958	0.797
1959	1.028
1960	1.067
1961	0.887
1962	0.723
1963	0.843
1964	0.715
1965	0.58
1966	0.88
1967	0.799
1968	1.813
1969	0.731
1970	0.855
1971	0.519
1972	0.77
1973	0.642
1974	1.018
1975	0.959
1976	1.314
1977	0.912
1978	1.03
1979	1.196
1980	0.703
1981	1.075
1982	0.945
1983	0.584
1984	0.932
1985	1.517
1986	0.934
1987	0.98
1988	0.936
1989	1.361
1990	1.287
1991	0.902
1992	1.881
1993	1.051
1994	1.231
1995	0.493
1996	1.328
1997	0.91
1998	0.478
1999	0.501
2000	0.729