# northamerica_mexico_mexi004 - Sierra del Nido Site B - 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/4041
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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_mexi004 - Sierra del Nido Site B - 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 Nido Site B
#	Location:
#	Country: Mexico
#	Northernmost_Latitude: 29.52
#	Southernmost_Latitude: 29.52
#	Easternmost_Longitude: -106.82
#	Westernmost_Longitude: -106.82
#	Elevation: 2333 m
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# Data_Collection
#	Collection_Name: northamerica_mexico_mexi004B
#	Earliest_Year: 1685
#	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":"4.74253161977","T2":"16.9301525071","M1":"0.0228903008511","M2":"0.328922837865"}}
#--------------------
# 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
#
#--------------------
# Data:
# Data lines follow (have no #)
# Data line format - tab-delimited text, variable short name as header
# Missing Values: nan
#
age	trsgi
1685	0.585
1686	1.125
1687	0.915
1688	0.698
1689	1.089
1690	1.082
1691	0.956
1692	1.306
1693	1.238
1694	1.47
1695	1.367
1696	0.765
1697	0.961
1698	0.557
1699	1.32
1700	0.979
1701	1.284
1702	0.417
1703	1.25
1704	1.292
1705	1.122
1706	1.367
1707	1.092
1708	1.191
1709	0.93
1710	1.312
1711	1.231
1712	1.2
1713	1.082
1714	1.115
1715	0.693
1716	0.807
1717	1.295
1718	1.275
1719	0.424
1720	1.328
1721	1.336
1722	1.414
1723	1.286
1724	0.728
1725	0.927
1726	1.25
1727	1.191
1728	0.441
1729	0.323
1730	0.425
1731	0.365
1732	0.277
1733	0.497
1734	0.493
1735	0.842
1736	0.883
1737	0.993
1738	0.952
1739	0.378
1740	0.412
1741	0.783
1742	0.416
1743	1.037
1744	1.186
1745	1.245
1746	1.91
1747	2.023
1748	0.526
1749	1.473
1750	0.843
1751	1.405
1752	0.779
1753	0.836
1754	0.78
1755	1.142
1756	1.003
1757	0.723
1758	0.919
1759	1.118
1760	0.88
1761	1.378
1762	1.362
1763	0.561
1764	1.309
1765	1.085
1766	1.333
1767	1.294
1768	1.211
1769	2.13
1770	1.651
1771	1.0
1772	0.798
1773	0.532
1774	0.695
1775	0.841
1776	0.723
1777	1.028
1778	0.677
1779	1.079
1780	0.902
1781	0.839
1782	1.136
1783	1.298
1784	1.447
1785	0.646
1786	0.723
1787	0.62
1788	0.921
1789	0.24
1790	0.625
1791	0.859
1792	1.197
1793	1.311
1794	0.989
1795	1.018
1796	0.971
1797	0.89
1798	0.726
1799	0.689
1800	1.069
1801	0.705
1802	0.714
1803	0.64
1804	0.988
1805	0.744
1806	1.036
1807	1.186
1808	1.04
1809	0.957
1810	1.053
1811	1.352
1812	1.137
1813	1.017
1814	1.116
1815	1.192
1816	1.391
1817	1.322
1818	0.982
1819	1.126
1820	0.935
1821	1.067
1822	1.129
1823	0.841
1824	0.97
1825	0.569
1826	1.012
1827	1.286
1828	1.051
1829	1.075
1830	1.141
1831	0.691
1832	0.894
1833	1.023
1834	1.144
1835	1.071
1836	0.725
1837	1.192
1838	1.175
1839	1.554
1840	1.568
1841	1.006
1842	1.347
1843	1.54
1844	1.561
1845	1.599
1846	1.514
1847	0.973
1848	1.259
1849	1.258
1850	1.382
1851	0.601
1852	0.933
1853	1.285
1854	0.958
1855	0.871
1856	1.467
1857	1.149
1858	1.54
1859	1.172
1860	1.16
1861	1.159
1862	0.905
1863	0.481
1864	0.97
1865	0.869
1866	1.018
1867	0.491
1868	0.682
1869	0.946
1870	1.174
1871	0.847
1872	0.825
1873	1.096
1874	0.943
1875	0.734
1876	0.958
1877	0.939
1878	0.329
1879	0.729
1880	0.714
1881	1.067
1882	1.0
1883	0.789
1884	0.964
1885	1.158
1886	0.808
1887	0.82
1888	1.083
1889	1.031
1890	0.566
1891	0.788
1892	0.456
1893	0.493
1894	0.811
1895	0.972
1896	1.114
1897	1.17
1898	1.359
1899	1.184
1900	1.111
1901	0.929
1902	0.862
1903	1.463
1904	0.546
1905	1.709
1906	1.645
1907	1.347
1908	1.354
1909	0.934
1910	0.688
1911	0.864
1912	1.311
1913	1.321
1914	1.438
1915	1.149
1916	0.676
1917	0.641
1918	0.706
1919	0.84
1920	1.371
1921	0.98
1922	0.796
1923	0.461
1924	1.053
1925	0.737
1926	1.316
1927	0.771
1928	1.047
1929	0.834
1930	0.84
1931	1.234
1932	0.893
1933	1.079
1934	0.726
1935	0.237
1936	0.681
1937	0.837
1938	0.91
1939	0.644
1940	0.912
1941	1.343
1942	0.708
1943	1.201
1944	1.418
1945	0.835
1946	1.119
1947	1.383
1948	0.503
1949	1.068
1950	1.395
1951	0.613
1952	0.798
1953	0.724
1954	0.484
1955	0.801
1956	1.032
1957	0.549
1958	1.106
1959	0.85
1960	0.583
1961	0.589
1962	0.567
1963	0.806
1964	0.589
1965	0.718
1966	0.636
1967	1.004
1968	1.278
1969	0.955
1970	0.631
1971	0.803