# northamerica_usa_nm568 - Mimbres Junction Recollection - 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/3379
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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_usa_nm568 - Mimbres Junction Recollection - 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: Mimbres Junction Recollection
#	Location:
#	Country: United States
#	Northernmost_Latitude: 32.95
#	Southernmost_Latitude: 32.95
#	Easternmost_Longitude: -108.02
#	Westernmost_Longitude: -108.02
#	Elevation: 1950 m
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# Data_Collection
#	Collection_Name: northamerica_usa_nm568B
#	Earliest_Year: 1697
#	Most_Recent_Year: 1986
#	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":"4.40601981626","T2":"16.9626008877","M1":"0.0234926779697","M2":"0.430409758148"}}
#--------------------
# Species
#	Species_Name: pinyon pine
#	Species_Code: PIED
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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
1697	1.186
1698	1.269
1699	1.517
1700	1.156
1701	1.409
1702	0.711
1703	1.365
1704	0.896
1705	1.005
1706	1.138
1707	0.972
1708	1.26
1709	0.661
1710	1.407
1711	1.028
1712	1.215
1713	0.689
1714	0.792
1715	0.617
1716	0.514
1717	1.118
1718	1.216
1719	1.17
1720	1.207
1721	1.235
1722	1.204
1723	0.838
1724	1.122
1725	0.886
1726	1.187
1727	1.085
1728	1.1
1729	1.502
1730	1.126
1731	1.046
1732	1.462
1733	0.309
1734	1.168
1735	0.894
1736	0.8
1737	0.798
1738	1.15
1739	0.51
1740	1.0
1741	1.373
1742	0.885
1743	1.439
1744	0.777
1745	1.05
1746	1.569
1747	1.31
1748	0.535
1749	1.178
1750	0.592
1751	1.354
1752	0.285
1753	0.461
1754	0.624
1755	0.233
1756	0.644
1757	0.39
1758	0.855
1759	1.006
1760	0.727
1761	0.765
1762	1.489
1763	0.441
1764	0.978
1765	0.693
1766	0.653
1767	0.786
1768	0.915
1769	0.952
1770	1.272
1771	1.603
1772	0.978
1773	-0.001
1774	0.3
1775	1.147
1776	0.929
1777	0.36
1778	0.938
1779	1.197
1780	0.29
1781	0.705
1782	0.482
1783	1.131
1784	1.137
1785	0.833
1786	0.691
1787	1.342
1788	0.814
1789	0.995
1790	1.21
1791	1.103
1792	1.204
1793	1.72
1794	0.558
1795	1.282
1796	0.924
1797	0.5
1798	1.046
1799	0.939
1800	0.836
1801	0.752
1802	1.02
1803	0.331
1804	1.161
1805	0.566
1806	0.39
1807	1.152
1808	1.072
1809	0.889
1810	1.369
1811	0.79
1812	0.741
1813	0.479
1814	0.705
1815	1.289
1816	1.556
1817	0.827
1818	-0.005
1819	0.458
1820	0.376
1821	0.801
1822	0.457
1823	0.887
1824	1.114
1825	0.694
1826	0.997
1827	1.272
1828	1.541
1829	1.397
1830	1.445
1831	0.57
1832	0.697
1833	1.491
1834	1.178
1835	1.141
1836	0.501
1837	1.129
1838	0.504
1839	1.301
1840	0.979
1841	0.915
1842	0.596
1843	1.052
1844	1.281
1845	1.396
1846	1.148
1847	0.538
1848	0.784
1849	1.641
1850	1.345
1851	0.316
1852	1.184
1853	0.708
1854	0.781
1855	1.021
1856	1.353
1857	1.159
1858	0.954
1859	0.25
1860	0.912
1861	0.33
1862	0.036
1863	0.245
1864	0.391
1865	1.089
1866	0.999
1867	1.088
1868	1.37
1869	1.349
1870	0.925
1871	1.441
1872	0.886
1873	1.0
1874	1.33
1875	0.754
1876	1.325
1877	1.534
1878	0.942
1879	1.28
1880	0.525
1881	0.89
1882	1.142
1883	0.775
1884	1.138
1885	1.764
1886	1.176
1887	1.325
1888	0.94
1889	1.43
1890	0.627
1891	2.006
1892	0.88
1893	0.437
1894	0.642
1895	0.665
1896	0.708
1897	1.288
1898	1.8
1899	1.01
1900	0.557
1901	1.161
1902	0.667
1903	2.267
1904	0.315
1905	2.087
1906	2.112
1907	2.449
1908	1.912
1909	1.025
1910	0.402
1911	1.817
1912	2.071
1913	1.33
1914	2.395
1915	1.239
1916	1.074
1917	1.531
1918	0.406
1919	1.693
1920	1.229
1921	1.331
1922	1.024
1923	1.056
1924	1.409
1925	-0.006
1926	1.062
1927	1.078
1928	1.155
1929	1.189
1930	1.163
1931	1.313
1932	0.817
1933	1.266
1934	0.465
1935	1.316
1936	0.716
1937	1.094
1938	0.656
1939	0.584
1940	1.296
1941	1.459
1942	1.084
1943	0.792
1944	0.37
1945	1.115
1946	0.489
1947	0.531
1948	0.817
1949	0.993
1950	0.178
1951	-0.006
1952	1.229
1953	0.713
1954	-0.006
1955	0.003
1956	-0.006
1957	0.39
1958	1.059
1959	0.545
1960	1.015
1961	0.346
1962	0.93
1963	0.885
1964	0.787
1965	1.307
1966	1.501
1967	0.605
1968	1.422
1969	0.231
1970	0.72
1971	-0.006
1972	0.952
1973	1.159
1974	-0.006
1975	1.445
1976	1.116
1977	1.192
1978	0.782
1979	1.757
1980	0.961
1981	0.462
1982	0.994
1983	1.368
1984	1.358
1985	1.518
1986	1.357