# northamerica_usa_tx030 - Capote Knob - 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/4823
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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_tx030 - Capote Knob - 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.
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#	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: Capote Knob
#	Location:
#	Country: United States
#	Northernmost_Latitude: 29.48
#	Southernmost_Latitude: 29.48
#	Easternmost_Longitude: -97.78
#	Westernmost_Longitude: -97.78
#	Elevation: 170 m
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# Data_Collection
#	Collection_Name: northamerica_usa_tx030B
#	Earliest_Year: 1764
#	Most_Recent_Year: 1982
#	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":"4.86801491198","T2":"16.4963534776","M1":"0.0222795569394","M2":"0.465946442122"}}
#--------------------
# Species
#	Species_Name: post oak
#	Species_Code: QUST
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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
1764	0.885
1765	0.991
1766	1.058
1767	1.089
1768	1.141
1769	0.944
1770	0.929
1771	0.878
1772	0.471
1773	0.755
1774	0.88
1775	0.691
1776	0.82
1777	0.673
1778	0.63
1779	0.764
1780	0.755
1781	0.935
1782	1.532
1783	1.152
1784	1.265
1785	0.816
1786	0.705
1787	1.017
1788	1.197
1789	0.641
1790	0.796
1791	1.062
1792	1.18
1793	1.327
1794	1.296
1795	1.172
1796	1.324
1797	1.117
1798	0.886
1799	1.284
1800	1.325
1801	0.803
1802	1.078
1803	0.993
1804	0.719
1805	0.554
1806	0.83
1807	0.977
1808	0.837
1809	0.9
1810	1.007
1811	0.959
1812	0.737
1813	1.061
1814	1.17
1815	1.314
1816	1.018
1817	1.152
1818	0.984
1819	0.815
1820	0.486
1821	1.027
1822	0.861
1823	0.917
1824	0.669
1825	0.913
1826	0.812
1827	0.783
1828	0.746
1829	0.776
1830	0.736
1831	0.669
1832	0.729
1833	1.044
1834	1.194
1835	0.625
1836	0.871
1837	0.736
1838	0.709
1839	0.7
1840	0.743
1841	0.599
1842	0.61
1843	0.925
1844	0.791
1845	0.721
1846	0.755
1847	0.672
1848	0.74
1849	0.796
1850	1.156
1851	0.733
1852	0.745
1853	0.736
1854	0.798
1855	0.734
1856	0.907
1857	0.693
1858	0.878
1859	0.811
1860	0.754
1861	0.997
1862	0.814
1863	0.856
1864	0.969
1865	1.101
1866	0.973
1867	1.292
1868	1.404
1869	1.536
1870	1.525
1871	1.415
1872	1.332
1873	1.098
1874	1.179
1875	1.64
1876	1.13
1877	1.403
1878	0.882
1879	1.195
1880	1.162
1881	1.298
1882	1.362
1883	0.922
1884	1.232
1885	1.083
1886	0.794
1887	0.71
1888	1.262
1889	0.91
1890	1.008
1891	1.29
1892	0.902
1893	0.968
1894	1.007
1895	0.916
1896	0.752
1897	1.123
1898	1.151
1899	0.837
1900	1.146
1901	1.099
1902	0.884
1903	1.61
1904	1.137
1905	1.182
1906	0.99
1907	1.033
1908	1.262
1909	1.062
1910	0.732
1911	1.301
1912	1.015
1913	0.882
1914	1.113
1915	1.055
1916	0.873
1917	0.896
1918	0.676
1919	1.118
1920	1.393
1921	1.138
1922	1.367
1923	1.157
1924	1.172
1925	0.458
1926	1.185
1927	0.714
1928	1.043
1929	1.053
1930	1.241
1931	0.939
1932	0.875
1933	0.83
1934	0.943
1935	1.188
1936	1.059
1937	0.901
1938	0.996
1939	0.598
1940	0.691
1941	0.847
1942	0.835
1943	0.853
1944	1.275
1945	0.99
1946	1.028
1947	1.196
1948	0.803
1949	1.025
1950	0.878
1951	0.634
1952	0.662
1953	0.872
1954	0.839
1955	0.604
1956	0.523
1957	0.924
1958	0.958
1959	0.992
1960	1.033
1961	0.969
1962	1.048
1963	0.779
1964	0.952
1965	1.317
1966	1.053
1967	0.606
1968	1.144
1969	0.901
1970	0.913
1971	0.544
1972	1.171
1973	1.039
1974	0.897
1975	1.173
1976	1.271
1977	1.166
1978	0.969
1979	1.045
1980	0.742
1981	0.904
1982	0.999