# northamerica_usa_tx006 - Ft. Worth - 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/4858
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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_tx006 - Ft. Worth - 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: Ft. Worth
#	Location:
#	Country: United States
#	Northernmost_Latitude: 32.85
#	Southernmost_Latitude: 32.85
#	Easternmost_Longitude: -97.48
#	Westernmost_Longitude: -97.48
#	Elevation: 190 m
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# Data_Collection
#	Collection_Name: northamerica_usa_tx006B
#	Earliest_Year: 1752
#	Most_Recent_Year: 1980
#	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":"4.8872356304","T2":"17.8583269051","M1":"0.0226940148164","M2":"0.520484973827"}}
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# 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
1752	1.073
1753	1.355
1754	1.102
1755	0.631
1756	0.602
1757	0.765
1758	1.212
1759	1.265
1760	1.45
1761	1.284
1762	1.267
1763	0.973
1764	0.845
1765	0.838
1766	0.734
1767	0.704
1768	0.753
1769	0.897
1770	0.752
1771	0.918
1772	0.581
1773	0.694
1774	0.875
1775	0.629
1776	0.512
1777	0.844
1778	0.82
1779	0.708
1780	0.616
1781	0.826
1782	1.237
1783	1.237
1784	1.153
1785	1.047
1786	0.848
1787	0.893
1788	1.03
1789	0.509
1790	0.533
1791	0.701
1792	1.083
1793	1.299
1794	1.331
1795	1.339
1796	1.366
1797	0.715
1798	0.609
1799	1.116
1800	1.025
1801	0.651
1802	0.582
1803	0.963
1804	0.764
1805	0.853
1806	0.561
1807	0.619
1808	0.542
1809	0.843
1810	0.994
1811	1.123
1812	0.855
1813	0.908
1814	0.782
1815	1.02
1816	0.784
1817	1.08
1818	0.76
1819	0.988
1820	0.651
1821	0.62
1822	0.711
1823	0.992
1824	0.713
1825	0.833
1826	0.727
1827	1.183
1828	0.875
1829	0.87
1830	0.916
1831	0.844
1832	0.802
1833	0.898
1834	0.895
1835	0.933
1836	1.682
1837	1.208
1838	1.263
1839	0.884
1840	0.941
1841	0.886
1842	0.73
1843	1.307
1844	1.228
1845	1.357
1846	1.258
1847	1.386
1848	0.909
1849	0.637
1850	1.05
1851	0.956
1852	0.848
1853	1.126
1854	1.165
1855	0.66
1856	0.866
1857	0.754
1858	0.916
1859	0.442
1860	0.63
1861	0.579
1862	0.63
1863	0.475
1864	0.563
1865	0.365
1866	0.525
1867	0.586
1868	0.839
1869	1.321
1870	1.213
1871	1.074
1872	1.092
1873	1.096
1874	0.824
1875	0.936
1876	0.983
1877	1.031
1878	1.001
1879	1.058
1880	1.188
1881	1.007
1882	1.391
1883	1.466
1884	1.478
1885	1.448
1886	0.75
1887	0.752
1888	1.501
1889	1.256
1890	1.71
1891	1.313
1892	1.3
1893	0.923
1894	0.683
1895	0.909
1896	0.685
1897	1.155
1898	1.257
1899	1.092
1900	0.913
1901	1.295
1902	1.069
1903	1.398
1904	1.051
1905	1.033
1906	1.575
1907	1.766
1908	1.523
1909	1.17
1910	1.374
1911	0.796
1912	0.861
1913	0.861
1914	1.055
1915	1.763
1916	1.543
1917	1.344
1918	0.866
1919	1.392
1920	1.368
1921	1.295
1922	1.143
1923	1.087
1924	1.161
1925	0.82
1926	1.009
1927	1.012
1928	1.441
1929	1.266
1930	1.089
1931	0.919
1932	1.212
1933	1.135
1934	0.744
1935	1.035
1936	0.924
1937	0.845
1938	0.957
1939	0.815
1940	1.005
1941	1.057
1942	1.073
1943	1.067
1944	0.775
1945	1.035
1946	0.907
1947	0.998
1948	0.871
1949	1.048
1950	1.063
1951	0.848
1952	0.682
1953	0.542
1954	0.704
1955	0.767
1956	0.691
1957	0.776
1958	0.737
1959	0.74
1960	0.812
1961	0.698
1962	0.643
1963	0.836
1964	0.686
1965	1.033
1966	0.863
1967	0.725
1968	1.021
1969	0.878
1970	0.965
1971	0.659
1972	0.791
1973	0.912
1974	0.751
1975	0.814
1976	0.781
1977	0.685
1978	0.686
1979	0.92
1980	0.747