# northamerica_usa_ar030 - Hot Springs - Breitenmoser Tree Ring Chronology Data
#-----------------------------------------------------------------------
#		World Data Center for Paleoclimatology, Boulder
#				and
#		NOAA Paleoclimatology Program
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# 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/4866
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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_ar030 - Hot Springs - 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: Hot Springs
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.52
#	Southernmost_Latitude: 34.52
#	Easternmost_Longitude: -93.5
#	Westernmost_Longitude: -93.5
#	Elevation: 275 m
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# Data_Collection
#	Collection_Name: northamerica_usa_ar030B
#	Earliest_Year: 1775
#	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":"4.33760594701","T2":"16.8157775839","M1":"0.0227673112226","M2":"0.570169759769"}}
#--------------------
# Species
#	Species_Name: shortleaf pine
#	Species_Code: PIEC
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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
1775	0.827
1776	1.083
1777	1.021
1778	1.133
1779	1.016
1780	0.941
1781	1.307
1782	0.928
1783	1.26
1784	0.719
1785	0.881
1786	0.822
1787	1.239
1788	0.911
1789	0.776
1790	0.91
1791	1.189
1792	0.958
1793	1.257
1794	1.212
1795	1.498
1796	1.075
1797	1.315
1798	1.042
1799	0.948
1800	0.77
1801	0.603
1802	0.78
1803	0.917
1804	1.087
1805	1.153
1806	0.803
1807	0.918
1808	1.251
1809	0.846
1810	1.106
1811	1.145
1812	1.052
1813	1.314
1814	1.051
1815	1.471
1816	1.284
1817	1.6
1818	0.985
1819	1.423
1820	0.993
1821	1.125
1822	0.518
1823	0.783
1824	0.734
1825	0.777
1826	0.628
1827	0.487
1828	0.769
1829	0.891
1830	0.881
1831	0.489
1832	0.675
1833	0.583
1834	0.727
1835	1.014
1836	0.929
1837	0.662
1838	0.756
1839	0.643
1840	0.444
1841	0.564
1842	0.833
1843	0.38
1844	1.286
1845	1.468
1846	1.384
1847	1.666
1848	1.593
1849	1.561
1850	1.038
1851	0.989
1852	1.214
1853	1.061
1854	1.01
1855	0.94
1856	0.631
1857	0.909
1858	1.066
1859	1.401
1860	0.739
1861	1.139
1862	0.863
1863	1.039
1864	1.312
1865	1.1
1866	1.101
1867	0.86
1868	0.543
1869	0.572
1870	1.045
1871	1.053
1872	1.377
1873	1.247
1874	0.941
1875	0.971
1876	0.904
1877	1.277
1878	1.332
1879	1.114
1880	0.981
1881	0.821
1882	1.284
1883	0.803
1884	0.885
1885	0.796
1886	0.813
1887	0.804
1888	1.108
1889	1.345
1890	1.148
1891	0.965
1892	1.201
1893	1.465
1894	0.986
1895	1.428
1896	0.869
1897	1.012
1898	0.89
1899	0.817
1900	0.96
1901	1.022
1902	0.971
1903	0.801
1904	0.86
1905	0.875
1906	0.985
1907	0.808
1908	1.069
1909	0.828
1910	1.001
1911	0.671
1912	0.654
1913	0.857
1914	0.747
1915	0.682
1916	0.695
1917	0.594
1918	0.825
1919	0.603
1920	0.754
1921	0.657
1922	0.512
1923	0.923
1924	0.96
1925	0.506
1926	0.616
1927	0.871
1928	0.866
1929	0.935
1930	0.832
1931	1.347
1932	0.865
1933	0.749
1934	0.696
1935	0.993
1936	1.131
1937	1.268
1938	0.831
1939	0.932
1940	1.137
1941	1.231
1942	1.337
1943	0.78
1944	1.001
1945	1.067
1946	0.963
1947	0.812
1948	0.875
1949	1.179
1950	1.415
1951	1.264
1952	1.16
1953	1.319
1954	0.991
1955	1.594
1956	0.748
1957	0.94
1958	1.059
1959	1.328
1960	1.008
1961	1.535
1962	1.198
1963	1.224
1964	0.665
1965	0.799
1966	0.871
1967	0.956
1968	1.122
1969	1.233
1970	1.292
1971	1.328
1972	0.576
1973	1.14
1974	0.893
1975	1.151
1976	1.137
1977	1.358
1978	0.841
1979	0.789
1980	0.431
1981	0.778
1982	0.975