# australia_ausl012 - Coolangatta Road - Breitenmoser Tree Ring Chronology Data
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#		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/3827
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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: australia_ausl012 - Coolangatta Road - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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: Coolangatta Road
#	Location:
#	Country: Australia
#	Northernmost_Latitude: -43.37
#	Southernmost_Latitude: -43.37
#	Easternmost_Longitude: 147.27
#	Westernmost_Longitude: 147.27
#	Elevation: 450 m
#--------------------
# Data_Collection
#	Collection_Name: australia_ausl012B
#	Earliest_Year: 1726
#	Most_Recent_Year: 1975
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"4.69408941399","T2":"14.1776421403","M1":"0.0226324966017","M2":"0.487089289913"}}
#--------------------
# Species
#	Species_Name: celery top pine
#	Species_Code: PHAS
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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
1726	0.843
1727	0.697
1728	0.586
1729	0.688
1730	0.604
1731	0.891
1732	0.684
1733	0.829
1734	0.922
1735	0.622
1736	0.667
1737	0.872
1738	0.735
1739	1.03
1740	0.701
1741	0.837
1742	0.859
1743	0.999
1744	0.83
1745	0.791
1746	1.152
1747	0.833
1748	1.026
1749	0.708
1750	1.015
1751	0.901
1752	0.833
1753	1.183
1754	0.898
1755	1.178
1756	0.976
1757	1.084
1758	0.913
1759	0.91
1760	0.826
1761	1.027
1762	0.721
1763	1.013
1764	0.928
1765	0.959
1766	0.973
1767	0.903
1768	1.021
1769	0.902
1770	1.048
1771	0.939
1772	1.1
1773	1.188
1774	1.027
1775	1.148
1776	0.592
1777	0.686
1778	1.283
1779	0.969
1780	1.272
1781	1.04
1782	1.125
1783	0.982
1784	0.853
1785	0.583
1786	0.777
1787	0.759
1788	0.784
1789	0.883
1790	0.825
1791	1.149
1792	1.21
1793	1.028
1794	1.152
1795	0.988
1796	1.139
1797	1.283
1798	1.225
1799	1.144
1800	1.447
1801	0.968
1802	1.289
1803	0.981
1804	1.264
1805	1.01
1806	1.096
1807	1.05
1808	0.62
1809	1.164
1810	1.208
1811	0.998
1812	1.228
1813	1.205
1814	0.741
1815	1.376
1816	0.792
1817	1.473
1818	1.508
1819	1.273
1820	1.461
1821	1.14
1822	1.493
1823	1.096
1824	1.261
1825	0.97
1826	1.211
1827	0.816
1828	0.922
1829	0.95
1830	1.06
1831	1.167
1832	0.682
1833	1.074
1834	0.795
1835	1.096
1836	1.003
1837	1.07
1838	0.834
1839	1.255
1840	0.72
1841	1.152
1842	1.174
1843	0.669
1844	1.077
1845	0.685
1846	1.068
1847	0.761
1848	0.905
1849	1.005
1850	0.751
1851	0.922
1852	0.747
1853	0.813
1854	0.607
1855	1.099
1856	0.902
1857	1.104
1858	0.794
1859	1.046
1860	0.606
1861	1.067
1862	1.35
1863	0.963
1864	1.404
1865	0.995
1866	0.98
1867	1.311
1868	1.362
1869	0.879
1870	1.452
1871	1.28
1872	0.863
1873	1.147
1874	1.305
1875	1.08
1876	1.279
1877	1.355
1878	0.997
1879	1.304
1880	0.559
1881	1.278
1882	0.672
1883	1.386
1884	1.308
1885	0.807
1886	0.897
1887	0.543
1888	1.086
1889	0.469
1890	1.071
1891	1.225
1892	0.881
1893	1.494
1894	1.191
1895	1.394
1896	1.24
1897	0.601
1898	0.434
1899	0.909
1900	1.193
1901	1.736
1902	1.62
1903	0.844
1904	1.139
1905	1.073
1906	1.173
1907	1.514
1908	0.545
1909	1.031
1910	0.212
1911	1.202
1912	0.838
1913	1.183
1914	0.411
1915	0.944
1916	1.232
1917	0.944
1918	1.534
1919	1.179
1920	0.842
1921	1.138
1922	1.575
1923	1.829
1924	1.127
1925	1.402
1926	0.717
1927	1.148
1928	0.735
1929	1.173
1930	1.066
1931	1.139
1932	1.271
1933	1.143
1934	0.328
1935	0.632
1936	0.581
1937	1.153
1938	0.451
1939	0.852
1940	0.895
1941	0.869
1942	0.982
1943	0.671
1944	0.884
1945	0.703
1946	0.231
1947	0.72
1948	0.728
1949	0.641
1950	0.706
1951	0.475
1952	0.812
1953	0.661
1954	0.88
1955	0.628
1956	0.638
1957	1.42
1958	0.972
1959	0.844
1960	0.651
1961	0.741
1962	1.123
1963	0.84
1964	0.659
1965	0.986
1966	0.25
1967	0.354
1968	0.929
1969	0.809
1970	1.013
1971	0.915
1972	0.98
1973	0.529
1974	0.767
1975	0.927