# australia_newz077 - Putara - 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/3058
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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_newz077 - Putara - 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: Putara
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -40.67
#	Southernmost_Latitude: -40.67
#	Easternmost_Longitude: 175.52
#	Westernmost_Longitude: 175.52
#	Elevation: 650 m
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# Data_Collection
#	Collection_Name: australia_newz077B
#	Earliest_Year: 1723
#	Most_Recent_Year: 1993
#	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":"5.16615316053","T2":"17.0061052196","M1":"0.0222915755244","M2":"0.506018255025"}}
#--------------------
# Species
#	Species_Name: pink pine
#	Species_Code: HABI
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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
1723	0.851
1724	0.997
1725	1.087
1726	1.062
1727	1.1
1728	1.296
1729	1.333
1730	1.47
1731	1.52
1732	1.328
1733	1.323
1734	1.474
1735	1.412
1736	1.337
1737	1.151
1738	1.187
1739	1.289
1740	1.096
1741	1.361
1742	1.316
1743	1.3
1744	1.148
1745	0.964
1746	0.877
1747	0.857
1748	0.914
1749	0.99
1750	0.741
1751	0.934
1752	1.086
1753	1.084
1754	1.058
1755	1.095
1756	1.202
1757	1.184
1758	1.084
1759	1.094
1760	1.001
1761	1.105
1762	1.12
1763	0.999
1764	0.932
1765	0.98
1766	1.103
1767	1.196
1768	0.947
1769	1.042
1770	0.977
1771	1.139
1772	1.234
1773	1.231
1774	1.353
1775	1.278
1776	1.358
1777	1.31
1778	1.414
1779	1.327
1780	1.444
1781	1.547
1782	1.367
1783	1.475
1784	1.398
1785	1.265
1786	1.399
1787	1.057
1788	0.961
1789	1.153
1790	1.073
1791	1.006
1792	0.974
1793	1.071
1794	1.232
1795	1.141
1796	1.148
1797	1.227
1798	1.045
1799	1.031
1800	1.192
1801	0.891
1802	1.077
1803	1.069
1804	0.999
1805	1.023
1806	0.959
1807	0.893
1808	0.987
1809	1.045
1810	0.967
1811	0.955
1812	0.974
1813	0.772
1814	0.885
1815	0.817
1816	0.794
1817	0.774
1818	0.808
1819	0.905
1820	0.907
1821	1.054
1822	0.975
1823	0.932
1824	0.967
1825	0.941
1826	0.733
1827	0.893
1828	0.909
1829	0.911
1830	1.025
1831	1.164
1832	0.956
1833	0.87
1834	0.664
1835	0.758
1836	0.865
1837	0.887
1838	0.864
1839	0.818
1840	0.8
1841	0.962
1842	0.789
1843	0.838
1844	0.758
1845	0.766
1846	0.68
1847	0.653
1848	0.782
1849	0.783
1850	0.89
1851	0.871
1852	0.829
1853	0.848
1854	0.773
1855	0.7
1856	0.707
1857	0.731
1858	0.749
1859	0.804
1860	0.76
1861	0.89
1862	1.022
1863	0.926
1864	1.03
1865	0.976
1866	1.156
1867	1.011
1868	0.936
1869	0.928
1870	0.886
1871	0.695
1872	0.64
1873	0.748
1874	0.798
1875	0.826
1876	0.952
1877	0.897
1878	0.686
1879	0.64
1880	0.637
1881	0.736
1882	0.773
1883	0.707
1884	0.766
1885	0.787
1886	0.564
1887	0.561
1888	0.625
1889	0.801
1890	0.963
1891	1.291
1892	1.212
1893	1.186
1894	1.145
1895	1.014
1896	0.834
1897	0.845
1898	0.858
1899	0.898
1900	0.865
1901	1.023
1902	0.786
1903	0.83
1904	0.7
1905	0.538
1906	0.711
1907	0.654
1908	0.801
1909	0.896
1910	1.14
1911	0.881
1912	0.782
1913	0.815
1914	0.77
1915	0.966
1916	1.05
1917	1.071
1918	0.95
1919	1.028
1920	0.977
1921	0.999
1922	0.99
1923	1.297
1924	1.129
1925	1.062
1926	0.86
1927	0.641
1928	0.714
1929	0.757
1930	0.654
1931	0.768
1932	0.865
1933	0.984
1934	1.016
1935	1.007
1936	0.973
1937	1.064
1938	0.926
1939	0.886
1940	1.085
1941	0.949
1942	0.964
1943	1.068
1944	1.028
1945	1.023
1946	0.793
1947	1.042
1948	1.036
1949	1.207
1950	1.328
1951	1.26
1952	1.283
1953	1.319
1954	1.443
1955	1.454
1956	1.466
1957	1.285
1958	1.429
1959	1.379
1960	1.386
1961	1.539
1962	1.387
1963	1.229
1964	1.228
1965	1.275
1966	1.29
1967	1.502
1968	1.171
1969	1.374
1970	1.295
1971	1.193
1972	1.155
1973	1.112
1974	0.941
1975	0.908
1976	0.864
1977	0.847
1978	0.915
1979	0.794
1980	0.977
1981	0.92
1982	0.912
1983	0.932
1984	0.92
1985	0.973
1986	0.862
1987	0.862
1988	0.962
1989	1.001
1990	0.939
1991	0.738
1992	0.715
1993	0.73