# australia_newz020 - Waimanoa Ecological Reserve - 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/3146
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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_newz020 - Waimanoa Ecological Reserve - Breitenmoser Tree Ring Chronology Data
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# 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: Waimanoa Ecological Reserve
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -38.57
#	Southernmost_Latitude: -38.57
#	Easternmost_Longitude: 175.7
#	Westernmost_Longitude: 175.7
#	Elevation: 518 m
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# Data_Collection
#	Collection_Name: australia_newz020B
#	Earliest_Year: 1749
#	Most_Recent_Year: 1976
#	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":"4.62755704306","T2":"12.6821046544","M1":"0.0225149182236","M2":"0.580508676327"}}
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# Species
#	Species_Name: toatoa celery pine celery pine
#	Species_Code: PHGL
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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
1749	0.844
1750	0.622
1751	0.811
1752	0.701
1753	0.855
1754	0.589
1755	0.836
1756	0.696
1757	0.954
1758	0.875
1759	0.996
1760	0.713
1761	0.97
1762	0.779
1763	0.972
1764	0.849
1765	0.94
1766	1.174
1767	0.742
1768	1.19
1769	0.911
1770	1.001
1771	1.08
1772	1.181
1773	0.841
1774	1.206
1775	1.08
1776	0.678
1777	1.331
1778	0.9
1779	1.319
1780	0.941
1781	0.945
1782	1.273
1783	1.017
1784	0.567
1785	1.252
1786	1.04
1787	0.946
1788	1.213
1789	1.249
1790	0.681
1791	1.129
1792	1.041
1793	1.079
1794	0.639
1795	1.157
1796	0.64
1797	1.206
1798	1.013
1799	0.826
1800	1.071
1801	0.822
1802	1.018
1803	1.195
1804	0.836
1805	1.197
1806	0.956
1807	1.337
1808	0.563
1809	1.004
1810	0.987
1811	0.658
1812	1.239
1813	1.076
1814	0.806
1815	1.172
1816	1.069
1817	0.512
1818	1.064
1819	0.708
1820	1.239
1821	0.928
1822	1.273
1823	0.871
1824	1.398
1825	0.988
1826	1.078
1827	1.079
1828	1.06
1829	1.205
1830	0.491
1831	0.899
1832	0.813
1833	1.102
1834	0.388
1835	0.815
1836	1.012
1837	0.712
1838	0.82
1839	0.913
1840	0.46
1841	1.14
1842	1.024
1843	1.13
1844	0.551
1845	1.27
1846	0.875
1847	0.472
1848	0.925
1849	0.56
1850	0.941
1851	0.654
1852	1.066
1853	1.029
1854	0.633
1855	0.987
1856	0.789
1857	1.2
1858	1.135
1859	0.522
1860	0.948
1861	0.699
1862	1.186
1863	0.725
1864	1.148
1865	0.825
1866	1.19
1867	0.663
1868	1.074
1869	0.915
1870	0.726
1871	0.916
1872	0.763
1873	1.146
1874	0.865
1875	1.399
1876	0.988
1877	1.595
1878	1.331
1879	1.128
1880	1.708
1881	1.682
1882	1.212
1883	1.683
1884	1.912
1885	0.774
1886	1.173
1887	0.978
1888	1.563
1889	0.799
1890	1.585
1891	1.661
1892	0.662
1893	1.198
1894	1.238
1895	0.957
1896	1.242
1897	1.36
1898	1.688
1899	1.056
1900	1.303
1901	1.742
1902	0.811
1903	1.325
1904	0.671
1905	1.183
1906	1.082
1907	0.535
1908	1.018
1909	0.928
1910	0.774
1911	1.201
1912	1.27
1913	0.48
1914	0.585
1915	0.503
1916	0.39
1917	0.999
1918	1.11
1919	1.105
1920	0.536
1921	1.284
1922	1.141
1923	0.95
1924	0.906
1925	1.04
1926	1.004
1927	1.105
1928	0.725
1929	1.051
1930	0.962
1931	0.66
1932	1.1
1933	0.905
1934	1.166
1935	0.561
1936	0.996
1937	0.903
1938	0.472
1939	0.958
1940	0.929
1941	0.818
1942	1.321
1943	0.786
1944	1.098
1945	1.032
1946	0.609
1947	0.917
1948	0.559
1949	1.0
1950	0.771
1951	1.038
1952	1.205
1953	0.645
1954	1.095
1955	0.698
1956	0.99
1957	1.185
1958	1.021
1959	0.659
1960	1.118
1961	1.105
1962	0.492
1963	1.125
1964	1.132
1965	0.958
1966	0.846
1967	1.179
1968	0.524
1969	1.006
1970	0.307
1971	0.688
1972	1.024
1973	0.474
1974	0.758
1975	0.826
1976	1.189