# australia_newz021 - Waiomu - 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.
#
#
# 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/3147
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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_newz021 - Waiomu - 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: Waiomu
#	Location:
#	Country: New Zealand
#	Northernmost_Latitude: -37.03
#	Southernmost_Latitude: -37.03
#	Easternmost_Longitude: 175.53
#	Westernmost_Longitude: 175.53
#	Elevation: 61 m
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# Data_Collection
#	Collection_Name: australia_newz021B
#	Earliest_Year: 1701
#	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":"4.55818605281","T2":"11.7899262175","M1":"0.022568823217","M2":"0.493114743853"}}
#--------------------
# Species
#	Species_Name: tanekaha celery top pine
#	Species_Code: PHTR
#--------------------
# 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
1701	0.478
1702	0.445
1703	0.548
1704	0.495
1705	0.388
1706	0.653
1707	0.447
1708	0.625
1709	0.399
1710	0.491
1711	0.41
1712	0.646
1713	0.496
1714	0.695
1715	0.386
1716	0.822
1717	0.5
1718	0.708
1719	0.578
1720	0.713
1721	0.434
1722	0.556
1723	0.558
1724	0.403
1725	0.614
1726	0.677
1727	0.638
1728	0.669
1729	0.626
1730	0.707
1731	0.649
1732	0.915
1733	1.011
1734	0.608
1735	0.519
1736	0.951
1737	0.858
1738	0.798
1739	0.627
1740	0.916
1741	0.698
1742	0.974
1743	0.771
1744	1.047
1745	1.002
1746	1.201
1747	0.956
1748	0.783
1749	0.813
1750	0.771
1751	0.851
1752	0.812
1753	0.918
1754	1.132
1755	1.288
1756	1.125
1757	1.517
1758	1.248
1759	1.107
1760	0.963
1761	1.27
1762	1.071
1763	1.163
1764	1.059
1765	1.059
1766	1.021
1767	1.044
1768	1.306
1769	1.193
1770	1.099
1771	0.96
1772	1.158
1773	0.932
1774	1.209
1775	1.119
1776	1.06
1777	1.433
1778	1.029
1779	1.413
1780	1.151
1781	1.333
1782	1.394
1783	1.264
1784	1.352
1785	1.351
1786	1.359
1787	1.293
1788	1.678
1789	1.337
1790	1.166
1791	1.56
1792	1.318
1793	1.602
1794	1.228
1795	1.58
1796	1.148
1797	1.498
1798	1.361
1799	1.596
1800	1.081
1801	1.27
1802	0.778
1803	1.41
1804	1.094
1805	1.214
1806	1.351
1807	1.034
1808	1.001
1809	1.075
1810	1.053
1811	0.954
1812	1.237
1813	0.947
1814	1.22
1815	1.11
1816	1.279
1817	1.039
1818	1.125
1819	0.736
1820	1.043
1821	0.826
1822	1.18
1823	0.984
1824	0.727
1825	0.902
1826	0.769
1827	1.001
1828	0.673
1829	1.267
1830	0.838
1831	1.253
1832	0.805
1833	1.248
1834	0.724
1835	1.118
1836	1.018
1837	1.199
1838	0.835
1839	0.999
1840	0.663
1841	1.075
1842	0.912
1843	1.268
1844	0.833
1845	1.162
1846	0.577
1847	0.523
1848	0.885
1849	0.554
1850	1.015
1851	0.882
1852	1.35
1853	1.029
1854	1.042
1855	1.205
1856	0.972
1857	1.077
1858	1.016
1859	0.664
1860	0.928
1861	0.838
1862	0.954
1863	0.824
1864	1.228
1865	0.743
1866	1.21
1867	0.679
1868	1.01
1869	0.893
1870	0.989
1871	0.83
1872	0.505
1873	0.841
1874	0.79
1875	1.065
1876	0.819
1877	1.245
1878	0.575
1879	1.23
1880	0.946
1881	1.283
1882	0.737
1883	1.264
1884	1.354
1885	0.895
1886	1.039
1887	0.959
1888	1.196
1889	0.823
1890	1.027
1891	0.973
1892	1.497
1893	1.179
1894	1.545
1895	1.213
1896	1.241
1897	1.042
1898	1.246
1899	1.088
1900	0.593
1901	1.293
1902	0.715
1903	0.979
1904	0.529
1905	1.075
1906	0.788
1907	0.869
1908	0.69
1909	0.827
1910	0.337
1911	0.825
1912	0.752
1913	0.497
1914	0.554
1915	0.514
1916	0.693
1917	0.695
1918	1.274
1919	1.272
1920	0.896
1921	1.111
1922	0.627
1923	0.983
1924	0.364
1925	1.052
1926	0.803
1927	1.044
1928	0.552
1929	0.677
1930	0.7
1931	0.69
1932	0.712
1933	0.733
1934	0.873
1935	0.552
1936	0.806
1937	0.782
1938	0.763
1939	1.14
1940	1.14
1941	1.015
1942	0.929
1943	0.995
1944	0.923
1945	0.991
1946	0.86
1947	1.062
1948	0.652
1949	0.931
1950	0.456
1951	0.896
1952	0.515
1953	0.945
1954	0.559
1955	0.6
1956	0.958
1957	0.98
1958	0.934
1959	1.185
1960	1.26
1961	1.161
1962	0.996
1963	1.419
1964	1.348
1965	1.516
1966	1.527
1967	1.273
1968	1.282
1969	1.208
1970	0.547
1971	0.706
1972	0.911
1973	0.612
1974	0.829
1975	1.267
1976	1.349