ÃÂ¯ÃÂ»ÃÂ¿# northamerica_usa_az135 - Hualapai Mountains - 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/3470
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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_az135 - Hualapai Mountains - 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: Hualapai Mountains
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.08
#	Southernmost_Latitude: 35.08
#	Easternmost_Longitude: -113.9
#	Westernmost_Longitude: -113.9
#	Elevation: 2316 m
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# Data_Collection
#	Collection_Name: northamerica_usa_az135B
#	Earliest_Year: 1569
#	Most_Recent_Year: 1971
#	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":"4.93396627445","T2":"16.3288178972","M1":"0.0222998077512","M2":"0.373692157674"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
#--------------------
# 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
1569	0.789
1570	0.818
1571	0.76
1572	0.454
1573	0.855
1574	0.755
1575	1.249
1576	1.298
1577	1.234
1578	1.167
1579	0.775
1580	0.849
1581	1.153
1582	1.127
1583	0.985
1584	0.383
1585	0.439
1586	1.406
1587	0.99
1588	0.78
1589	0.831
1590	0.693
1591	1.034
1592	1.091
1593	1.604
1594	1.257
1595	1.442
1596	1.421
1597	0.924
1598	1.302
1599	0.967
1600	0.627
1601	0.645
1602	1.096
1603	1.082
1604	1.497
1605	1.762
1606	1.157
1607	1.349
1608	1.196
1609	1.199
1610	1.241
1611	0.789
1612	0.691
1613	0.451
1614	1.21
1615	1.057
1616	1.113
1617	1.308
1618	1.39
1619	1.011
1620	1.283
1621	1.46
1622	0.861
1623	0.548
1624	0.687
1625	1.129
1626	0.815
1627	0.936
1628	0.914
1629	0.944
1630	0.872
1631	0.791
1632	0.481
1633	0.738
1634	0.997
1635	0.996
1636	1.091
1637	0.695
1638	1.064
1639	0.896
1640	1.052
1641	0.901
1642	1.048
1643	0.412
1644	0.868
1645	0.9
1646	1.011
1647	1.008
1648	0.493
1649	1.257
1650	1.046
1651	1.27
1652	0.425
1653	0.674
1654	0.326
1655	1.087
1656	1.106
1657	1.245
1658	0.963
1659	1.136
1660	1.131
1661	1.24
1662	1.335
1663	1.139
1664	1.289
1665	0.245
1666	1.138
1667	0.563
1668	0.554
1669	0.719
1670	0.109
1671	0.936
1672	1.287
1673	1.221
1674	1.128
1675	0.856
1676	0.472
1677	0.914
1678	0.565
1679	1.176
1680	1.336
1681	1.489
1682	1.121
1683	1.028
1684	0.869
1685	0.661
1686	0.374
1687	1.062
1688	1.034
1689	1.269
1690	0.92
1691	1.276
1692	1.21
1693	0.86
1694	1.181
1695	1.028
1696	0.933
1697	1.092
1698	0.893
1699	1.437
1700	1.671
1701	2.055
1702	1.099
1703	0.603
1704	1.248
1705	1.645
1706	1.392
1707	0.605
1708	0.836
1709	0.727
1710	1.348
1711	0.89
1712	0.918
1713	1.332
1714	0.795
1715	0.745
1716	0.945
1717	0.906
1718	1.701
1719	1.201
1720	1.326
1721	0.734
1722	0.331
1723	1.521
1724	1.31
1725	1.233
1726	1.922
1727	1.059
1728	0.946
1729	0.942
1730	1.047
1731	0.859
1732	0.788
1733	0.421
1734	1.243
1735	0.027
1736	0.982
1737	0.722
1738	1.184
1739	0.489
1740	0.792
1741	0.985
1742	0.472
1743	1.125
1744	0.817
1745	0.861
1746	1.217
1747	1.059
1748	0.306
1749	1.224
1750	0.982
1751	0.726
1752	0.304
1753	1.021
1754	0.907
1755	0.769
1756	1.016
1757	1.26
1758	1.622
1759	0.993
1760	1.077
1761	1.215
1762	1.426
1763	0.524
1764	1.666
1765	0.679
1766	1.38
1767	1.149
1768	1.035
1769	1.279
1770	0.912
1771	1.655
1772	0.987
1773	0.497
1774	0.656
1775	1.222
1776	0.939
1777	0.729
1778	0.817
1779	1.072
1780	0.785
1781	0.877
1782	0.578
1783	1.318
1784	1.605
1785	1.092
1786	1.302
1787	1.43
1788	0.444
1789	1.204
1790	0.254
1791	1.719
1792	1.074
1793	1.335
1794	0.971
1795	1.56
1796	1.053
1797	1.005
1798	0.879
1799	1.157
1800	0.473
1801	0.479
1802	1.207
1803	0.288
1804	1.289
1805	0.427
1806	0.968
1807	0.992
1808	0.943
1809	0.785
1810	0.562
1811	0.851
1812	1.053
1813	0.604
1814	0.619
1815	0.675
1816	0.779
1817	0.804
1818	0.677
1819	0.546
1820	0.289
1821	0.826
1822	0.215
1823	0.208
1824	0.826
1825	0.767
1826	1.047
1827	0.793
1828	1.267
1829	0.121
1830	0.881
1831	1.167
1832	1.362
1833	1.494
1834	1.054
1835	1.224
1836	1.028
1837	0.981
1838	1.25
1839	1.219
1840	1.066
1841	0.501
1842	0.708
1843	1.127
1844	1.04
1845	0.277
1846	1.07
1847	0.13
1848	1.154
1849	1.277
1850	1.439
1851	0.956
1852	1.222
1853	1.186
1854	1.124
1855	0.997
1856	0.821
1857	0.048
1858	1.439
1859	0.136
1860	1.027
1861	0.811
1862	0.914
1863	0.502
1864	0.601
1865	0.801
1866	1.203
1867	0.788
1868	1.667
1869	1.237
1870	1.067
1871	1.035
1872	0.625
1873	0.685
1874	1.096
1875	0.856
1876	0.77
1877	1.021
1878	1.037
1879	-0.009
1880	0.276
1881	0.729
1882	0.714
1883	0.718
1884	0.757
1885	0.849
1886	0.566
1887	0.751
1888	0.75
1889	0.776
1890	0.85
1891	0.917
1892	0.843
1893	0.565
1894	0.831
1895	0.891
1896	0.176
1897	1.045
1898	0.851
1899	0.223
1900	0.751
1901	0.777
1902	0.393
1903	0.852
1904	0.278
1905	1.259
1906	1.328
1907	1.758
1908	1.882
1909	1.693
1910	1.408
1911	1.821
1912	1.821
1913	1.476
1914	2.075
1915	1.739
1916	1.399
1917	1.483
1918	1.129
1919	1.606
1920	1.621
1921	2.128
1922	2.114
1923	2.045
1924	1.688
1925	2.108
1926	1.991
1927	1.233
1928	1.118
1929	0.346
1930	1.838
1931	1.324
1932	1.453
1933	0.766
1934	0.092
1935	1.471
1936	0.906
1937	1.393
1938	0.94
1939	1.139
1940	1.294
1941	0.907
1942	1.147
1943	1
1944	1.133
1945	0.867
1946	0.691
1947	0.888
1948	0.763
1949	1.011
1950	0.766
1951	0.912
1952	1.137
1953	0.775
1954	1.28
1955	0.654
1956	0.166
1957	0.933
1958	1.028
1959	0.606
1960	0.953
1961	0.811
1962	0.866
1963	0.477
1964	0.792
1965	0.56
1966	0.726
1967	0.824
1968	0.779
1969	0.983
1970	0.673
1971	0.48