# northamerica_usa_az143 - Hualapai Laguna Tank - 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/5019
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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_az143 - Hualapai Laguna Tank - 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 Laguna Tank
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.95
#	Southernmost_Latitude: 35.95
#	Easternmost_Longitude: -113.08
#	Westernmost_Longitude: -113.08
#	Elevation: 2085 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_az143B
#	Earliest_Year: 1680
#	Most_Recent_Year: 1972
#	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":"3.66165397449","T2":"16.1262443854","M1":"0.0239607445757","M2":"0.447808433056"}}
#--------------------
# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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# Chronology:
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#
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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
1680	1.009
1681	1.401
1682	1.058
1683	1.231
1684	0.544
1685	0.48
1686	0.217
1687	0.799
1688	1.123
1689	1.129
1690	1.121
1691	0.763
1692	1.167
1693	1.141
1694	0.983
1695	1.423
1696	1.291
1697	1.341
1698	0.882
1699	1.878
1700	1.253
1701	1.543
1702	1.014
1703	0.385
1704	0.92
1705	1.554
1706	1.216
1707	0.219
1708	0.409
1709	0.766
1710	1.637
1711	1.605
1712	1.568
1713	1.326
1714	1.059
1715	0.989
1716	0.391
1717	1.209
1718	1.813
1719	1.773
1720	2.146
1721	1.371
1722	0.397
1723	1.329
1724	1.037
1725	1.169
1726	1.543
1727	1.207
1728	1.005
1729	0.515
1730	1.265
1731	0.991
1732	1.236
1733	0.56
1734	1.153
1735	0.057
1736	0.543
1737	0.818
1738	1.204
1739	0.416
1740	0.791
1741	1.027
1742	0.595
1743	1.015
1744	0.931
1745	1.231
1746	1.964
1747	1.657
1748	0.662
1749	1.429
1750	0.611
1751	0.452
1752	0.12
1753	0.335
1754	0.308
1755	0.12
1756	0.332
1757	0.501
1758	1.009
1759	0.87
1760	1.222
1761	0.77
1762	0.781
1763	0.591
1764	1.135
1765	1.0
1766	1.732
1767	2.064
1768	1.942
1769	0.854
1770	1.158
1771	1.686
1772	1.125
1773	0.199
1774	0.763
1775	1.307
1776	0.881
1777	0.72
1778	0.577
1779	1.23
1780	1.157
1781	1.176
1782	0.224
1783	1.246
1784	1.986
1785	0.539
1786	1.059
1787	1.827
1788	0.601
1789	1.054
1790	0.567
1791	1.339
1792	1.784
1793	1.926
1794	1.067
1795	1.528
1796	1.039
1797	0.954
1798	0.601
1799	1.256
1800	0.148
1801	0.509
1802	1.084
1803	0.358
1804	0.892
1805	0.046
1806	0.297
1807	0.393
1808	0.695
1809	0.72
1810	0.338
1811	0.159
1812	0.509
1813	0.561
1814	0.076
1815	0.319
1816	0.746
1817	0.624
1818	0.472
1819	1.201
1820	0.465
1821	1.371
1822	0.349
1823	0.505
1824	1.073
1825	0.952
1826	1.77
1827	1.603
1828	2.703
1829	1.543
1830	1.392
1831	1.348
1832	1.544
1833	2.139
1834	1.203
1835	1.405
1836	0.947
1837	1.207
1838	2.035
1839	2.171
1840	2.027
1841	0.777
1842	0.666
1843	1.259
1844	1.761
1845	0.529
1846	0.623
1847	0.277
1848	1.18
1849	1.499
1850	1.823
1851	0.577
1852	1.298
1853	1.078
1854	1.328
1855	1.068
1856	0.511
1857	0.176
1858	0.77
1859	0.213
1860	0.022
1861	0.002
1862	0.583
1863	0.734
1864	0.603
1865	0.664
1866	0.823
1867	2.111
1868	1.813
1869	2.273
1870	2.222
1871	1.292
1872	1.145
1873	0.707
1874	0.661
1875	1.505
1876	0.794
1877	0.774
1878	0.407
1879	0.513
1880	0.21
1881	0.243
1882	0.085
1883	0.243
1884	0.732
1885	1.125
1886	1.047
1887	0.743
1888	1.245
1889	1.372
1890	1.708
1891	1.546
1892	1.042
1893	1.156
1894	0.51
1895	0.947
1896	0.149
1897	0.941
1898	0.666
1899	0.045
1900	0.239
1901	0.377
1902	0.01
1903	0.702
1904	0.043
1905	1.034
1906	1.016
1907	1.502
1908	1.723
1909	2.36
1910	1.637
1911	1.419
1912	1.627
1913	1.403
1914	1.642
1915	1.726
1916	2.136
1917	1.848
1918	1.098
1919	1.843
1920	1.881
1921	1.102
1922	1.833
1923	1.31
1924	0.774
1925	0.995
1926	0.895
1927	1.007
1928	0.848
1929	0.599
1930	0.707
1931	0.812
1932	1.258
1933	0.836
1934	0.357
1935	0.881
1936	0.75
1937	0.962
1938	1.062
1939	1.136
1940	1.035
1941	1.836
1942	1.617
1943	1.421
1944	0.806
1945	1.238
1946	0.634
1947	0.52
1948	0.747
1949	0.813
1950	0.699
1951	0.209
1952	1.102
1953	0.646
1954	0.751
1955	0.921
1956	-0.005
1957	0.614
1958	0.936
1959	0.464
1960	0.779
1961	0.703
1962	0.931
1963	0.333
1964	0.995
1965	0.735
1966	0.959
1967	1.16
1968	1.016
1969	1.614
1970	1.321
1971	1.099
1972	0.578