# northamerica_usa_az109 - Hualapai Peak - 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/5020
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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_az109 - Hualapai Peak - 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 Peak
#	Location:
#	Country: United States
#	Northernmost_Latitude: 35.0
#	Southernmost_Latitude: 35.0
#	Easternmost_Longitude: -113.0
#	Westernmost_Longitude: -113.0
#	Elevation: 1900 m
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# Data_Collection
#	Collection_Name: northamerica_usa_az109B
#	Earliest_Year: 1769
#	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":"4.92379332658","T2":"17.5121186085","M1":"0.0228707240341","M2":"0.383061204402"}}
#--------------------
# Species
#	Species_Name: Douglas fir
#	Species_Code: PSME
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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)
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##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
1769	1.545
1770	0.912
1771	1.152
1772	1.016
1773	0.355
1774	0.527
1775	0.834
1776	0.706
1777	0.391
1778	0.612
1779	0.948
1780	0.472
1781	0.803
1782	0.531
1783	1.465
1784	1.581
1785	1.103
1786	1.466
1787	1.682
1788	0.378
1789	0.947
1790	0.421
1791	1.419
1792	1.31
1793	1.513
1794	1.121
1795	1.704
1796	0.995
1797	0.728
1798	0.647
1799	1.077
1800	0.548
1801	0.574
1802	0.936
1803	0.493
1804	0.967
1805	0.534
1806	0.941
1807	0.693
1808	0.879
1809	0.673
1810	0.556
1811	1.191
1812	1.038
1813	0.48
1814	0.839
1815	0.767
1816	0.854
1817	1.082
1818	0.764
1819	1.208
1820	0.551
1821	1.493
1822	0.515
1823	0.528
1824	0.827
1825	0.807
1826	0.842
1827	0.647
1828	0.933
1829	0.129
1830	0.696
1831	1.692
1832	1.515
1833	1.416
1834	1.133
1835	1.403
1836	0.779
1837	0.822
1838	1.149
1839	1.24
1840	1.126
1841	0.614
1842	0.832
1843	1.364
1844	1.042
1845	0.481
1846	1.622
1847	0.353
1848	1.4
1849	1.322
1850	1.793
1851	1.012
1852	1.368
1853	1.365
1854	1.356
1855	1.4
1856	0.971
1857	0.255
1858	1.496
1859	0.523
1860	0.827
1861	0.712
1862	0.933
1863	0.528
1864	0.562
1865	0.829
1866	1.37
1867	1.058
1868	1.722
1869	1.646
1870	0.948
1871	0.998
1872	0.693
1873	0.643
1874	0.9
1875	0.783
1876	0.66
1877	0.77
1878	0.941
1879	0.196
1880	0.451
1881	0.803
1882	0.964
1883	0.788
1884	0.894
1885	0.943
1886	0.754
1887	0.755
1888	0.969
1889	1.137
1890	1.065
1891	1.565
1892	1.343
1893	0.839
1894	1.18
1895	1.298
1896	0.608
1897	1.118
1898	0.991
1899	0.601
1900	0.801
1901	0.879
1902	0.411
1903	0.801
1904	0.592
1905	1.249
1906	1.326
1907	1.478
1908	1.493
1909	1.575
1910	1.206
1911	1.549
1912	1.452
1913	1.105
1914	1.835
1915	1.598
1916	1.353
1917	1.357
1918	1.136
1919	1.841
1920	1.791
1921	1.736
1922	1.65
1923	1.116
1924	1.026
1925	1.254
1926	1.104
1927	0.728
1928	0.704
1929	0.247
1930	1.189
1931	1.022
1932	1.019
1933	0.647
1934	0.238
1935	1.02
1936	0.797
1937	1.082
1938	0.74
1939	0.869
1940	0.942
1941	0.886
1942	0.937
1943	0.782
1944	0.843
1945	0.702
1946	0.734
1947	0.763
1948	0.699
1949	0.844
1950	0.673
1951	0.841
1952	0.995
1953	0.829
1954	1.184
1955	0.535
1956	0.21
1957	0.505
1958	0.779
1959	0.467
1960	0.743
1961	0.566
1962	0.74
1963	0.575
1964	0.873
1965	1.14
1966	1.136
1967	1.295
1968	1.168
1969	0.932
1970	0.724
1971	0.64