# northamerica_usa_az523 - Grasshopper Recollection - 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/3359
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# Description/Documentation lines begin with #
# Data lines have no #
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# Archive: Tree Rings
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# Contribution_Date
#	Date: 2016-01-07
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# Title
#	Study_Name: northamerica_usa_az523 - Grasshopper Recollection - 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: Grasshopper Recollection
#	Location:
#	Country: United States
#	Northernmost_Latitude: 34.07
#	Southernmost_Latitude: 34.07
#	Easternmost_Longitude: -110.62
#	Westernmost_Longitude: -110.62
#	Elevation: 1798 m
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# Data_Collection
#	Collection_Name: northamerica_usa_az523B
#	Earliest_Year: 1746
#	Most_Recent_Year: 1985
#	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":"3.52023504635","T2":"14.8812132889","M1":"0.0233720552296","M2":"0.507977708571"}}
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# Species
#	Species_Name: ponderosa pine
#	Species_Code: PIPO
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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
1746	1.613
1747	1.596
1748	0.533
1749	1.539
1750	1.622
1751	0.974
1752	0.217
1753	0.67
1754	0.923
1755	0.808
1756	0.625
1757	0.595
1758	0.911
1759	0.909
1760	0.925
1761	0.501
1762	1.13
1763	0.588
1764	1.509
1765	0.796
1766	1.598
1767	1.02
1768	1.472
1769	1.177
1770	1.177
1771	1.303
1772	1.28
1773	0.437
1774	0.977
1775	1.174
1776	1.461
1777	0.982
1778	0.489
1779	0.99
1780	0.462
1781	0.532
1782	0.205
1783	0.975
1784	1.491
1785	0.495
1786	1.062
1787	1.356
1788	0.462
1789	1.166
1790	0.851
1791	1.216
1792	1.664
1793	1.952
1794	1.009
1795	1.545
1796	1.236
1797	0.643
1798	0.907
1799	1.011
1800	0.643
1801	0.386
1802	0.816
1803	0.247
1804	0.787
1805	0.6
1806	0.75
1807	0.934
1808	1.295
1809	1.261
1810	1.145
1811	1.277
1812	1.165
1813	0.875
1814	1.106
1815	1.335
1816	1.614
1817	1.052
1818	0.548
1819	0.374
1820	-0.022
1821	0.756
1822	0.146
1823	-0.022
1824	0.743
1825	0.961
1826	1.22
1827	0.801
1828	1.3
1829	0.676
1830	1.098
1831	1.03
1832	1.334
1833	1.311
1834	1.536
1835	1.228
1836	1.412
1837	1.01
1838	1.741
1839	1.898
1840	1.285
1841	0.361
1842	0.651
1843	0.732
1844	1.455
1845	0.333
1846	0.671
1847	-0.022
1848	0.677
1849	1.087
1850	1.262
1851	1.06
1852	1.567
1853	1.597
1854	0.893
1855	1.548
1856	1.194
1857	0.53
1858	1.248
1859	0.761
1860	1.295
1861	0.592
1862	1.34
1863	0.675
1864	-0.022
1865	1.231
1866	1.311
1867	1.402
1868	2.53
1869	1.643
1870	0.849
1871	0.235
1872	0.665
1873	0.494
1874	0.715
1875	1.151
1876	0.701
1877	0.854
1878	1.011
1879	0.718
1880	0.718
1881	0.541
1882	0.814
1883	1.036
1884	1.462
1885	1.602
1886	1.34
1887	0.454
1888	1.166
1889	1.044
1890	1.32
1891	0.961
1892	0.962
1893	0.528
1894	0.27
1895	0.69
1896	0.843
1897	0.937
1898	1.067
1899	0.818
1900	0.235
1901	0.884
1902	0.14
1903	0.659
1904	-0.022
1905	0.781
1906	1.023
1907	1.39
1908	1.725
1909	1.969
1910	1.229
1911	1.911
1912	1.858
1913	1.324
1914	1.779
1915	1.761
1916	1.389
1917	1.406
1918	1.113
1919	1.576
1920	1.611
1921	0.935
1922	1.487
1923	1.382
1924	1.25
1925	0.901
1926	1.063
1927	1.045
1928	1.055
1929	1.212
1930	1.197
1931	1.335
1932	1.339
1933	0.921
1934	0.383
1935	1.155
1936	0.694
1937	1.174
1938	0.912
1939	0.761
1940	0.742
1941	1.357
1942	0.93
1943	1.146
1944	1.127
1945	0.964
1946	0.376
1947	0.743
1948	0.49
1949	0.784
1950	0.359
1951	0.29
1952	0.843
1953	0.82
1954	0.884
1955	0.131
1956	0.372
1957	0.736
1958	0.749
1959	0.272
1960	0.946
1961	0.511
1962	0.719
1963	0.587
1964	0.343
1965	0.725
1966	0.872
1967	0.762
1968	0.924
1969	1.147
1970	0.746
1971	0.551
1972	0.945
1973	1.03
1974	0.728
1975	1.369
1976	1.721
1977	0.65
1978	0.828
1979	1.405
1980	1.466
1981	0.89
1982	1.695
1983	1.684
1984	1.03
1985	1.457