# northamerica_usa_co083 - Niwot Ridge A - 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/3462
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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_co083 - Niwot Ridge A - 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: Niwot Ridge A
#	Location:
#	Country: United States
#	Northernmost_Latitude: 40.07
#	Southernmost_Latitude: 40.07
#	Easternmost_Longitude: -105.58
#	Westernmost_Longitude: -105.58
#	Elevation: 3700 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co083B
#	Earliest_Year: 1689
#	Most_Recent_Year: 1979
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[6, 7, 8]"}}{"VSLite_parameters":{"T1":"4.25159029446","T2":"18.6996545125","M1":"0.0221993745321","M2":"0.323044603986"}}
#--------------------
# Species
#	Species_Name: Engelmann spruce
#	Species_Code: PCEN
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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)
#
##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
1689	1.353
1690	1.313
1691	0.866
1692	0.857
1693	0.883
1694	0.859
1695	0.837
1696	1.001
1697	1.111
1698	0.879
1699	1.057
1700	0.688
1701	0.787
1702	0.853
1703	0.704
1704	0.673
1705	0.879
1706	1.005
1707	1.022
1708	0.998
1709	1.066
1710	1.087
1711	0.981
1712	1.226
1713	1.135
1714	0.936
1715	0.844
1716	0.893
1717	1.418
1718	1.47
1719	1.097
1720	0.995
1721	0.9
1722	0.749
1723	0.714
1724	0.921
1725	1.082
1726	1.065
1727	0.905
1728	1.115
1729	0.875
1730	0.828
1731	0.899
1732	1.003
1733	1.05
1734	1.053
1735	0.896
1736	0.702
1737	0.755
1738	0.913
1739	1.043
1740	0.766
1741	0.759
1742	0.874
1743	0.644
1744	0.798
1745	0.862
1746	0.949
1747	1.025
1748	1.048
1749	1.122
1750	1.298
1751	0.928
1752	0.75
1753	1.011
1754	0.97
1755	1.138
1756	0.849
1757	1.063
1758	0.593
1759	0.865
1760	0.795
1761	0.72
1762	1.19
1763	0.966
1764	0.666
1765	0.882
1766	0.755
1767	1.114
1768	0.832
1769	1.028
1770	0.815
1771	1.015
1772	1.185
1773	1.323
1774	1.419
1775	1.311
1776	1.078
1777	1.044
1778	0.995
1779	0.947
1780	1.307
1781	1.175
1782	1.019
1783	1.238
1784	1.21
1785	1.267
1786	1.265
1787	0.95
1788	0.969
1789	0.76
1790	0.599
1791	0.621
1792	0.826
1793	0.769
1794	0.855
1795	0.927
1796	0.972
1797	1.052
1798	1.385
1799	1.218
1800	1.077
1801	1.207
1802	1.252
1803	1.011
1804	1.105
1805	1.001
1806	1.033
1807	1.272
1808	1.022
1809	0.881
1810	0.792
1811	0.891
1812	1.244
1813	1.078
1814	0.931
1815	1.055
1816	1.055
1817	0.96
1818	0.926
1819	0.895
1820	0.928
1821	0.904
1822	1.106
1823	1.066
1824	1.15
1825	1.078
1826	1.122
1827	1.151
1828	1.179
1829	1.656
1830	1.364
1831	1.184
1832	0.987
1833	1.324
1834	1.098
1835	0.876
1836	0.854
1837	0.963
1838	0.762
1839	0.587
1840	0.591
1841	0.842
1842	0.833
1843	0.782
1844	0.889
1845	0.565
1846	0.717
1847	0.548
1848	0.787
1849	0.758
1850	1.034
1851	0.904
1852	0.795
1853	0.759
1854	0.686
1855	0.834
1856	1.139
1857	0.848
1858	0.877
1859	1.264
1860	1.156
1861	1.181
1862	1.114
1863	1.164
1864	1.094
1865	0.795
1866	0.79
1867	0.809
1868	0.542
1869	0.667
1870	0.527
1871	0.782
1872	0.401
1873	0.798
1874	0.928
1875	0.643
1876	0.826
1877	0.625
1878	0.772
1879	0.73
1880	0.582
1881	0.984
1882	0.512
1883	0.523
1884	0.606
1885	0.734
1886	0.898
1887	0.403
1888	0.388
1889	0.452
1890	0.549
1891	0.722
1892	0.859
1893	0.77
1894	1.041
1895	0.845
1896	0.889
1897	1.213
1898	1.188
1899	0.852
1900	1.123
1901	1.159
1902	0.755
1903	0.828
1904	0.711
1905	0.895
1906	0.69
1907	0.957
1908	1.092
1909	1.115
1910	1.017
1911	0.979
1912	1.024
1913	0.817
1914	0.969
1915	0.857
1916	0.896
1917	0.827
1918	0.87
1919	0.91
1920	0.68
1921	0.748
1922	0.778
1923	0.765
1924	0.906
1925	0.781
1926	0.98
1927	0.972
1928	1.113
1929	1.245
1930	1.111
1931	1.046
1932	1.204
1933	1.184
1934	1.175
1935	1.091
1936	1.177
1937	1.206
1938	1.247
1939	1.447
1940	1.395
1941	1.149
1942	1.093
1943	1.097
1944	1.243
1945	1.197
1946	1.289
1947	1.239
1948	1.221
1949	1.275
1950	1.157
1951	1.315
1952	1.139
1953	1.064
1954	1.104
1955	1.087
1956	1.045
1957	1.044
1958	1.216
1959	1.031
1960	0.981
1961	1.141
1962	0.975
1963	1.232
1964	1.404
1965	1.146
1966	1.376
1967	0.761
1968	0.815
1969	0.996
1970	0.795
1971	0.652
1972	0.883
1973	0.781
1974	0.969
1975	0.964
1976	1.15
1977	1.09
1978	0.964
1979	1.122