# northamerica_usa_co538 - Horsetooth Reservior 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.
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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/3368
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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_co538 - Horsetooth Reservior 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: Horsetooth Reservior A
#	Location:
#	Country: United States
#	Northernmost_Latitude: 40.53
#	Southernmost_Latitude: 40.53
#	Easternmost_Longitude: -105.13
#	Westernmost_Longitude: -105.13
#	Elevation: 1706 m
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# Data_Collection
#	Collection_Name: northamerica_usa_co538B
#	Earliest_Year: 1695
#	Most_Recent_Year: 1987
#	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":"4.20880242224","T2":"15.509988453","M1":"0.0237867917719","M2":"0.493405145266"}}
#--------------------
# 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)
#
##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
1695	0.764
1696	0.927
1697	0.866
1698	0.742
1699	0.855
1700	1.049
1701	0.967
1702	1.132
1703	0.752
1704	0.904
1705	1.113
1706	0.867
1707	0.832
1708	0.628
1709	0.597
1710	0.926
1711	0.398
1712	0.676
1713	0.802
1714	0.887
1715	0.802
1716	0.884
1717	0.627
1718	1.064
1719	1.207
1720	1.601
1721	1.574
1722	1.466
1723	0.739
1724	0.778
1725	0.949
1726	1.434
1727	1.335
1728	1.359
1729	0.911
1730	0.752
1731	1.225
1732	1.378
1733	1.428
1734	1.562
1735	0.911
1736	0.783
1737	1.144
1738	0.986
1739	0.7
1740	0.873
1741	0.727
1742	0.688
1743	1.253
1744	0.93
1745	1.402
1746	1.284
1747	1.023
1748	0.828
1749	1.001
1750	0.786
1751	1.058
1752	1.044
1753	1.3
1754	1.772
1755	1.221
1756	0.932
1757	1.22
1758	0.631
1759	0.388
1760	0.618
1761	1.369
1762	0.676
1763	0.811
1764	1.093
1765	0.314
1766	0.502
1767	0.353
1768	0.813
1769	0.711
1770	0.807
1771	1.159
1772	0.84
1773	1.035
1774	1.452
1775	1.325
1776	1.383
1777	1.36
1778	1.479
1779	1.136
1780	1.253
1781	1.462
1782	1.006
1783	1.247
1784	0.92
1785	1.042
1786	0.747
1787	1.015
1788	0.877
1789	0.697
1790	0.972
1791	0.78
1792	1.204
1793	1.25
1794	1.712
1795	1.595
1796	1.212
1797	1.448
1798	1.166
1799	1.015
1800	0.934
1801	0.677
1802	0.689
1803	1.321
1804	0.866
1805	0.505
1806	0.98
1807	0.672
1808	0.926
1809	0.879
1810	0.907
1811	1.128
1812	1.112
1813	1.031
1814	1.152
1815	1.149
1816	1.06
1817	0.906
1818	0.708
1819	0.719
1820	0.911
1821	1.041
1822	0.906
1823	0.902
1824	0.805
1825	1.073
1826	0.7
1827	0.889
1828	1.057
1829	0.749
1830	1.264
1831	0.838
1832	0.784
1833	0.812
1834	0.817
1835	1.211
1836	1.07
1837	0.995
1838	1.362
1839	1.729
1840	1.062
1841	1.176
1842	0.553
1843	1.329
1844	1.283
1845	1.2
1846	1.018
1847	0.762
1848	0.566
1849	0.985
1850	1.076
1851	0.673
1852	0.738
1853	0.828
1854	0.498
1855	0.323
1856	0.294
1857	0.851
1858	1.168
1859	0.8
1860	1.261
1861	0.946
1862	1.075
1863	0.887
1864	0.952
1865	0.97
1866	1.445
1867	1.139
1868	1.139
1869	1.547
1870	0.926
1871	0.868
1872	1.288
1873	0.744
1874	0.718
1875	0.542
1876	0.713
1877	0.794
1878	1.189
1879	0.968
1880	0.185
1881	0.966
1882	1.159
1883	0.986
1884	1.242
1885	1.353
1886	1.158
1887	1.26
1888	0.96
1889	1.085
1890	1.037
1891	1.306
1892	1.014
1893	0.639
1894	0.934
1895	1.114
1896	0.934
1897	1.448
1898	1.301
1899	1.235
1900	1.315
1901	1.188
1902	0.851
1903	1.414
1904	1.307
1905	1.324
1906	1.623
1907	1.441
1908	1.015
1909	1.095
1910	0.968
1911	1.367
1912	2.08
1913	1.291
1914	1.261
1915	1.357
1916	0.672
1917	0.848
1918	1.27
1919	0.529
1920	0.987
1921	1.101
1922	0.68
1923	0.867
1924	0.749
1925	-0.018
1926	1.201
1927	0.724
1928	0.818
1929	0.897
1930	0.966
1931	1.049
1932	0.783
1933	0.467
1934	0.675
1935	0.467
1936	0.736
1937	0.877
1938	1.106
1939	0.799
1940	0.289
1941	1.075
1942	0.815
1943	0.698
1944	0.655
1945	0.997
1946	0.307
1947	1.147
1948	1.179
1949	1.179
1950	0.897
1951	1.176
1952	1.18
1953	1.192
1954	0.098
1955	0.962
1956	0.877
1957	0.922
1958	1.422
1959	0.798
1960	1.001
1961	1.365
1962	0.72
1963	0.349
1964	1.013
1965	1.13
1966	0.299
1967	1.251
1968	0.791
1969	0.797
1970	1.261
1971	1.661
1972	1.108
1973	1.212
1974	1.482
1975	1.646
1976	1.399
1977	0.622
1978	0.624
1979	1.144
1980	0.718
1981	0.848
1982	0.592
1983	1.231
1984	0.669
1985	0.867
1986	0.914
1987	0.918