ÃÂ¯ÃÂ»ÃÂ¿# northamerica_usa_ca087 - Kaiser Pass - 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:
#
# Online_Resource: https://www.ncdc.noaa.gov/paleo/study/24611
#
# Original_Source_URL:https://www.ncdc.noaa.gov/paleo/study/3532
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_ca087 - Kaiser Pass - 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 VaganovÃÂ¢ÃÂÃÂShashkin 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 4ÃÂ¢ÃÂÃÂ6 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 modelÃÂ¢ÃÂÃÂs 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.
#------------------
# 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
#------------------
# Site_Information
#	Site_Name: Kaiser Pass
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.28
#	Southernmost_Latitude: 37.28
#	Easternmost_Longitude: -119.08
#	Westernmost_Longitude: -119.08
#	Elevation: 2731 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_ca087B
#	Earliest_Year: 1140
#	Most_Recent_Year: 1981
#	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":"4.86176765156","T2":"17.3117130014","M1":"0.0230807255878","M2":"0.492884308972"}}
#--------------------
# Species
#	Species_Name: western juniper
#	Species_Code: JUOC
#--------------------
# Chronology:
#
#
#
#--------------------
# 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
1140	0.975
1141	1.13
1142	1.152
1143	0.989
1144	1.052
1145	1.043
1146	1.219
1147	1.252
1148	0.612
1149	0.519
1150	1.018
1151	0.936
1152	0.895
1153	0.761
1154	0.73
1155	0.804
1156	0.627
1157	0.323
1158	0.691
1159	0.671
1160	0.65
1161	0.64
1162	0.8
1163	0.865
1164	0.855
1165	0.771
1166	1.028
1167	0.708
1168	0.752
1169	0.785
1170	1.001
1171	0.722
1172	0.831
1173	1.015
1174	0.995
1175	1.083
1176	1.019
1177	0.716
1178	0.434
1179	0.63
1180	0.86
1181	0.708
1182	0.939
1183	0.468
1184	0.391
1185	0.711
1186	0.811
1187	0.757
1188	0.514
1189	0.581
1190	0.682
1191	0.905
1192	1.018
1193	1.232
1194	1.211
1195	1.213
1196	1.237
1197	0.89
1198	1.094
1199	1.05
1200	1.153
1201	1.234
1202	1.156
1203	1.033
1204	1.205
1205	1.173
1206	1.186
1207	1.119
1208	1.74
1209	1.352
1210	1.423
1211	1.54
1212	1.358
1213	1.232
1214	1.072
1215	1.422
1216	1.086
1217	1.076
1218	0.961
1219	1.021
1220	1.163
1221	1.141
1222	1.025
1223	1.026
1224	1.146
1225	1.124
1226	1.375
1227	0.984
1228	1.057
1229	1.309
1230	1.228
1231	1.146
1232	1.135
1233	1.461
1234	1.379
1235	1.068
1236	1.36
1237	0.986
1238	1.267
1239	1.645
1240	1.173
1241	1.065
1242	1.531
1243	1.338
1244	1.205
1245	1.342
1246	1.43
1247	1.297
1248	1.051
1249	1.437
1250	1.216
1251	1.031
1252	1.145
1253	1.159
1254	1.136
1255	0.912
1256	1.089
1257	0.952
1258	0.398
1259	0.613
1260	0.931
1261	0.881
1262	1.048
1263	1.228
1264	1.166
1265	1.142
1266	1.221
1267	0.902
1268	1.006
1269	1.188
1270	0.867
1271	1.218
1272	1.025
1273	1.027
1274	0.937
1275	1.199
1276	0.796
1277	0.81
1278	1.153
1279	1.01
1280	0.682
1281	0.881
1282	0.935
1283	0.897
1284	0.858
1285	0.433
1286	0.78
1287	1.13
1288	0.769
1289	0.69
1290	0.798
1291	0.988
1292	0.814
1293	0.517
1294	0.816
1295	0.859
1296	0.723
1297	0.424
1298	0.712
1299	0.575
1300	0.81
1301	0.728
1302	0.743
1303	0.869
1304	0.773
1305	0.552
1306	0.761
1307	0.958
1308	0.736
1309	0.919
1310	0.794
1311	0.527
1312	0.556
1313	0.401
1314	0.926
1315	0.459
1316	0.473
1317	0.602
1318	0.388
1319	0.389
1320	0.605
1321	0.678
1322	0.433
1323	0.404
1324	0.463
1325	0.565
1326	0.653
1327	0.625
1328	0.845
1329	0.715
1330	0.73
1331	0.879
1332	1.087
1333	0.912
1334	1.344
1335	1.451
1336	1.394
1337	1.352
1338	1.241
1339	1.038
1340	0.982
1341	1.039
1342	0.918
1343	1.003
1344	0.969
1345	1.159
1346	1.447
1347	1.2
1348	0.892
1349	1.134
1350	0.985
1351	1.014
1352	1.303
1353	1.542
1354	1.077
1355	1.066
1356	1.132
1357	1.041
1358	0.945
1359	1.193
1360	1.193
1361	1.071
1362	1.066
1363	0.884
1364	0.928
1365	0.825
1366	1.025
1367	0.883
1368	1.237
1369	1.231
1370	1.119
1371	1.115
1372	1.214
1373	1.237
1374	1.431
1375	1.059
1376	1.253
1377	0.944
1378	1.138
1379	1.125
1380	1.062
1381	1.228
1382	1.094
1383	1.317
1384	1.028
1385	1.268
1386	0.989
1387	1.106
1388	1.1
1389	1.201
1390	1.03
1391	1.023
1392	1.233
1393	1.22
1394	1.4
1395	0.848
1396	0.853
1397	0.87
1398	1.016
1399	0.904
1400	0.886
1401	0.794
1402	0.66
1403	0.797
1404	0.864
1405	0.941
1406	0.909
1407	0.707
1408	0.7
1409	0.868
1410	0.514
1411	0.795
1412	0.866
1413	0.417
1414	0.692
1415	0.738
1416	0.563
1417	0.822
1418	0.815
1419	0.669
1420	1.316
1421	1.056
1422	1.446
1423	1.486
1424	1.091
1425	0.763
1426	0.686
1427	1.019
1428	1.215
1429	1.419
1430	1.184
1431	0.776
1432	0.807
1433	0.9
1434	0.814
1435	0.997
1436	1.001
1437	0.817
1438	0.902
1439	0.88
1440	1.31
1441	1.158
1442	0.847
1443	1.015
1444	0.897
1445	0.947
1446	0.821
1447	0.933
1448	0.833
1449	0.889
1450	0.882
1451	0.771
1452	0.73
1453	0.84
1454	0.627
1455	0.793
1456	0.747
1457	0.868
1458	0.65
1459	0.592
1460	1.079
1461	0.975
1462	1.247
1463	1.143
1464	0.781
1465	0.97
1466	1.144
1467	1.219
1468	0.449
1469	1.058
1470	1.585
1471	1.165
1472	1.365
1473	1.109
1474	0.995
1475	0.975
1476	0.896
1477	1.126
1478	0.983
1479	0.751
1480	1.098
1481	1.141
1482	0.908
1483	0.952
1484	1.521
1485	1.29
1486	1.048
1487	0.952
1488	0.983
1489	1.166
1490	1.1
1491	1.468
1492	1.477
1493	1.495
1494	1.244
1495	1.072
1496	1.137
1497	1.063
1498	1.084
1499	1.169
1500	0.439
1501	0.887
1502	0.888
1503	1.035
1504	1.167
1505	1.207
1506	0.764
1507	0.659
1508	0.55
1509	1.027
1510	1.03
1511	0.844
1512	0.955
1513	1.066
1514	0.966
1515	0.791
1516	1.03
1517	1.31
1518	0.837
1519	0.812
1520	1.041
1521	1.006
1522	1.086
1523	0.989
1524	1.319
1525	1.477
1526	1.196
1527	1.127
1528	1.329
1529	1.099
1530	1.241
1531	1.11
1532	0.878
1533	0.685
1534	1.146
1535	1.078
1536	0.929
1537	0.813
1538	0.767
1539	1.102
1540	0.936
1541	0.683
1542	0.847
1543	0.813
1544	0.848
1545	0.893
1546	0.957
1547	1.005
1548	0.77
1549	1.26
1550	0.699
1551	1.021
1552	1.098
1553	1.413
1554	0.762
1555	0.837
1556	1.599
1557	1.198
1558	1.029
1559	1.199
1560	1.187
1561	1.05
1562	1.105
1563	1.188
1564	1.367
1565	1.223
1566	1.032
1567	1.103
1568	1.279
1569	0.66
1570	0.584
1571	0.811
1572	0.878
1573	1.001
1574	0.902
1575	0.835
1576	0.878
1577	1.424
1578	1.019
1579	0.673
1580	0.57
1581	1.264
1582	0.647
1583	1.054
1584	0.739
1585	0.953
1586	0.788
1587	0.815
1588	0.905
1589	1.368
1590	1
1591	0.971
1592	0.881
1593	0.804
1594	1.152
1595	0.604
1596	1.286
1597	0.929
1598	0.887
1599	1.138
1600	0.851
1601	1.124
1602	0.922
1603	0.875
1604	1.413
1605	1.46
1606	1.275
1607	0.778
1608	1.208
1609	0.967
1610	0.999
1611	1.173
1612	0.997
1613	0.777
1614	1.187
1615	1.25
1616	1.166
1617	1.535
1618	1.152
1619	0.896
1620	0.995
1621	0.92
1622	0.527
1623	0.893
1624	0.94
1625	1.363
1626	0.761
1627	0.979
1628	1.009
1629	0.876
1630	0.801
1631	0.57
1632	0.559
1633	0.941
1634	0.761
1635	0.664
1636	1.181
1637	0.686
1638	0.713
1639	0.645
1640	0.774
1641	0.829
1642	1.251
1643	0.861
1644	1.198
1645	1.331
1646	1.157
1647	1.203
1648	1.491
1649	1.367
1650	1.337
1651	1.355
1652	1.251
1653	0.742
1654	0.954
1655	0.499
1656	1.103
1657	0.36
1658	0.47
1659	0.702
1660	1.228
1661	1.155
1662	0.798
1663	0.743
1664	0.832
1665	0.852
1666	1.171
1667	0.813
1668	0.87
1669	0.691
1670	1.081
1671	1.174
1672	1.208
1673	1
1674	1.111
1675	1.011
1676	1.073
1677	1.316
1678	1.267
1679	1.276
1680	1.243
1681	1.28
1682	1.142
1683	1.355
1684	0.846
1685	0.995
1686	0.916
1687	1.012
1688	0.971
1689	1.01
1690	0.693
1691	0.642
1692	1.093
1693	0.92
1694	0.993
1695	0.859
1696	0.942
1697	1.259
1698	1.099
1699	1.23
1700	1.096
1701	0.89
1702	1.122
1703	0.799
1704	1.288
1705	1.588
1706	1.155
1707	0.911
1708	0.972
1709	1.14
1710	0.678
1711	0.987
1712	0.807
1713	0.766
1714	0.57
1715	0.552
1716	0.663
1717	0.922
1718	0.819
1719	0.739
1720	0.915
1721	0.735
1722	0.699
1723	0.762
1724	0.486
1725	0.931
1726	1.006
1727	0.956
1728	0.853
1729	0.544
1730	1.073
1731	0.863
1732	0.791
1733	0.726
1734	1.364
1735	0.923
1736	1.17
1737	0.929
1738	0.804
1739	0.796
1740	1.336
1741	1.379
1742	1.152
1743	1.279
1744	1.053
1745	1.805
1746	1.126
1747	1.279
1748	0.943
1749	1.153
1750	0.96
1751	1.045
1752	1.044
1753	0.869
1754	0.806
1755	0.767
1756	0.79
1757	0.887
1758	1.003
1759	0.79
1760	1.167
1761	1.06
1762	0.842
1763	1.079
1764	0.983
1765	0.89
1766	1.178
1767	1.058
1768	1.112
1769	0.833
1770	0.934
1771	0.913
1772	0.947
1773	0.944
1774	1.019
1775	0.844
1776	1.055
1777	0.807
1778	0.966
1779	0.808
1780	0.779
1781	0.827
1782	0.678
1783	0.72
1784	0.795
1785	0.678
1786	0.776
1787	0.798
1788	0.615
1789	0.751
1790	0.842
1791	0.787
1792	1.109
1793	0.648
1794	0.865
1795	0.648
1796	0.546
1797	0.73
1798	0.755
1799	1.111
1800	0.98
1801	0.857
1802	0.931
1803	0.999
1804	0.85
1805	1.061
1806	0.756
1807	0.782
1808	0.669
1809	1.057
1810	1.056
1811	1.237
1812	1.065
1813	1.281
1814	1.484
1815	1.164
1816	1.284
1817	1.467
1818	1.279
1819	1.277
1820	1.241
1821	1.16
1822	1.08
1823	0.919
1824	0.718
1825	1.251
1826	1.358
1827	0.912
1828	0.917
1829	0.951
1830	1.163
1831	0.989
1832	1.611
1833	0.911
1834	0.824
1835	1.027
1836	0.921
1837	0.914
1838	1.23
1839	0.875
1840	0.844
1841	0.667
1842	0.851
1843	0.87
1844	0.682
1845	1.465
1846	0.912
1847	1.128
1848	1.27
1849	1.031
1850	1.001
1851	0.801
1852	1.395
1853	1.246
1854	0.899
1855	0.977
1856	0.637
1857	1.093
1858	0.743
1859	0.802
1860	0.977
1861	0.902
1862	0.965
1863	1.062
1864	1.228
1865	1.09
1866	1.214
1867	1.108
1868	0.816
1869	0.754
1870	0.916
1871	0.581
1872	0.598
1873	0.721
1874	0.763
1875	0.8
1876	0.866
1877	0.772
1878	1.055
1879	1.032
1880	0.963
1881	1.24
1882	1.127
1883	1.013
1884	1.596
1885	1.816
1886	1.254
1887	1.219
1888	1.575
1889	1.409
1890	1.665
1891	1.48
1892	0.97
1893	1.498
1894	1.426
1895	1.539
1896	1.355
1897	1.468
1898	1.221
1899	0.993
1900	1.262
1901	1.729
1902	1.154
1903	0.978
1904	1.395
1905	1.192
1906	1.442
1907	1.161
1908	1.08
1909	1.012
1910	0.934
1911	1.253
1912	0.795
1913	1.105
1914	1.324
1915	1.069
1916	1.14
1917	0.965
1918	0.829
1919	0.82
1920	0.752
1921	0.894
1922	0.75
1923	0.647
1924	0.564
1925	0.997
1926	0.856
1927	0.529
1928	0.503
1929	0.681
1930	0.457
1931	0.819
1932	0.676
1933	0.455
1934	0.648
1935	0.798
1936	1.016
1937	0.859
1938	1.044
1939	0.838
1940	1.02
1941	0.947
1942	0.894
1943	0.886
1944	0.634
1945	0.816
1946	0.805
1947	0.779
1948	0.838
1949	0.623
1950	0.903
1951	0.89
1952	1.014
1953	0.741
1954	1.07
1955	0.747
1956	0.86
1957	0.958
1958	1.181
1959	0.699
1960	0.517
1961	0.691
1962	0.84
1963	0.799
1964	0.741
1965	0.906
1966	0.886
1967	1.015
1968	0.688
1969	1.319
1970	0.951
1971	0.817
1972	1.124
1973	0.951
1974	0.973
1975	1.167
1976	0.98
1977	1.232
1978	1.686
1979	1.336
1980	1.505
1981	1.165