ÃÂ¯ÃÂ»ÃÂ¿# northamerica_usa_nv519 - Lucky Horseshoe - 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/3711
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: northamerica_usa_nv519 - Lucky Horseshoe - 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: Lucky Horseshoe
#	Location:
#	Country: United States
#	Northernmost_Latitude: 37.87
#	Southernmost_Latitude: 37.87
#	Easternmost_Longitude: -118.33
#	Westernmost_Longitude: -118.33
#	Elevation: 3140 m
#--------------------
# Data_Collection
#	Collection_Name: northamerica_usa_nv519B
#	Earliest_Year: 990
#	Most_Recent_Year: 2000
#	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":"4.70377514916","T2":"17.3175075337","M1":"0.0230323725587","M2":"0.39973655958"}}
#--------------------
# Species
#	Species_Name: limber pine
#	Species_Code: PIFL
#--------------------
# 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
990	0.932
991	0.914
992	0.886
993	1.039
994	0.915
995	0.729
996	0.816
997	0.656
998	0.805
999	0.982
1000	0.847
1001	0.633
1002	0.945
1003	0.795
1004	0.952
1005	0.82
1006	0.831
1007	0.926
1008	0.837
1009	0.772
1010	0.966
1011	0.89
1012	1.021
1013	0.836
1014	0.95
1015	0.964
1016	1.03
1017	1.197
1018	1.343
1019	0.904
1020	1.161
1021	0.953
1022	0.992
1023	1.158
1024	1.123
1025	1.034
1026	0.907
1027	0.856
1028	1.307
1029	1.168
1030	1.095
1031	1.117
1032	0.989
1033	1.074
1034	1.055
1035	0.495
1036	0.9
1037	1.002
1038	0.933
1039	0.997
1040	1.038
1041	1.245
1042	1.111
1043	0.923
1044	0.449
1045	0.941
1046	1.077
1047	1.038
1048	0.416
1049	0.878
1050	1.056
1051	1.331
1052	0.971
1053	0.693
1054	0.847
1055	0.455
1056	0.89
1057	0.766
1058	1.173
1059	0.967
1060	0.866
1061	1.145
1062	0.948
1063	0.797
1064	0.847
1065	0.889
1066	0.763
1067	0.825
1068	0.816
1069	0.692
1070	0.643
1071	0.872
1072	1.115
1073	0.952
1074	0.952
1075	1.007
1076	1.055
1077	0.397
1078	1.003
1079	1.236
1080	1.089
1081	1.126
1082	0.919
1083	1.147
1084	0.732
1085	0.927
1086	1.105
1087	1.072
1088	1.093
1089	1.176
1090	1.044
1091	1.21
1092	1.073
1093	1.001
1094	0.864
1095	1.018
1096	1.18
1097	1.123
1098	0.972
1099	1.133
1100	1.302
1101	0.965
1102	0.899
1103	0.756
1104	1.326
1105	0.89
1106	0.883
1107	1.423
1108	1.504
1109	1.015
1110	1.053
1111	1.104
1112	1.086
1113	1.018
1114	0.924
1115	0.907
1116	0.669
1117	0.763
1118	0.856
1119	1.084
1120	0.904
1121	0.545
1122	1.045
1123	0.928
1124	1.017
1125	1.074
1126	0.936
1127	0.468
1128	1.034
1129	0.652
1130	0.885
1131	1.232
1132	0.506
1133	0.316
1134	0.83
1135	0.36
1136	0.708
1137	0.638
1138	0.57
1139	0.599
1140	0.544
1141	0.817
1142	0.57
1143	0.691
1144	0.814
1145	0.781
1146	0.737
1147	0.746
1148	0.857
1149	0.946
1150	0.924
1151	1.045
1152	1.057
1153	0.839
1154	0.838
1155	0.889
1156	1.052
1157	1.08
1158	0.897
1159	0.692
1160	1.136
1161	1.166
1162	1.152
1163	1.181
1164	0.936
1165	1.269
1166	1.266
1167	1.178
1168	0.895
1169	1.111
1170	1.199
1171	1.178
1172	1.012
1173	1.015
1174	1.01
1175	1.018
1176	0.947
1177	0.864
1178	0.956
1179	0.795
1180	0.654
1181	1.099
1182	1.033
1183	1.119
1184	1.138
1185	1.207
1186	1.164
1187	1.486
1188	1.332
1189	0.959
1190	1.297
1191	1.201
1192	1.372
1193	1.437
1194	1.218
1195	1.135
1196	0.941
1197	1.192
1198	1.006
1199	1.343
1200	1.025
1201	1.189
1202	1.143
1203	1.333
1204	1.187
1205	1.391
1206	1.099
1207	1.217
1208	1.11
1209	1.026
1210	1.216
1211	1.326
1212	1.239
1213	1.355
1214	1.304
1215	1.088
1216	1.024
1217	0.46
1218	0.221
1219	1.165
1220	1.098
1221	1.13
1222	1.158
1223	1.038
1224	0.954
1225	1.093
1226	1.187
1227	0.551
1228	1.199
1229	1.001
1230	0.797
1231	1.052
1232	0.973
1233	0.68
1234	0.672
1235	0.836
1236	0.837
1237	0.986
1238	1.127
1239	1.145
1240	0.957
1241	0.976
1242	0.95
1243	1.002
1244	0.88
1245	0.935
1246	0.507
1247	0.907
1248	1.232
1249	1.143
1250	0.924
1251	1.037
1252	1.021
1253	1.31
1254	0.49
1255	0.928
1256	0.959
1257	1.362
1258	0.607
1259	1.194
1260	1.204
1261	1.429
1262	1.431
1263	1.416
1264	1.308
1265	1.18
1266	0.932
1267	1.123
1268	1.156
1269	1.076
1270	1.209
1271	1.228
1272	1.261
1273	0.821
1274	1.247
1275	1.542
1276	0.847
1277	1.304
1278	1.16
1279	1.263
1280	1.183
1281	1.053
1282	1.041
1283	1.218
1284	1.092
1285	1.01
1286	1.103
1287	0.793
1288	0.783
1289	0.89
1290	0.88
1291	0.993
1292	1.057
1293	1.068
1294	0.97
1295	1.073
1296	0.902
1297	0.665
1298	0.762
1299	0.666
1300	1.059
1301	0.897
1302	0.818
1303	1.028
1304	0.854
1305	1.062
1306	1.098
1307	0.814
1308	1.123
1309	1.006
1310	1.124
1311	1.21
1312	1.21
1313	1.392
1314	1.352
1315	0.91
1316	0.866
1317	1.138
1318	1.099
1319	1.204
1320	1.409
1321	1.594
1322	1.291
1323	0.733
1324	1.336
1325	1.391
1326	1.092
1327	1.236
1328	1.419
1329	1.045
1330	1.221
1331	1.35
1332	1.166
1333	1.369
1334	0.72
1335	0.772
1336	0.644
1337	0.957
1338	0.725
1339	0.593
1340	0.651
1341	0.656
1342	0.641
1343	0.863
1344	0.945
1345	0.99
1346	1.128
1347	0.811
1348	0.957
1349	0.945
1350	0.94
1351	0.768
1352	0.852
1353	0.774
1354	0.729
1355	1.065
1356	1.062
1357	1.082
1358	1.001
1359	0.889
1360	0.949
1361	0.677
1362	0.62
1363	0.795
1364	0.768
1365	0.876
1366	1.129
1367	1.055
1368	1.207
1369	1.365
1370	1.293
1371	1.054
1372	0.979
1373	0.928
1374	0.966
1375	0.898
1376	0.962
1377	0.406
1378	1.037
1379	0.381
1380	0.888
1381	0.874
1382	0.663
1383	0.947
1384	0.819
1385	1.055
1386	1.002
1387	1.115
1388	1.231
1389	1.133
1390	1.236
1391	1.17
1392	1.271
1393	1.272
1394	1.28
1395	1.285
1396	0.928
1397	0.744
1398	0.712
1399	0.97
1400	0.912
1401	0.549
1402	1.161
1403	1.061
1404	1.073
1405	0.89
1406	1.279
1407	0.35
1408	1.024
1409	1.044
1410	0.984
1411	1.111
1412	1.036
1413	0.866
1414	0.859
1415	1.046
1416	1.133
1417	1.141
1418	0.926
1419	1.135
1420	1.078
1421	0.857
1422	1.058
1423	1.102
1424	1.209
1425	0.943
1426	0.596
1427	0.756
1428	1.142
1429	1.142
1430	1.067
1431	0.614
1432	0.92
1433	0.941
1434	0.521
1435	1.316
1436	1.142
1437	0.839
1438	0.594
1439	0.893
1440	0.998
1441	0.947
1442	0.389
1443	1.164
1444	0.847
1445	0.789
1446	0.9
1447	0.741
1448	0.72
1449	0.705
1450	0.465
1451	0.799
1452	0.842
1453	0.884
1454	0.812
1455	0.789
1456	0.717
1457	0.628
1458	0.474
1459	0.417
1460	0.386
1461	0.58
1462	0.497
1463	0.715
1464	0.608
1465	0.601
1466	0.924
1467	0.751
1468	0.503
1469	0.779
1470	0.852
1471	0.613
1472	0.692
1473	0.593
1474	0.82
1475	0.313
1476	0.94
1477	0.936
1478	0.881
1479	0.846
1480	0.886
1481	1.035
1482	0.808
1483	0.839
1484	0.921
1485	1.034
1486	0.98
1487	0.821
1488	0.963
1489	1.078
1490	1.157
1491	0.822
1492	0.39
1493	0.768
1494	1.036
1495	0.675
1496	0.799
1497	0.507
1498	0.758
1499	0.789
1500	0.659
1501	0.895
1502	1
1503	1.07
1504	0.931
1505	0.883
1506	0.837
1507	0.726
1508	0.894
1509	1.09
1510	1.199
1511	0.996
1512	0.967
1513	1.023
1514	0.963
1515	0.68
1516	1.021
1517	0.907
1518	1.112
1519	0.964
1520	1.132
1521	1.16
1522	1.311
1523	0.638
1524	1.343
1525	1.204
1526	1.446
1527	1.724
1528	1.28
1529	1.299
1530	1.182
1531	1.262
1532	1.162
1533	0.805
1534	1.147
1535	1.511
1536	1.236
1537	1.281
1538	1.151
1539	1.376
1540	1.164
1541	0.659
1542	0.402
1543	1.036
1544	0.913
1545	1.047
1546	1.153
1547	0.836
1548	0.784
1549	1.124
1550	1.074
1551	1.001
1552	0.927
1553	1.202
1554	1.269
1555	1.257
1556	1.279
1557	1.104
1558	1.044
1559	1.14
1560	1.107
1561	1.177
1562	1.352
1563	0.937
1564	1.097
1565	1.149
1566	0.746
1567	1.151
1568	1.24
1569	1.14
1570	1.064
1571	0.881
1572	1.036
1573	1.061
1574	1.014
1575	0.959
1576	1.086
1577	0.823
1578	0.884
1579	0.26
1580	0.405
1581	1.017
1582	1.03
1583	1.076
1584	1.036
1585	1.178
1586	1.162
1587	1.162
1588	1.126
1589	1.145
1590	0.594
1591	0.892
1592	0.918
1593	1.017
1594	1.341
1595	1.253
1596	1.266
1597	1.336
1598	1.392
1599	1.087
1600	0.839
1601	0.978
1602	0.95
1603	1.13
1604	1.084
1605	1.161
1606	1.097
1607	0.887
1608	0.995
1609	1.05
1610	0.969
1611	0.867
1612	1.037
1613	0.809
1614	1.173
1615	0.916
1616	1.161
1617	1.258
1618	0.953
1619	1.086
1620	1.272
1621	1.291
1622	1.006
1623	1.071
1624	0.778
1625	1.037
1626	0.642
1627	1.136
1628	1.227
1629	1.143
1630	1.147
1631	0.97
1632	0.846
1633	1.093
1634	1.212
1635	1.09
1636	1.097
1637	1.026
1638	1.369
1639	1.206
1640	1.283
1641	0.779
1642	0.788
1643	0.877
1644	0.883
1645	0.761
1646	0.781
1647	0.734
1648	0.964
1649	0.957
1650	1.015
1651	1.277
1652	0.831
1653	1.151
1654	0.952
1655	0.852
1656	0.954
1657	1.285
1658	1.227
1659	1.211
1660	1.317
1661	1.312
1662	1.133
1663	1.136
1664	1.181
1665	1.047
1666	1.178
1667	1.192
1668	0.291
1669	0.746
1670	0.62
1671	1.073
1672	0.919
1673	0.793
1674	1.17
1675	0.804
1676	0.639
1677	0.584
1678	0.657
1679	0.856
1680	1.005
1681	0.525
1682	1.12
1683	1.408
1684	1.161
1685	1.039
1686	0.888
1687	1.121
1688	0.681
1689	1.167
1690	1.179
1691	1.085
1692	1.034
1693	1.049
1694	1.176
1695	1.168
1696	0.969
1697	0.87
1698	0.905
1699	0.784
1700	0.896
1701	1.039
1702	1.079
1703	0.533
1704	0.661
1705	0.624
1706	0.837
1707	0.821
1708	0.804
1709	1.176
1710	1.007
1711	0.994
1712	1.17
1713	1.05
1714	1.16
1715	1.007
1716	0.883
1717	1.082
1718	1.291
1719	1.417
1720	1.331
1721	1.451
1722	0.946
1723	0.789
1724	1.244
1725	1.297
1726	1.153
1727	1.392
1728	1.55
1729	1.244
1730	0.983
1731	0.877
1732	0.889
1733	0.678
1734	0.878
1735	0.624
1736	0.904
1737	1.074
1738	1.015
1739	0.998
1740	1.05
1741	1.066
1742	0.859
1743	1.285
1744	1.093
1745	0.954
1746	1.157
1747	1.257
1748	1.141
1749	0.995
1750	0.984
1751	1.157
1752	0.765
1753	0.629
1754	0.722
1755	0.889
1756	0.863
1757	1.115
1758	1.185
1759	0.886
1760	1.12
1761	1.039
1762	0.822
1763	0.875
1764	0.626
1765	0.848
1766	0.724
1767	0.915
1768	0.682
1769	1.028
1770	0.856
1771	1.024
1772	0.864
1773	1.001
1774	0.806
1775	0.976
1776	0.876
1777	0.866
1778	1.001
1779	0.92
1780	0.94
1781	0.613
1782	0.928
1783	0.887
1784	0.866
1785	0.965
1786	0.94
1787	1.034
1788	1.115
1789	0.835
1790	0.954
1791	0.89
1792	0.827
1793	0.916
1794	0.805
1795	1.007
1796	1.146
1797	0.719
1798	0.629
1799	0.847
1800	0.877
1801	0.705
1802	0.771
1803	0.689
1804	0.71
1805	0.841
1806	0.779
1807	0.666
1808	0.932
1809	0.766
1810	0.602
1811	0.545
1812	0.309
1813	0.614
1814	0.661
1815	0.835
1816	0.651
1817	0.956
1818	0.825
1819	0.725
1820	0.837
1821	0.901
1822	0.578
1823	0.783
1824	0.676
1825	0.888
1826	0.918
1827	1.001
1828	0.973
1829	0.952
1830	0.915
1831	0.917
1832	0.745
1833	0.848
1834	0.786
1835	0.64
1836	0.755
1837	0.701
1838	0.678
1839	0.938
1840	0.758
1841	0.875
1842	0.749
1843	0.925
1844	0.822
1845	0.712
1846	0.891
1847	0.785
1848	0.939
1849	1.01
1850	0.454
1851	0.899
1852	1.106
1853	0.923
1854	1.174
1855	1
1856	1.001
1857	0.764
1858	0.829
1859	1.086
1860	1.077
1861	0.97
1862	1.159
1863	1.162
1864	1.114
1865	0.647
1866	1.302
1867	1.085
1868	1.37
1869	1.431
1870	1.518
1871	1.107
1872	1.435
1873	0.797
1874	1.063
1875	0.861
1876	0.676
1877	0.971
1878	0.83
1879	0.898
1880	0.759
1881	0.675
1882	0.895
1883	0.871
1884	0.788
1885	0.828
1886	0.705
1887	0.679
1888	0.796
1889	0.795
1890	0.677
1891	1.011
1892	0.9
1893	0.82
1894	0.933
1895	0.898
1896	0.611
1897	0.664
1898	0.687
1899	0.836
1900	0.746
1901	0.933
1902	0.864
1903	0.998
1904	0.779
1905	1.014
1906	0.982
1907	1.091
1908	0.987
1909	1.114
1910	0.767
1911	1.251
1912	1.132
1913	1.049
1914	1.152
1915	1.25
1916	0.999
1917	1.12
1918	1.209
1919	1.206
1920	0.974
1921	1.03
1922	1.085
1923	0.654
1924	0.633
1925	0.746
1926	0.823
1927	0.814
1928	0.991
1929	0.445
1930	0.99
1931	0.994
1932	0.988
1933	1.042
1934	1.001
1935	0.849
1936	0.647
1937	0.979
1938	1.016
1939	1.039
1940	1.165
1941	1.08
1942	1.128
1943	1.149
1944	0.851
1945	1.017
1946	1.226
1947	1.24
1948	1.059
1949	1.094
1950	0.834
1951	1.07
1952	0.997
1953	1.061
1954	0.999
1955	1.193
1956	1.323
1957	1.221
1958	1.18
1959	1.189
1960	0.455
1961	1.214
1962	1.169
1963	1.24
1964	1.275
1965	1.389
1966	1.075
1967	1.198
1968	1.265
1969	1.637
1970	1.191
1971	1.238
1972	1.219
1973	1.354
1974	1.221
1975	1.296
1976	1.3
1977	1.234
1978	1.237
1979	1.083
1980	1.178
1981	1.058
1982	1.077
1983	1.083
1984	1.242
1985	1.221
1986	1.045
1987	1.135
1988	1.329
1989	1.234
1990	1.214
1991	1.246
1992	1.329
1993	1.189
1994	0.846
1995	0.906
1996	1.218
1997	1.368
1998	1.171
1999	1.11
2000	1.192