# southamerica_arge087 - RÃÂ­o Frias - 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/5186
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge087 - RÃÂ­o Frias - 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: RÃÂ­o Frias
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -41.1
#	Southernmost_Latitude: -41.1
#	Easternmost_Longitude: -71.8
#	Westernmost_Longitude: -71.8
#	Elevation: 950 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge087B
#	Earliest_Year: 888
#	Most_Recent_Year: 1991
#	Time_Unit: y_ad
#	Core_Length:
#	Notes: {"database":{"database1":"LMR","database2":"Breits"}} {"climateInterpretation":{"basis":"", "climateVariable":"T", "climateVariableDetail":"air", "interpDirection":"positive", "seasonality":"[-12, 1, 2]"}}{"VSLite_parameters":{"T1":"2.6592336542","T2":"12.4486968324","M1":"0.0226672452743","M2":"0.578804716454"}} A negative exponential detrending approached 0, thus this dataset was alternately standardized using a 75% cutoff smoothing spline methodology in ARSTAN, following the methodology outlined in Breitenmoser 2014.
#--------------------
# Species
#	Species_Name: alerce cypress
#	Species_Code: FICU
#--------------------
# 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
888	1.116
889	0.982
890	0.867
891	0.837
892	0.972
893	0.948
894	1.417
895	1.16
896	1.056
897	1.038
898	0.847
899	0.996
900	1.071
901	1.197
902	1.135
903	1.249
904	1.225
905	1.282
906	1.239
907	1.46
908	1.223
909	1.168
910	1.169
911	0.937
912	0.944
913	0.869
914	0.888
915	0.933
916	0.972
917	1.011
918	0.955
919	1.006
920	1.128
921	1.04
922	0.996
923	0.907
924	0.895
925	0.716
926	0.755
927	0.781
928	0.775
929	0.866
930	0.88
931	0.952
932	1.192
933	1.316
934	1.149
935	1.143
936	0.955
937	1.093
938	1.081
939	0.892
940	0.854
941	1.064
942	0.993
943	0.948
944	1.021
945	1.048
946	1.359
947	1.467
948	1.309
949	1.165
950	1.159
951	1.12
952	1.035
953	0.949
954	0.896
955	1.091
956	1.012
957	1.046
958	0.987
959	0.907
960	0.955
961	0.928
962	0.909
963	1.018
964	0.971
965	0.898
966	0.769
967	1.117
968	1.267
969	1.33
970	1.099
971	1.039
972	1.019
973	1.061
974	1.069
975	0.994
976	1.112
977	1.238
978	1.369
979	1.225
980	1.105
981	0.96
982	0.766
983	0.884
984	1.221
985	0.976
986	1.054
987	1.149
988	1.178
989	1.012
990	0.866
991	0.994
992	1.039
993	0.923
994	0.941
995	0.703
996	0.874
997	0.79
998	0.827
999	0.946
1000	0.807
1001	0.899
1002	0.926
1003	1.07
1004	0.979
1005	1.031
1006	0.599
1007	0.907
1008	1.008
1009	1.093
1010	1.108
1011	1.189
1012	1.051
1013	0.862
1014	0.931
1015	1.181
1016	1.178
1017	1.214
1018	1.275
1019	1.233
1020	0.976
1021	0.977
1022	1.249
1023	1.238
1024	1
1025	0.985
1026	1.079
1027	1.071
1028	1.019
1029	0.857
1030	0.699
1031	0.89
1032	1.098
1033	0.827
1034	0.923
1035	0.815
1036	0.723
1037	0.852
1038	0.802
1039	0.773
1040	0.909
1041	0.978
1042	1.007
1043	0.974
1044	0.875
1045	0.994
1046	0.657
1047	0.785
1048	0.714
1049	0.932
1050	0.877
1051	0.851
1052	0.764
1053	1.106
1054	1.054
1055	1.052
1056	0.946
1057	1.092
1058	1.31
1059	1.241
1060	1.416
1061	1.311
1062	1.7
1063	1.179
1064	1.079
1065	1.362
1066	1.58
1067	1.382
1068	1.05
1069	1.041
1070	0.788
1071	0.858
1072	0.873
1073	0.851
1074	0.821
1075	0.708
1076	1.285
1077	1.378
1078	1.298
1079	0.975
1080	1.116
1081	1.144
1082	0.853
1083	1.016
1084	1.218
1085	1.163
1086	1.132
1087	0.578
1088	0.734
1089	0.865
1090	0.908
1091	1.113
1092	0.921
1093	0.697
1094	0.868
1095	1.107
1096	0.762
1097	0.824
1098	0.728
1099	0.848
1100	0.694
1101	0.729
1102	0.733
1103	0.868
1104	0.916
1105	0.702
1106	0.927
1107	0.871
1108	0.934
1109	1.082
1110	0.827
1111	0.975
1112	0.94
1113	0.902
1114	1.047
1115	1.055
1116	0.945
1117	0.885
1118	0.588
1119	0.962
1120	0.877
1121	0.916
1122	1.01
1123	0.856
1124	0.757
1125	0.677
1126	0.547
1127	0.785
1128	0.61
1129	0.758
1130	0.71
1131	0.79
1132	0.578
1133	0.767
1134	0.769
1135	0.629
1136	0.63
1137	0.991
1138	0.876
1139	0.721
1140	0.847
1141	0.533
1142	0.639
1143	0.78
1144	0.507
1145	0.643
1146	0.862
1147	0.64
1148	0.904
1149	0.901
1150	1.065
1151	0.871
1152	1.122
1153	0.951
1154	0.804
1155	0.788
1156	1.024
1157	1.065
1158	0.804
1159	1.216
1160	1.082
1161	1.288
1162	1.236
1163	0.765
1164	1.127
1165	0.938
1166	1.206
1167	1.047
1168	1.092
1169	1.198
1170	1.048
1171	1.146
1172	1.093
1173	0.861
1174	0.941
1175	1.208
1176	0.996
1177	0.992
1178	1.091
1179	0.884
1180	0.843
1181	0.803
1182	0.799
1183	0.819
1184	0.738
1185	0.638
1186	0.852
1187	0.867
1188	1.154
1189	1.071
1190	1.545
1191	1.198
1192	1.052
1193	1.362
1194	0.72
1195	1.083
1196	1.461
1197	1.464
1198	2.121
1199	1.674
1200	1.502
1201	1.439
1202	0.994
1203	1.07
1204	0.866
1205	1.11
1206	1.115
1207	1.197
1208	0.858
1209	1.357
1210	0.864
1211	0.889
1212	0.898
1213	1.117
1214	1.107
1215	1.108
1216	0.889
1217	1.074
1218	0.986
1219	1.386
1220	1.239
1221	1.238
1222	1.272
1223	1.39
1224	1.107
1225	1.396
1226	1.374
1227	0.704
1228	1.067
1229	0.982
1230	0.798
1231	0.801
1232	0.555
1233	0.328
1234	0.423
1235	0.638
1236	0.623
1237	0.676
1238	0.645
1239	0.74
1240	0.733
1241	0.803
1242	0.572
1243	0.75
1244	1.145
1245	1.097
1246	1.072
1247	1.043
1248	1.087
1249	1.037
1250	0.796
1251	0.74
1252	0.866
1253	0.657
1254	0.7
1255	0.904
1256	0.738
1257	1.093
1258	1.178
1259	0.905
1260	0.818
1261	0.841
1262	1.099
1263	0.88
1264	0.808
1265	0.925
1266	0.949
1267	1.081
1268	1.139
1269	1.033
1270	0.916
1271	0.568
1272	0.925
1273	0.701
1274	1.035
1275	0.867
1276	0.943
1277	1.015
1278	0.748
1279	0.704
1280	0.874
1281	1.007
1282	0.802
1283	0.678
1284	0.801
1285	0.965
1286	0.924
1287	0.936
1288	0.804
1289	0.94
1290	0.986
1291	1.038
1292	0.679
1293	0.87
1294	0.913
1295	0.93
1296	1.093
1297	0.982
1298	1.054
1299	0.856
1300	0.643
1301	0.75
1302	1.478
1303	1.321
1304	1.396
1305	1.121
1306	1.073
1307	1.265
1308	1.27
1309	1.179
1310	1.157
1311	0.515
1312	0.898
1313	0.808
1314	1.055
1315	1.141
1316	1.087
1317	0.895
1318	0.642
1319	0.862
1320	1.048
1321	0.806
1322	0.982
1323	1.159
1324	1.122
1325	1.115
1326	1.201
1327	1.059
1328	0.967
1329	1.198
1330	1.178
1331	1.12
1332	0.682
1333	1.082
1334	1.121
1335	1.331
1336	1.208
1337	0.98
1338	1.011
1339	1.25
1340	1.386
1341	1.763
1342	1.764
1343	1.692
1344	1.563
1345	1.543
1346	0.906
1347	1.106
1348	1.239
1349	1.257
1350	1.14
1351	1.357
1352	1.097
1353	1.165
1354	1.17
1355	0.762
1356	0.646
1357	0.921
1358	1.265
1359	1.053
1360	0.939
1361	0.986
1362	1.031
1363	1.052
1364	1.242
1365	1.053
1366	1.015
1367	1.065
1368	1.159
1369	1.313
1370	1.33
1371	1.062
1372	1.14
1373	0.938
1374	0.893
1375	0.914
1376	0.892
1377	1.094
1378	0.843
1379	0.871
1380	0.973
1381	0.769
1382	0.929
1383	0.891
1384	0.95
1385	0.596
1386	0.574
1387	0.87
1388	0.832
1389	0.888
1390	0.932
1391	0.661
1392	0.862
1393	0.895
1394	0.825
1395	0.838
1396	0.284
1397	0.494
1398	0.485
1399	0.526
1400	0.836
1401	0.921
1402	0.901
1403	0.746
1404	0.875
1405	0.907
1406	0.993
1407	1.063
1408	1.002
1409	0.908
1410	1.076
1411	0.891
1412	0.829
1413	0.988
1414	0.883
1415	0.856
1416	0.976
1417	1.055
1418	0.968
1419	0.969
1420	1.036
1421	1.07
1422	1.406
1423	1.236
1424	0.885
1425	1.133
1426	1.299
1427	1.199
1428	1.11
1429	1.403
1430	1.229
1431	1.252
1432	1.401
1433	1.271
1434	1.113
1435	1.132
1436	0.832
1437	0.885
1438	0.821
1439	1.244
1440	1.089
1441	0.978
1442	1.009
1443	0.92
1444	0.992
1445	0.949
1446	0.916
1447	0.834
1448	1.164
1449	1.077
1450	1.196
1451	1.102
1452	0.9
1453	1.144
1454	0.799
1455	0.839
1456	0.531
1457	0.489
1458	0.717
1459	0.825
1460	1.048
1461	0.655
1462	0.864
1463	0.622
1464	0.889
1465	0.981
1466	0.989
1467	0.931
1468	-0.021
1469	0.004
1470	0.044
1471	0.346
1472	0.474
1473	0.543
1474	0.765
1475	0.925
1476	1.124
1477	1.091
1478	1.282
1479	1.133
1480	0.745
1481	0.89
1482	0.872
1483	0.892
1484	0.876
1485	1.041
1486	1.278
1487	1.103
1488	1.088
1489	1.158
1490	1.209
1491	1.066
1492	1.142
1493	1.092
1494	0.764
1495	1.15
1496	1.002
1497	1.016
1498	0.941
1499	1.143
1500	0.898
1501	0.926
1502	1.035
1503	1.005
1504	1.134
1505	1.131
1506	1.176
1507	1.077
1508	1.083
1509	1.239
1510	0.778
1511	0.714
1512	1.098
1513	0.972
1514	1.031
1515	1.446
1516	0.851
1517	1.139
1518	1.104
1519	1.2
1520	1.08
1521	0.99
1522	1.338
1523	1.014
1524	1.487
1525	1.343
1526	1.249
1527	1.126
1528	1.344
1529	1.346
1530	1.358
1531	1.204
1532	1.523
1533	1.239
1534	1.398
1535	1.288
1536	1.166
1537	1.31
1538	1.175
1539	1.37
1540	1.579
1541	1.749
1542	1.448
1543	1.369
1544	1.226
1545	1.292
1546	1.355
1547	1.531
1548	1.232
1549	1.294
1550	1.163
1551	1.325
1552	1.342
1553	1.278
1554	1.27
1555	0.679
1556	1.08
1557	1.209
1558	1.238
1559	0.984
1560	0.955
1561	1.245
1562	1.17
1563	1.187
1564	0.916
1565	0.856
1566	1.116
1567	1.172
1568	1.299
1569	1.252
1570	1.199
1571	0.87
1572	0.745
1573	0.812
1574	1.183
1575	1.227
1576	1.159
1577	1.099
1578	0.86
1579	1.164
1580	1.096
1581	1.272
1582	0.843
1583	0.799
1584	1.284
1585	1.187
1586	1.08
1587	1.102
1588	1.084
1589	1.079
1590	1.408
1591	1.385
1592	0.996
1593	1.122
1594	1.218
1595	1.161
1596	1.279
1597	1.039
1598	1.115
1599	0.59
1600	0.859
1601	0.986
1602	1.014
1603	1.087
1604	0.773
1605	0.831
1606	1.019
1607	0.785
1608	0.853
1609	1.323
1610	1.255
1611	1.024
1612	0.775
1613	1.118
1614	1.14
1615	1.157
1616	1.03
1617	1.076
1618	1.017
1619	1.135
1620	1.297
1621	1.089
1622	1.399
1623	1.315
1624	1.169
1625	1.17
1626	1.093
1627	0.893
1628	1.086
1629	0.789
1630	0.985
1631	1.051
1632	0.785
1633	1.161
1634	1.181
1635	1.016
1636	1.219
1637	1.284
1638	1.184
1639	0.946
1640	0.887
1641	0.88
1642	1.162
1643	1.191
1644	1.192
1645	1.304
1646	1.093
1647	1.091
1648	1.16
1649	1.342
1650	0.96
1651	0.777
1652	0.532
1653	0.687
1654	0.806
1655	0.86
1656	0.996
1657	0.928
1658	1.049
1659	1.036
1660	1.004
1661	0.86
1662	0.816
1663	0.914
1664	0.657
1665	0.466
1666	0.574
1667	0.545
1668	0.608
1669	0.694
1670	0.555
1671	0.754
1672	0.565
1673	0.702
1674	0.819
1675	0.665
1676	0.692
1677	0.768
1678	0.824
1679	0.633
1680	0.805
1681	0.927
1682	0.861
1683	0.918
1684	1.017
1685	0.895
1686	0.651
1687	0.776
1688	0.802
1689	0.662
1690	0.709
1691	0.922
1692	0.853
1693	0.546
1694	1.028
1695	0.73
1696	0.836
1697	1.019
1698	0.709
1699	0.278
1700	0.531
1701	0.656
1702	0.663
1703	0.812
1704	0.9
1705	0.941
1706	0.866
1707	0.768
1708	0.893
1709	1.135
1710	0.831
1711	1.184
1712	0.934
1713	1.109
1714	1.101
1715	1.007
1716	1.027
1717	1.12
1718	0.381
1719	0.538
1720	0.783
1721	0.781
1722	0.652
1723	0.869
1724	0.604
1725	0.678
1726	0.738
1727	0.826
1728	0.784
1729	0.746
1730	0.935
1731	0.946
1732	1.018
1733	0.906
1734	0.67
1735	1.255
1736	1.063
1737	0.737
1738	0.667
1739	0.763
1740	0.955
1741	1.023
1742	0.844
1743	0.875
1744	1.079
1745	0.917
1746	0.969
1747	0.657
1748	0.674
1749	0.829
1750	1.007
1751	0.796
1752	0.859
1753	0.894
1754	0.949
1755	0.437
1756	0.705
1757	1.044
1758	1.02
1759	1.196
1760	1.108
1761	1.091
1762	1.16
1763	1.101
1764	1.339
1765	1.091
1766	0.506
1767	0.65
1768	0.42
1769	0.611
1770	0.6
1771	0.711
1772	0.575
1773	0.738
1774	0.691
1775	0.551
1776	0.596
1777	0.716
1778	0.755
1779	0.658
1780	0.657
1781	0.867
1782	0.922
1783	0.84
1784	0.73
1785	0.721
1786	0.784
1787	0.783
1788	0.811
1789	0.877
1790	0.977
1791	0.961
1792	0.643
1793	0.729
1794	0.868
1795	0.814
1796	0.855
1797	1.028
1798	0.861
1799	0.919
1800	1.076
1801	1.101
1802	1.091
1803	0.852
1804	1.147
1805	0.808
1806	1.291
1807	1.098
1808	1.238
1809	1.292
1810	0.927
1811	0.956
1812	0.868
1813	0.902
1814	0.803
1815	0.677
1816	0.745
1817	1.008
1818	0.689
1819	0.802
1820	0.795
1821	0.802
1822	0.988
1823	1.121
1824	0.841
1825	0.703
1826	1.317
1827	1.134
1828	1.415
1829	1.5
1830	1.132
1831	1.093
1832	1.359
1833	0.812
1834	1.071
1835	1.242
1836	1.22
1837	1.044
1838	1.191
1839	1.106
1840	0.926
1841	0.884
1842	0.967
1843	0.804
1844	1.055
1845	0.925
1846	0.992
1847	1.056
1848	1.119
1849	1.302
1850	0.972
1851	0.65
1852	0.782
1853	0.949
1854	1.018
1855	1.038
1856	0.915
1857	1.091
1858	0.899
1859	0.907
1860	0.744
1861	0.976
1862	0.821
1863	1.124
1864	0.908
1865	0.688
1866	0.826
1867	0.656
1868	1.058
1869	0.96
1870	1
1871	1.058
1872	1.029
1873	1.01
1874	1.024
1875	0.953
1876	1.076
1877	0.309
1878	0.691
1879	0.785
1880	0.808
1881	0.657
1882	0.914
1883	0.764
1884	1.036
1885	0.818
1886	1.166
1887	0.931
1888	0.617
1889	0.868
1890	0.875
1891	0.851
1892	0.9
1893	0.909
1894	0.853
1895	1.001
1896	1.107
1897	0.845
1898	0.731
1899	1.14
1900	1.021
1901	1.438
1902	1.034
1903	1.484
1904	1.24
1905	1.322
1906	1.42
1907	1.445
1908	1.107
1909	1.24
1910	1.192
1911	0.783
1912	0.858
1913	0.873
1914	0.698
1915	0.828
1916	0.974
1917	0.902
1918	0.851
1919	0.528
1920	0.776
1921	1.053
1922	0.994
1923	0.86
1924	1.083
1925	0.963
1926	1.018
1927	0.819
1928	1.035
1929	1.129
1930	0.972
1931	0.967
1932	1.118
1933	1.116
1934	1.027
1935	1.253
1936	0.622
1937	0.946
1938	1.027
1939	1.165
1940	1.157
1941	1.144
1942	1.047
1943	1.184
1944	0.833
1945	0.99
1946	1.607
1947	1.542
1948	1.293
1949	1.231
1950	1.036
1951	1.351
1952	1.323
1953	1.096
1954	1.206
1955	0.953
1956	1.109
1957	0.96
1958	1.004
1959	1.11
1960	0.78
1961	0.9
1962	1.096
1963	1.147
1964	1.214
1965	1.031
1966	1.308
1967	1.043
1968	1.18
1969	1.182
1970	1.344
1971	1.56
1972	1.356
1973	1.401
1974	1.398
1975	1.096
1976	1.52
1977	1.474
1978	0.951
1979	0.81
1980	1.257
1981	1.414
1982	1.383
1983	1.18
1984	1.324
1985	1.279
1986	1.268
1987	1.33
1988	1.427
1989	1.608
1990	1.188
1991	1.447