# southamerica_arge090 - RÃÂ­o Horqueta 2 - 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/5188
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge090 - RÃÂ­o Horqueta 2 - 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 Horqueta 2
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -41.83
#	Southernmost_Latitude: -41.83
#	Easternmost_Longitude: -71.78
#	Westernmost_Longitude: -71.78
#	Elevation: 1230 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge090B
#	Earliest_Year: 574
#	Most_Recent_Year: 1993
#	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":"2.78808085901","T2":"14.6820340991","M1":"0.023116427275","M2":"0.503301033085"}} 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
574	1.045
575	0.811
576	0.909
577	0.781
578	0.878
579	0.836
580	0.847
581	0.848
582	0.881
583	0.926
584	1.122
585	0.732
586	0.776
587	0.864
588	0.854
589	0.866
590	0.965
591	1.033
592	1.001
593	0.935
594	0.759
595	0.904
596	0.849
597	1.162
598	1.119
599	1.008
600	1.178
601	0.91
602	0.989
603	0.957
604	1.037
605	0.778
606	0.642
607	0.722
608	0.905
609	0.86
610	0.815
611	0.942
612	0.897
613	1.025
614	1.072
615	0.923
616	1.271
617	1.041
618	0.95
619	1.09
620	1.138
621	0.964
622	1.317
623	0.955
624	1.015
625	1.063
626	0.852
627	0.758
628	0.913
629	0.878
630	0.915
631	1.238
632	1.096
633	1.098
634	1.111
635	1.064
636	0.921
637	0.91
638	1.044
639	1.179
640	1.156
641	0.89
642	0.708
643	0.72
644	0.819
645	0.906
646	0.919
647	0.883
648	0.959
649	0.861
650	0.862
651	1.049
652	0.926
653	1.002
654	1.028
655	0.891
656	0.88
657	0.856
658	0.996
659	0.946
660	0.871
661	0.936
662	0.822
663	0.785
664	0.939
665	0.812
666	0.645
667	0.749
668	0.944
669	0.984
670	1.18
671	1.078
672	0.883
673	1.028
674	1.03
675	1.11
676	1.196
677	1.345
678	1.343
679	1.221
680	1.436
681	1.203
682	1.449
683	1.507
684	1.218
685	1.21
686	1.09
687	1.205
688	0.954
689	1.236
690	1.205
691	1.252
692	1.087
693	1.361
694	0.725
695	0.748
696	0.836
697	0.836
698	1.007
699	0.967
700	1.351
701	1.242
702	1.223
703	1.094
704	1.094
705	1.208
706	0.566
707	0.464
708	0.518
709	0.86
710	1.072
711	1.323
712	0.927
713	0.748
714	0.98
715	0.684
716	0.668
717	1.066
718	0.865
719	0.837
720	1.227
721	1.294
722	1.296
723	1.033
724	0.78
725	0.705
726	0.639
727	0.981
728	0.64
729	0.508
730	0.837
731	0.665
732	0.78
733	0.752
734	0.892
735	0.393
736	0.56
737	0.577
738	0.919
739	0.982
740	0.742
741	0.58
742	0.813
743	0.861
744	1.011
745	0.896
746	0.631
747	0.849
748	0.867
749	0.666
750	0.522
751	0.633
752	0.566
753	0.786
754	0.522
755	0.694
756	0.625
757	0.676
758	0.902
759	0.902
760	0.599
761	0.789
762	0.451
763	0.462
764	0.516
765	0.625
766	0.708
767	0.674
768	0.525
769	0.442
770	0.568
771	0.809
772	0.751
773	0.696
774	0.67
775	0.796
776	0.789
777	0.646
778	0.655
779	0.57
780	0.881
781	0.99
782	0.52
783	0.655
784	0.826
785	0.632
786	0.73
787	1.033
788	0.926
789	0.885
790	0.869
791	0.879
792	1.29
793	1.074
794	1.135
795	1.338
796	0.614
797	0.719
798	1.037
799	0.917
800	1.062
801	1.101
802	0.93
803	0.85
804	1.067
805	1.008
806	1.411
807	0.906
808	0.776
809	0.736
810	0.945
811	0.731
812	1.127
813	0.8
814	0.994
815	1.196
816	1.353
817	1.385
818	1.155
819	1.022
820	0.99
821	0.92
822	0.944
823	1.163
824	0.926
825	1.2
826	1
827	1.19
828	1.075
829	0.854
830	0.93
831	0.818
832	1.039
833	0.988
834	0.544
835	0.922
836	0.684
837	0.881
838	1.139
839	1.078
840	1.163
841	1.071
842	0.871
843	1.024
844	0.946
845	0.906
846	1.101
847	1.097
848	0.423
849	0.463
850	0.7
851	0.912
852	0.96
853	1.013
854	1.082
855	0.867
856	0.785
857	1.159
858	1.225
859	1.124
860	1.258
861	1.258
862	1.294
863	1.295
864	1.391
865	0.929
866	0.848
867	0.71
868	0.784
869	0.695
870	0.938
871	1.119
872	0.846
873	0.819
874	0.863
875	1.061
876	1.052
877	0.956
878	0.998
879	1.129
880	1.203
881	1.099
882	0.995
883	1.176
884	0.376
885	0.501
886	0.811
887	0.881
888	0.888
889	0.678
890	0.758
891	0.841
892	0.995
893	0.813
894	1.09
895	1.014
896	0.98
897	1.121
898	1.045
899	1.043
900	0.982
901	1.023
902	0.84
903	0.967
904	0.838
905	0.818
906	0.968
907	0.995
908	1.175
909	1.121
910	1.002
911	0.506
912	1.014
913	0.692
914	0.501
915	0.772
916	0.488
917	0.702
918	0.835
919	1.03
920	1.155
921	1.234
922	1.242
923	1.111
924	0.879
925	0.925
926	0.431
927	0.842
928	0.697
929	0.674
930	0.268
931	0.381
932	0.473
933	0.461
934	0.558
935	0.774
936	1.009
937	1.007
938	0.997
939	0.948
940	0.625
941	1.031
942	1.107
943	1.16
944	1.156
945	1.236
946	1.441
947	1.334
948	1.174
949	1.181
950	1.287
951	1.16
952	1.296
953	1.037
954	0.891
955	1.044
956	0.994
957	0.86
958	1.053
959	0.721
960	0.855
961	0.959
962	0.948
963	0.942
964	0.821
965	0.84
966	0.542
967	0.92
968	0.948
969	1.026
970	0.908
971	1.006
972	1.014
973	1.175
974	1.31
975	1.318
976	1.344
977	1.527
978	1.523
979	1.443
980	1.312
981	0.652
982	0.785
983	0.907
984	1.218
985	1.154
986	0.994
987	1.244
988	1.496
989	1.505
990	0.968
991	1.148
992	1.305
993	1.067
994	1.381
995	1.405
996	1.198
997	1.31
998	0.875
999	1.197
1000	0.899
1001	1.039
1002	0.939
1003	1.38
1004	1.292
1005	1.067
1006	0.791
1007	1.199
1008	0.966
1009	1.179
1010	1.181
1011	1.554
1012	1.235
1013	0.843
1014	0.653
1015	0.797
1016	0.736
1017	0.966
1018	1.164
1019	1.266
1020	1.353
1021	1.129
1022	1.144
1023	1.148
1024	1.215
1025	1.052
1026	1.027
1027	0.814
1028	0.842
1029	0.829
1030	0.339
1031	0.522
1032	0.693
1033	0.682
1034	0.929
1035	0.972
1036	1.044
1037	1.148
1038	1.032
1039	0.949
1040	1.159
1041	1.249
1042	1.259
1043	1.318
1044	0.808
1045	0.904
1046	0.907
1047	0.822
1048	0.893
1049	0.928
1050	0.881
1051	0.989
1052	0.862
1053	0.803
1054	1.127
1055	1.115
1056	1.061
1057	0.973
1058	1.218
1059	0.985
1060	0.887
1061	1.048
1062	1.194
1063	1.043
1064	1.049
1065	1.158
1066	1.392
1067	1.206
1068	0.954
1069	1.077
1070	0.828
1071	0.859
1072	0.952
1073	0.855
1074	0.901
1075	0.819
1076	0.824
1077	1.068
1078	1.12
1079	1.089
1080	1.067
1081	0.994
1082	0.974
1083	0.976
1084	0.96
1085	0.974
1086	1.008
1087	0.822
1088	0.889
1089	0.888
1090	0.872
1091	0.888
1092	0.983
1093	1.134
1094	1.163
1095	1.556
1096	0.865
1097	0.836
1098	1.051
1099	1.186
1100	1.041
1101	1.006
1102	1.124
1103	1.039
1104	0.998
1105	1.034
1106	1.198
1107	1.107
1108	0.892
1109	1.334
1110	1.031
1111	1.132
1112	0.857
1113	0.744
1114	0.935
1115	1.133
1116	1.035
1117	1.012
1118	0.744
1119	1.186
1120	1.231
1121	1.188
1122	1.013
1123	1.094
1124	0.949
1125	1.029
1126	0.985
1127	1.263
1128	0.998
1129	1.085
1130	0.96
1131	0.921
1132	0.842
1133	1.048
1134	0.85
1135	1.082
1136	1.071
1137	1.295
1138	1.099
1139	0.945
1140	1.06
1141	0.724
1142	0.755
1143	0.66
1144	0.805
1145	0.77
1146	0.812
1147	0.981
1148	1.101
1149	1.14
1150	1.228
1151	0.967
1152	1.186
1153	1.069
1154	1.174
1155	1.161
1156	1.181
1157	1.06
1158	0.791
1159	0.981
1160	1.035
1161	1.409
1162	1.083
1163	0.792
1164	0.806
1165	0.924
1166	1.216
1167	1.151
1168	1.189
1169	1.224
1170	1.128
1171	1.089
1172	0.728
1173	0.905
1174	0.939
1175	1.062
1176	0.934
1177	0.959
1178	0.975
1179	1.051
1180	1.07
1181	0.926
1182	1.079
1183	0.937
1184	0.795
1185	1.184
1186	1.393
1187	1.214
1188	1.66
1189	1.531
1190	1.534
1191	1.611
1192	1.45
1193	1.565
1194	0.747
1195	0.913
1196	1.009
1197	0.905
1198	0.927
1199	1.011
1200	1.166
1201	1.022
1202	0.974
1203	1.017
1204	0.927
1205	0.803
1206	0.885
1207	1.085
1208	0.686
1209	0.868
1210	0.954
1211	0.751
1212	0.946
1213	0.872
1214	0.838
1215	0.879
1216	1.127
1217	1.316
1218	0.952
1219	1.244
1220	1.029
1221	1.262
1222	1.393
1223	1.561
1224	1.236
1225	1.337
1226	0.903
1227	0.988
1228	1.036
1229	1.265
1230	1.004
1231	1.098
1232	0.797
1233	0.936
1234	0.859
1235	0.891
1236	0.896
1237	0.836
1238	0.898
1239	0.767
1240	0.842
1241	0.979
1242	0.969
1243	0.603
1244	1.066
1245	0.886
1246	0.893
1247	0.945
1248	0.986
1249	0.883
1250	0.701
1251	0.714
1252	1
1253	0.722
1254	0.891
1255	0.83
1256	0.785
1257	1.252
1258	1.389
1259	1.422
1260	1.112
1261	0.863
1262	1.219
1263	1.316
1264	0.951
1265	1.004
1266	0.691
1267	1.001
1268	0.74
1269	1.084
1270	0.861
1271	0.781
1272	0.746
1273	0.821
1274	1.132
1275	0.844
1276	0.916
1277	1.113
1278	0.628
1279	0.625
1280	0.854
1281	0.858
1282	0.883
1283	0.479
1284	0.614
1285	1.086
1286	0.96
1287	1.064
1288	0.879
1289	1.006
1290	1.194
1291	1.04
1292	0.827
1293	0.845
1294	0.872
1295	0.856
1296	1.05
1297	1.016
1298	0.898
1299	0.827
1300	0.734
1301	0.575
1302	1.197
1303	0.919
1304	1.016
1305	1.076
1306	0.929
1307	0.937
1308	1.012
1309	0.913
1310	1.041
1311	0.686
1312	0.827
1313	0.814
1314	0.874
1315	0.89
1316	1.014
1317	0.978
1318	0.574
1319	0.727
1320	0.986
1321	0.762
1322	0.514
1323	0.796
1324	0.71
1325	0.692
1326	0.914
1327	0.687
1328	0.816
1329	1.019
1330	0.711
1331	0.945
1332	0.861
1333	1.04
1334	1.104
1335	1.184
1336	1.062
1337	0.826
1338	0.942
1339	1.036
1340	1.032
1341	1.294
1342	1.266
1343	1.147
1344	1.356
1345	1.273
1346	0.796
1347	0.828
1348	0.883
1349	0.902
1350	0.944
1351	1.088
1352	0.812
1353	0.785
1354	0.947
1355	0.769
1356	0.571
1357	0.771
1358	0.798
1359	0.607
1360	0.789
1361	1.01
1362	1.106
1363	1.135
1364	1.162
1365	1.122
1366	1.186
1367	1.24
1368	1.213
1369	1.368
1370	1.353
1371	1.28
1372	1.42
1373	1.245
1374	0.892
1375	1.134
1376	1.027
1377	1.219
1378	1.086
1379	1.062
1380	1.102
1381	0.966
1382	1.1
1383	1.107
1384	1.174
1385	0.875
1386	0.452
1387	0.735
1388	0.645
1389	0.606
1390	0.835
1391	0.412
1392	0.498
1393	0.725
1394	0.496
1395	0.571
1396	0.527
1397	0.905
1398	1.005
1399	0.624
1400	0.736
1401	0.76
1402	0.685
1403	0.857
1404	0.818
1405	0.908
1406	0.788
1407	0.952
1408	0.894
1409	0.761
1410	1.043
1411	0.859
1412	0.702
1413	1.046
1414	1.038
1415	1.076
1416	1.137
1417	0.971
1418	0.962
1419	0.988
1420	1.01
1421	1.216
1422	1.238
1423	1.275
1424	1.219
1425	1.12
1426	1.388
1427	1.142
1428	1.124
1429	1.416
1430	1.176
1431	0.809
1432	1.076
1433	1.152
1434	0.95
1435	0.973
1436	0.738
1437	0.849
1438	0.96
1439	1.128
1440	1.273
1441	1.018
1442	1.156
1443	1.133
1444	1.038
1445	1.147
1446	1.088
1447	1.195
1448	1.277
1449	1.145
1450	1.047
1451	1.091
1452	1.063
1453	1.115
1454	0.911
1455	0.691
1456	0.773
1457	0.738
1458	0.869
1459	0.719
1460	1.012
1461	0.709
1462	0.839
1463	0.78
1464	1.183
1465	0.896
1466	0.9
1467	0.885
1468	0.145
1469	0.07
1470	0.059
1471	0.18
1472	0.236
1473	0.219
1474	0.265
1475	0.341
1476	0.502
1477	0.673
1478	0.782
1479	0.773
1480	0.473
1481	0.484
1482	0.635
1483	0.486
1484	0.328
1485	0.685
1486	0.764
1487	0.805
1488	0.828
1489	0.695
1490	0.936
1491	1.068
1492	1.147
1493	0.763
1494	0.672
1495	0.936
1496	0.831
1497	0.867
1498	0.973
1499	1.173
1500	0.798
1501	0.974
1502	1.243
1503	1.21
1504	1.101
1505	1.263
1506	1.177
1507	1.093
1508	1.046
1509	1.394
1510	0.792
1511	0.602
1512	1.032
1513	0.949
1514	0.768
1515	1.269
1516	0.984
1517	0.996
1518	1.016
1519	1.017
1520	0.916
1521	0.787
1522	0.975
1523	1.04
1524	1.3
1525	1.087
1526	1.153
1527	0.877
1528	1.066
1529	1.02
1530	1.132
1531	1.203
1532	1.368
1533	1.428
1534	1.393
1535	1.264
1536	1.375
1537	1.327
1538	1.117
1539	0.964
1540	1.188
1541	1.195
1542	1.284
1543	1.008
1544	1.138
1545	1.182
1546	1.109
1547	1.314
1548	1.309
1549	1.267
1550	1.291
1551	1.163
1552	1.129
1553	1.175
1554	1.283
1555	0.719
1556	0.946
1557	0.965
1558	1.198
1559	1.073
1560	0.865
1561	1.219
1562	1.154
1563	1.005
1564	0.664
1565	0.541
1566	0.631
1567	0.67
1568	0.856
1569	0.93
1570	1.156
1571	0.945
1572	0.91
1573	0.909
1574	1.03
1575	1.251
1576	1.021
1577	1.272
1578	1.129
1579	1.154
1580	1.198
1581	1.411
1582	1.093
1583	0.929
1584	1.201
1585	1.29
1586	1.211
1587	1.291
1588	1.295
1589	1.178
1590	1.116
1591	1.236
1592	1.17
1593	1.063
1594	1.117
1595	1.089
1596	1.48
1597	0.836
1598	0.926
1599	0.91
1600	1.024
1601	1.113
1602	1.251
1603	1.196
1604	0.884
1605	0.693
1606	0.903
1607	0.799
1608	0.676
1609	1.073
1610	0.905
1611	0.969
1612	0.79
1613	0.923
1614	1.038
1615	1.299
1616	1.084
1617	1.085
1618	1.169
1619	1.316
1620	1.49
1621	1.143
1622	1.172
1623	1.13
1624	1.203
1625	1.301
1626	1.216
1627	1.109
1628	1.066
1629	1.035
1630	1.102
1631	1.144
1632	1.032
1633	1.237
1634	1.044
1635	1.028
1636	1.038
1637	1.146
1638	1.201
1639	1.281
1640	1.009
1641	1.213
1642	1.214
1643	1.237
1644	1.328
1645	1.281
1646	1.383
1647	1.218
1648	1.429
1649	1.28
1650	1.313
1651	1.136
1652	1.043
1653	0.924
1654	1.256
1655	0.905
1656	0.903
1657	0.954
1658	1.033
1659	0.94
1660	1.111
1661	1.092
1662	1.133
1663	1.197
1664	1.253
1665	0.762
1666	0.802
1667	0.942
1668	0.866
1669	0.973
1670	0.735
1671	0.859
1672	0.881
1673	0.819
1674	0.708
1675	0.894
1676	0.925
1677	0.96
1678	1.055
1679	0.8
1680	0.969
1681	1.043
1682	1.022
1683	0.932
1684	1.115
1685	0.933
1686	0.955
1687	1.074
1688	0.961
1689	0.927
1690	0.811
1691	1.078
1692	0.958
1693	0.532
1694	0.947
1695	0.678
1696	0.521
1697	0.694
1698	0.653
1699	0.485
1700	0.413
1701	0.52
1702	0.457
1703	0.517
1704	0.585
1705	0.93
1706	1.004
1707	0.941
1708	1.063
1709	1.222
1710	1.074
1711	1.163
1712	1.039
1713	1.08
1714	0.983
1715	1.01
1716	1.017
1717	1.072
1718	0.529
1719	0.651
1720	0.646
1721	0.751
1722	0.691
1723	0.754
1724	0.494
1725	0.748
1726	0.774
1727	0.982
1728	0.909
1729	0.916
1730	0.924
1731	1.037
1732	1.417
1733	1.126
1734	0.704
1735	0.966
1736	1.23
1737	0.709
1738	0.697
1739	0.792
1740	0.771
1741	0.764
1742	0.63
1743	0.64
1744	0.807
1745	0.711
1746	0.813
1747	0.653
1748	0.41
1749	0.488
1750	0.538
1751	0.472
1752	0.566
1753	0.525
1754	0.619
1755	0.565
1756	0.499
1757	0.7
1758	0.73
1759	0.965
1760	0.714
1761	0.635
1762	0.692
1763	0.846
1764	0.981
1765	0.822
1766	0.594
1767	0.734
1768	0.565
1769	0.654
1770	0.551
1771	0.536
1772	0.4
1773	0.512
1774	0.52
1775	0.495
1776	0.394
1777	0.48
1778	0.732
1779	0.751
1780	0.762
1781	0.795
1782	0.886
1783	0.863
1784	0.85
1785	0.535
1786	0.761
1787	0.822
1788	0.837
1789	0.928
1790	0.974
1791	0.964
1792	0.83
1793	0.809
1794	1.016
1795	0.886
1796	0.798
1797	1.117
1798	0.869
1799	1.051
1800	1.272
1801	1.348
1802	1.256
1803	1.247
1804	1.418
1805	1.107
1806	1.391
1807	1.048
1808	1.16
1809	1.158
1810	1.049
1811	0.713
1812	0.807
1813	0.807
1814	0.802
1815	0.62
1816	0.467
1817	0.602
1818	0.554
1819	0.342
1820	0.698
1821	0.526
1822	0.89
1823	0.978
1824	0.699
1825	1.014
1826	1.313
1827	1.214
1828	1.503
1829	1.507
1830	1.281
1831	1.325
1832	1.392
1833	1.04
1834	1.35
1835	1.385
1836	1.483
1837	1.334
1838	1.362
1839	1.2
1840	1.126
1841	1.312
1842	1.286
1843	0.904
1844	1.206
1845	0.921
1846	0.953
1847	0.76
1848	0.835
1849	1.252
1850	0.957
1851	0.441
1852	0.656
1853	0.704
1854	0.791
1855	0.814
1856	0.736
1857	0.872
1858	0.976
1859	0.704
1860	0.677
1861	0.993
1862	0.88
1863	1.006
1864	1.163
1865	0.637
1866	0.921
1867	0.888
1868	1.171
1869	1.162
1870	1.244
1871	0.949
1872	1.193
1873	1.174
1874	1.229
1875	1.207
1876	1.132
1877	0.58
1878	0.848
1879	0.661
1880	0.813
1881	0.643
1882	0.756
1883	0.509
1884	1.023
1885	0.934
1886	1.092
1887	1.257
1888	0.89
1889	0.84
1890	1.079
1891	0.941
1892	0.926
1893	0.965
1894	1.248
1895	0.84
1896	1.113
1897	0.964
1898	0.945
1899	0.999
1900	1.135
1901	0.99
1902	0.911
1903	1.278
1904	1.069
1905	1.057
1906	0.828
1907	1.094
1908	1.06
1909	1.239
1910	1.095
1911	0.869
1912	0.895
1913	1.159
1914	0.969
1915	0.791
1916	1.012
1917	1.248
1918	1.061
1919	0.51
1920	0.531
1921	0.669
1922	1.101
1923	0.711
1924	0.861
1925	0.855
1926	1.175
1927	0.929
1928	0.999
1929	1.268
1930	1.091
1931	1.101
1932	1.131
1933	1.313
1934	1.204
1935	1.273
1936	0.983
1937	1.25
1938	1.274
1939	1.469
1940	1.145
1941	1.38
1942	1.244
1943	1.154
1944	0.906
1945	0.882
1946	1.004
1947	1.183
1948	1.263
1949	1.137
1950	1.246
1951	1.19
1952	1.302
1953	1.107
1954	1.119
1955	0.87
1956	1.213
1957	0.921
1958	1.09
1959	1.137
1960	0.557
1961	0.567
1962	0.791
1963	0.734
1964	0.923
1965	0.991
1966	0.964
1967	0.902
1968	1.037
1969	1.049
1970	1.175
1971	0.948
1972	1.37
1973	1.231
1974	1.539
1975	0.768
1976	1.176
1977	1.303
1978	1.163
1979	1.054
1980	1.652
1981	1.299
1982	1.282
1983	1.241
1984	1.23
1985	1.248
1986	1.198
1987	1.111
1988	1.247
1989	1.651
1990	1.077
1991	1.21
1992	0.938
1993	1.084