# southamerica_arge089 - RÃÂ­o Horqueta - 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/5187
#
# Description/Documentation lines begin with #
# Data lines have no #
#
# Archive: Tree Rings
#--------------------
# Contribution_Date
#	Date: 2016-01-07
#--------------------
# Title
#	Study_Name: southamerica_arge089 - RÃÂ­o Horqueta - 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
#	Location:
#	Country: Argentina
#	Northernmost_Latitude: -41.83
#	Southernmost_Latitude: -41.83
#	Easternmost_Longitude: -71.77
#	Westernmost_Longitude: -71.77
#	Elevation: 950 m
#--------------------
# Data_Collection
#	Collection_Name: southamerica_arge089B
#	Earliest_Year: 539
#	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":"2.82712427908","T2":"12.1250842646","M1":"0.0223376102608","M2":"0.589782178961"}}
#--------------------
# 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
539	0.868
540	0.855
541	0.961
542	0.909
543	0.909
544	0.896
545	0.923
546	0.963
547	0.91
548	0.924
549	0.712
550	0.831
551	0.845
552	0.725
553	0.872
554	0.872
555	0.699
556	0.739
557	0.846
558	0.713
559	0.806
560	0.673
561	0.62
562	0.727
563	0.7
564	0.66
565	0.754
566	0.674
567	0.755
568	0.701
569	0.782
570	0.809
571	0.702
572	0.675
573	0.688
574	0.783
575	0.702
576	0.729
577	0.635
578	0.703
579	0.824
580	0.797
581	0.676
582	0.676
583	0.663
584	0.676
585	0.677
586	0.771
587	0.731
588	0.663
589	0.704
590	0.623
591	0.745
592	0.664
593	0.705
594	0.719
595	0.719
596	0.705
597	0.855
598	0.828
599	0.924
600	0.965
601	0.87
602	1.007
603	1.103
604	0.884
605	0.994
606	1.076
607	1.131
608	0.926
609	1.036
610	1.091
611	0.982
612	1.037
613	0.996
614	1.107
615	1.093
616	1.272
617	1.328
618	1.191
619	1.288
620	1.329
621	1.192
622	1.137
623	1.193
624	1.055
625	1.069
626	1.153
627	1.056
628	0.973
629	1.098
630	1.099
631	1.224
632	1.086
633	1.1
634	1.017
635	1.017
636	0.906
637	1.088
638	0.921
639	0.935
640	1.033
641	0.866
642	0.88
643	0.783
644	0.867
645	0.881
646	1.119
647	1.091
648	1.092
649	1.148
650	1.134
651	0.995
652	0.953
653	1.08
654	0.982
655	0.954
656	1.024
657	1.095
658	0.983
659	1.068
660	0.998
661	1.026
662	0.97
663	0.984
664	0.942
665	0.9
666	0.915
667	0.858
668	0.915
669	0.93
670	0.887
671	0.944
672	1.016
673	1.115
674	0.974
675	1.002
676	0.989
677	1.103
678	0.989
679	0.79
680	1.004
681	0.976
682	1.062
683	1.062
684	0.991
685	1.02
686	1.049
687	1.164
688	1.093
689	1.064
690	1.179
691	1.223
692	1.066
693	1.052
694	0.937
695	1.139
696	1.067
697	1.125
698	1.039
699	1.097
700	1.054
701	1.069
702	0.968
703	1.055
704	1.07
705	1.038
706	1.023
707	0.908
708	0.904
709	0.89
710	0.903
711	1.03
712	1.043
713	1.028
714	1.106
715	0.951
716	0.94
717	1.037
718	1.037
719	1.278
720	1.047
721	0.962
722	0.954
723	0.916
724	1.079
725	1.096
726	0.973
727	1.097
728	0.951
729	0.878
730	1.105
731	1.072
732	1.023
733	0.985
734	0.858
735	0.82
736	0.921
737	1.024
738	0.963
739	0.652
740	0.915
741	0.899
742	0.988
743	0.932
744	0.874
745	1.014
746	1.038
747	1.068
748	1.079
749	0.982
750	0.862
751	0.823
752	0.816
753	0.876
754	1.016
755	0.89
756	0.653
757	0.767
758	0.905
759	0.899
760	1.058
761	0.937
762	0.71
763	0.726
764	0.891
765	0.953
766	1.025
767	1.057
768	0.806
769	0.945
770	0.867
771	0.898
772	1.008
773	1.026
774	0.852
775	0.948
776	0.848
777	0.835
778	1.03
779	0.773
780	0.764
781	1.139
782	0.935
783	0.959
784	1.037
785	0.89
786	0.848
787	1.229
788	1.097
789	0.952
790	1.249
791	1.32
792	1.521
793	1.393
794	1.322
795	1.123
796	1.26
797	1.35
798	1.494
799	1.005
800	1.148
801	1.071
802	1.081
803	1.004
804	0.951
805	1.139
806	1.285
807	0.922
808	1.027
809	1.101
810	0.924
811	0.79
812	1.179
813	0.942
814	0.805
815	1.119
816	1.001
817	1.119
818	1.177
819	1.045
820	0.993
821	0.915
822	0.982
823	0.923
824	0.773
825	1.01
826	0.884
827	1.026
828	1.001
829	1.001
830	1.166
831	1.041
832	1.272
833	1.167
834	0.823
835	0.925
836	0.826
837	0.858
838	1.052
839	1.056
840	0.902
841	1.03
842	0.812
843	1.064
844	0.929
845	0.901
846	0.845
847	0.902
848	0.801
849	1.019
850	0.857
851	0.772
852	0.948
853	0.832
854	0.85
855	0.826
856	0.851
857	0.946
858	1.07
859	0.947
860	0.98
861	0.905
862	0.982
863	0.921
864	0.896
865	0.823
866	0.73
867	0.744
868	0.986
869	0.967
870	1.016
871	0.81
872	0.715
873	0.922
874	0.954
875	0.84
876	0.82
877	0.925
878	0.769
879	0.983
880	0.846
881	1.106
882	1.057
883	1.11
884	0.724
885	0.907
886	1.184
887	0.843
888	1.063
889	0.981
890	0.672
891	0.877
892	0.829
893	0.914
894	0.943
895	1.107
896	1.095
897	1.143
898	1.188
899	1.099
900	1.096
901	1.024
902	1.158
903	1.158
904	1.02
905	0.959
906	1.083
907	1.007
908	1.198
909	1.226
910	1.297
911	0.869
912	1.046
913	0.961
914	0.781
915	0.785
916	0.653
917	0.622
918	0.915
919	0.71
920	0.901
921	0.896
922	0.956
923	1.031
924	0.858
925	0.844
926	0.814
927	0.843
928	0.93
929	0.659
930	0.718
931	0.737
932	0.694
933	0.835
934	0.868
935	1.037
936	0.942
937	1.191
938	1.29
939	1.145
940	0.706
941	1.022
942	1.206
943	1.031
944	1.032
945	0.756
946	0.974
947	0.872
948	1.076
949	0.905
950	1.113
951	0.969
952	1.109
953	1.041
954	1.206
955	1.119
956	1.008
957	1.351
958	1.327
959	0.984
960	1.107
961	1.188
962	1.175
963	1.279
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967	1.016
968	1.106
969	1.298
970	0.986
971	0.956
972	1.08
973	1.135
974	1.218
975	1.175
976	1.074
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978	1.427
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983	1.153
984	1.208
985	1.028
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987	1.039
988	1.314
989	1.323
990	1.113
991	1.237
992	1.399
993	1.217
994	1.25
995	1.098
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999	1.079
1000	0.811
1001	1.045
1002	1.069
1003	1.161
1004	1.268
1005	1.153
1006	0.232
1007	0.837
1008	0.846
1009	0.652
1010	1.016
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1012	0.953
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1014	0.894
1015	0.775
1016	1.01
1017	1.157
1018	1.093
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1020	1.203
1021	1.02
1022	1.271
1023	1.236
1024	1.251
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1028	1.147
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1030	0.219
1031	0.79
1032	0.947
1033	0.913
1034	1.145
1035	0.946
1036	0.929
1037	0.954
1038	0.659
1039	0.863
1040	0.949
1041	0.807
1042	1.007
1043	0.994
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1045	1.174
1046	1.115
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1048	1.074
1049	1.08
1050	1.082
1051	1.035
1052	0.962
1053	1.088
1054	1.182
1055	1.265
1056	1.406
1057	1.586
1058	1.613
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1063	1.341
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1080	0.967
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1096	0.817
1097	1
1098	1.15
1099	1.054
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1101	0.913
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1103	0.919
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1162	1.029
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1165	1.168
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1168	1.024
1169	1.332
1170	1.341
1171	1.194
1172	1.03
1173	1.044
1174	1.028
1175	1.038
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1177	0.861
1178	1.134
1179	0.957
1180	0.812
1181	0.851
1182	1.168
1183	0.886
1184	1
1185	0.756
1186	0.774
1187	0.576
1188	0.908
1189	0.832
1190	1.078
1191	0.997
1192	1.054
1193	1.001
1194	0.757
1195	0.715
1196	0.842
1197	0.517
1198	0.911
1199	0.611
1200	0.823
1201	0.832
1202	0.832
1203	1.094
1204	0.727
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1206	0.754
1207	0.987
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1209	1.028
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1211	0.897
1212	0.91
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1214	0.852
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1220	0.571
1221	0.564
1222	0.791
1223	0.958
1224	0.547
1225	0.967
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1227	1.068
1228	1.316
1229	1.219
1230	1.263
1231	1.325
1232	0.925
1233	0.97
1234	0.733
1235	0.508
1236	0.767
1237	0.628
1238	0.689
1239	0.866
1240	0.884
1241	1.052
1242	0.87
1243	0.543
1244	0.935
1245	0.732
1246	0.677
1247	0.762
1248	0.818
1249	0.936
1250	0.75
1251	0.89
1252	1.105
1253	0.843
1254	0.835
1255	0.935
1256	0.755
1257	1.261
1258	1.248
1259	1.092
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1261	0.86
1262	0.928
1263	1.007
1264	0.741
1265	0.985
1266	0.738
1267	1.047
1268	0.95
1269	1.095
1270	0.807
1271	0.735
1272	0.855
1273	0.769
1274	1.031
1275	0.911
1276	1.139
1277	1.124
1278	0.667
1279	0.814
1280	0.861
1281	0.7
1282	0.84
1283	0.546
1284	0.797
1285	1.164
1286	1.129
1287	1.236
1288	0.949
1289	0.955
1290	1.091
1291	1.177
1292	0.797
1293	0.827
1294	0.925
1295	0.907
1296	1.041
1297	1.146
1298	1.149
1299	1.209
1300	0.981
1301	0.983
1302	1.66
1303	1.317
1304	1.363
1305	1.412
1306	1.183
1307	1.237
1308	1.356
1309	1.383
1310	1.377
1311	0.534
1312	0.787
1313	0.565
1314	0.835
1315	1.023
1316	1.1
1317	1.079
1318	0.66
1319	0.889
1320	1.137
1321	0.875
1322	0.674
1323	0.859
1324	0.826
1325	0.694
1326	1.145
1327	0.972
1328	0.923
1329	0.898
1330	0.928
1331	1.02
1332	0.803
1333	1.034
1334	1.011
1335	1.2
1336	1.13
1337	0.971
1338	0.935
1339	1.203
1340	0.82
1341	1.102
1342	1.045
1343	1.015
1344	1.113
1345	1.248
1346	0.852
1347	0.838
1348	0.952
1349	0.982
1350	1.026
1351	1.295
1352	1.109
1353	1.074
1354	1.149
1355	0.872
1356	0.696
1357	0.761
1358	0.855
1359	0.668
1360	0.767
1361	0.938
1362	0.963
1363	1.028
1364	1.196
1365	1.244
1366	1.06
1367	1.267
1368	1.13
1369	1.212
1370	1.26
1371	1.047
1372	1.178
1373	0.846
1374	0.724
1375	0.926
1376	0.808
1377	0.998
1378	0.829
1379	0.894
1380	1.041
1381	0.795
1382	0.905
1383	1.034
1384	0.799
1385	0.54
1386	0.228
1387	0.603
1388	0.485
1389	0.496
1390	0.694
1391	0.455
1392	0.637
1393	0.672
1394	0.567
1395	0.618
1396	0.481
1397	0.662
1398	0.615
1399	0.381
1400	0.646
1401	0.626
1402	0.608
1403	0.653
1404	0.633
1405	0.879
1406	0.602
1407	0.818
1408	0.924
1409	0.842
1410	1.073
1411	0.898
1412	0.798
1413	1.117
1414	0.91
1415	0.849
1416	1.027
1417	0.976
1418	0.996
1419	1.006
1420	0.873
1421	0.98
1422	1.072
1423	0.988
1424	0.741
1425	0.731
1426	1.163
1427	0.999
1428	1.011
1429	1.236
1430	0.894
1431	0.725
1432	0.916
1433	1.041
1434	0.937
1435	0.945
1436	0.738
1437	0.777
1438	0.832
1439	1.216
1440	1.217
1441	0.96
1442	1.016
1443	0.697
1444	0.921
1445	0.815
1446	0.687
1447	0.768
1448	1.113
1449	0.865
1450	1.02
1451	1.094
1452	0.973
1453	1.297
1454	0.907
1455	0.79
1456	0.763
1457	0.696
1458	0.751
1459	0.669
1460	1.056
1461	0.79
1462	0.857
1463	0.859
1464	1.169
1465	0.912
1466	1.107
1467	0.971
1468	0.114
1469	0.13
1470	0.231
1471	0.476
1472	0.658
1473	0.647
1474	0.839
1475	0.945
1476	0.977
1477	0.935
1478	1.073
1479	0.886
1480	0.391
1481	0.62
1482	0.685
1483	0.446
1484	0.287
1485	0.479
1486	0.586
1487	0.68
1488	0.73
1489	0.87
1490	0.94
1491	1.127
1492	1.056
1493	0.958
1494	0.881
1495	1.172
1496	1.022
1497	0.93
1498	1.037
1499	1.152
1500	0.935
1501	1.084
1502	1.007
1503	1.115
1504	0.849
1505	1.114
1506	1.085
1507	1.122
1508	1.272
1509	1.538
1510	0.975
1511	0.969
1512	1.251
1513	0.929
1514	0.899
1515	1.239
1516	0.804
1517	0.933
1518	0.899
1519	1.151
1520	0.948
1521	0.908
1522	1.089
1523	0.958
1524	1.463
1525	1.157
1526	1.229
1527	1.072
1528	1.336
1529	1.061
1530	0.978
1531	1.158
1532	1.345
1533	1.577
1534	1.445
1535	1.417
1536	1.357
1537	1.426
1538	0.999
1539	0.767
1540	1.057
1541	1.199
1542	1.185
1543	1.148
1544	1.001
1545	1.079
1546	1.297
1547	1.239
1548	1.214
1549	1.141
1550	1.217
1551	1.236
1552	1.434
1553	1.419
1554	1.309
1555	0.731
1556	1.051
1557	0.996
1558	1.113
1559	1.022
1560	0.971
1561	1.224
1562	1.207
1563	1.146
1564	0.752
1565	1.046
1566	1.206
1567	1.217
1568	1.283
1569	1.241
1570	1.343
1571	0.979
1572	0.904
1573	1.074
1574	1.283
1575	1.241
1576	1.115
1577	1.224
1578	1.043
1579	1.146
1580	1.005
1581	1.182
1582	0.735
1583	0.739
1584	0.989
1585	1.146
1586	1.284
1587	1.264
1588	1.249
1589	1.168
1590	1.462
1591	1.276
1592	1.131
1593	1.505
1594	1.391
1595	1.427
1596	1.606
1597	1.122
1598	1.259
1599	0.757
1600	0.747
1601	1.019
1602	1.067
1603	1.111
1604	0.8
1605	0.884
1606	1.228
1607	0.992
1608	0.818
1609	1.403
1610	1.209
1611	1.155
1612	0.823
1613	1.07
1614	1.215
1615	1.201
1616	1.037
1617	1.031
1618	1.13
1619	1.166
1620	1.507
1621	1.208
1622	1.125
1623	1.13
1624	1.119
1625	1.333
1626	1.019
1627	0.884
1628	1.121
1629	1.049
1630	1.285
1631	1.082
1632	0.81
1633	1.124
1634	0.926
1635	0.981
1636	1.259
1637	1.2
1638	1.241
1639	0.962
1640	0.997
1641	1.124
1642	1.117
1643	1.085
1644	1.699
1645	1.373
1646	1.133
1647	1.156
1648	1.262
1649	1.399
1650	1.096
1651	0.865
1652	1.073
1653	0.757
1654	1.299
1655	0.861
1656	0.976
1657	0.911
1658	1.084
1659	1.144
1660	0.971
1661	0.929
1662	1.008
1663	1.214
1664	0.958
1665	0.455
1666	0.579
1667	0.796
1668	0.594
1669	0.646
1670	0.425
1671	0.721
1672	0.8
1673	0.701
1674	0.62
1675	0.801
1676	0.658
1677	0.866
1678	0.915
1679	0.845
1680	0.935
1681	1.129
1682	1.112
1683	1.081
1684	1.249
1685	0.998
1686	0.792
1687	1.042
1688	0.831
1689	0.698
1690	0.783
1691	1.119
1692	1.131
1693	0.511
1694	1.025
1695	0.703
1696	0.726
1697	0.841
1698	0.791
1699	0.431
1700	0.478
1701	0.589
1702	0.672
1703	0.824
1704	0.939
1705	1.159
1706	1.103
1707	1.131
1708	1.208
1709	1.296
1710	1.026
1711	1.087
1712	1.056
1713	1.348
1714	1.243
1715	1.218
1716	1.189
1717	1.114
1718	0.508
1719	0.704
1720	0.929
1721	0.83
1722	0.836
1723	0.884
1724	0.763
1725	1.042
1726	0.986
1727	1.047
1728	1.216
1729	1.049
1730	1.169
1731	1.202
1732	1.27
1733	1.039
1734	0.747
1735	1.316
1736	1.352
1737	0.779
1738	0.815
1739	1.053
1740	1.027
1741	1.024
1742	0.839
1743	0.812
1744	0.816
1745	0.747
1746	0.826
1747	0.672
1748	0.463
1749	0.761
1750	0.771
1751	0.581
1752	0.772
1753	0.934
1754	1.01
1755	0.477
1756	0.64
1757	0.958
1758	0.943
1759	1.072
1760	0.9
1761	0.997
1762	0.975
1763	1.007
1764	1.134
1765	0.903
1766	0.661
1767	0.818
1768	0.722
1769	0.644
1770	0.501
1771	0.574
1772	0.437
1773	0.551
1774	0.817
1775	0.662
1776	0.634
1777	0.615
1778	1
1779	0.651
1780	0.967
1781	0.985
1782	0.948
1783	0.949
1784	1.151
1785	0.988
1786	0.977
1787	1.161
1788	1.077
1789	1.032
1790	1.058
1791	0.871
1792	0.753
1793	0.885
1794	0.981
1795	0.941
1796	0.993
1797	1.261
1798	1.046
1799	1.084
1800	1.275
1801	1.478
1802	1.431
1803	1.424
1804	1.174
1805	1.041
1806	1.245
1807	1.013
1808	1.33
1809	1.221
1810	1.06
1811	0.834
1812	0.921
1813	0.866
1814	0.68
1815	0.488
1816	0.714
1817	0.825
1818	0.602
1819	0.593
1820	0.674
1821	0.467
1822	0.81
1823	1.003
1824	0.476
1825	0.431
1826	0.787
1827	0.892
1828	1.084
1829	1.2
1830	0.886
1831	1.136
1832	1.328
1833	0.721
1834	0.795
1835	1.144
1836	0.991
1837	1.029
1838	1.167
1839	0.976
1840	0.613
1841	0.692
1842	0.987
1843	0.574
1844	0.777
1845	0.728
1846	0.872
1847	0.953
1848	0.926
1849	1.326
1850	0.859
1851	0.318
1852	0.551
1853	0.806
1854	0.803
1855	0.835
1856	1.029
1857	0.962
1858	0.974
1859	0.821
1860	0.681
1861	1.073
1862	0.891
1863	1.186
1864	1.111
1865	0.774
1866	0.917
1867	0.892
1868	1.295
1869	1.055
1870	1.225
1871	0.836
1872	1.134
1873	1.178
1874	0.985
1875	1.3
1876	1.201
1877	0.532
1878	0.828
1879	0.751
1880	0.952
1881	0.809
1882	0.773
1883	0.726
1884	1.106
1885	0.893
1886	1.115
1887	1.06
1888	0.861
1889	1.081
1890	1.015
1891	1.033
1892	1.073
1893	1.125
1894	1.2
1895	1.167
1896	1.414
1897	0.721
1898	0.865
1899	0.924
1900	0.884
1901	1.105
1902	1.094
1903	1.281
1904	1.444
1905	1.222
1906	0.993
1907	1.21
1908	1.235
1909	1.188
1910	1.248
1911	0.989
1912	1.118
1913	1.23
1914	0.946
1915	0.986
1916	0.986
1917	1.317
1918	1.002
1919	0.574
1920	0.811
1921	1.097
1922	1.219
1923	0.863
1924	1.231
1925	1.17
1926	1.363
1927	0.796
1928	1.108
1929	1.443
1930	1.204
1931	1.1
1932	1.227
1933	1.235
1934	1.232
1935	1.422
1936	0.887
1937	0.999
1938	0.983
1939	1.171
1940	0.92
1941	1.191
1942	1.02
1943	0.897
1944	0.779
1945	0.97
1946	1.081
1947	1.171
1948	1.077
1949	0.965
1950	1.178
1951	0.983
1952	0.932
1953	0.927
1954	0.971
1955	0.604
1956	0.905
1957	0.671
1958	0.878
1959	0.937
1960	0.468
1961	0.592
1962	0.793
1963	0.859
1964	0.99
1965	0.79
1966	1.016
1967	0.863
1968	1.138
1969	0.995
1970	1.019
1971	1.144
1972	1.175
1973	0.881
1974	1.28
1975	0.793
1976	1.23
1977	1.403
1978	0.942
1979	1.061
1980	1.224
1981	1.147
1982	1.008
1983	0.909
1984	0.924
1985	1.174
1986	1.021
1987	1.081
1988	0.777
1989	0.866
1990	0.961
1991	0.855
1992	0.492
1993	0.798