Citation:

PANGAEA.946054

Name: Age model analyses from sediment core SHN-T295
Published: 2022-07-13
License: https://creativecommons.org/licenses/by/4.0/
Keywords: Holocene; oxygen isotope data; Paleoceanography; Paleoclimate; western South Atlantic

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Keyword(s):

Holocene; oxygen isotope data; Paleoceanography; Paleoclimate; western South Atlantic

Related to:

García Chapori, Natalia Luz; Laprida, Cecilia; Lo Prete, Daniel; Chiessi, Cristiano Mazur; Mayr, Christoph; Violante, R A (2022): Holocene palaeoceanographic history of the western South Atlantic. Journal of South American Earth Sciences, 117, 103896, https://doi.org/10.1016/j.jsames.2022.103896

Project(s):

Center for Marine Environmental Sciences (MARUM)

Funding:

Agencia Nacional de Promoción Científica y Tecnológica (MINCYT), grant/award no. PICT2017-1458

Coordenação de Aperfeicoamento de Pessoal de Nível Superior (CAPES), grant/award no. 88881.313535/201901

National Council for Scientific and Technological Development (CNPq), grant/award no. 312458/2020-7

National Scientific and Technical Research Council (CONICET), grant/award no. PIP11220150100038CO

São Paulo Research Foundation (FAPESP), grant/award no. 2018/15123-4

São Paulo Research Foundation (FAPESP), grant/award no. 2019/24349-9

University of Buenos Aires (UBA), grant/award no. 20020190100204BA: UBACyT

Coverage:

Latitude: -37.466667 * Longitude: -54.000000

Minimum DEPTH, sediment/rock: 0.03 m * Maximum DEPTH, sediment/rock: 0.97 m

Event(s):

SHN-T295 * Latitude: -37.466667 * Longitude: -54.000000

Parameter(s):

#	Name	Short Name	Unit	Principal Investigator	Method/Device	Comment
1	DEPTH, sediment/rock	Depth sed	m	Lo Prete, Daniel		Geocode
2	Age model	Age model	ka	Lo Prete, Daniel
3	Age model	Age model	ka	Lo Prete, Daniel	Age, 14C AMS	2.5% Quantile
4	Age model	Age model	ka	Lo Prete, Daniel	Age, 14C AMS	97.5% Quantile

License:

Creative Commons Attribution 4.0 International (CC-BY-4.0)

Status:

Curation Level: Enhanced curation (CurationLevelC)

Size:

288 data points

Data

Download dataset as tab-delimited text — use the following character encoding:

1 Depth sed [m]	2 Age model [ka]	3 Age model [ka] (2.5% Quantile)	4 Age model [ka] (97.5% Quantile)
0.03	1.847	0.790	3.826
0.04	1.988	0.932	3.898
0.05	2.129	1.025	3.963
0.06	2.269	1.091	4.009
0.07	2.410	1.143	4.130
0.08	2.551	1.188	4.298
0.09	2.696	1.375	4.383
0.10	2.842	1.512	4.471
0.11	2.987	1.607	4.571
0.12	3.133	1.677	4.692
0.13	3.278	1.765	4.888
0.14	3.421	1.985	4.947
0.15	3.564	2.155	5.023
0.16	3.707	2.256	5.129
0.17	3.850	2.368	5.276
0.18	3.993	2.440	5.417
0.19	4.133	2.641	5.475
0.20	4.274	2.812	5.531
0.21	4.414	2.912	5.621
0.22	4.555	3.015	5.758
0.23	4.695	3.114	5.922
0.24	4.836	3.448	5.983
0.25	4.977	3.781	6.051
0.26	5.119	3.998	6.142
0.27	5.260	4.184	6.245
0.28	5.401	4.335	6.367
0.29	5.539	4.472	6.502
0.30	5.678	4.572	6.693
0.31	5.816	4.669	6.945
0.32	5.954	4.727	7.233
0.33	6.093	4.811	7.549
0.34	6.228	4.934	7.651
0.35	6.364	5.065	7.809
0.36	6.499	5.163	7.979
0.37	6.635	5.238	8.149
0.38	6.770	5.284	8.398
0.39	6.909	5.480	8.520
0.40	7.048	5.616	8.652
0.41	7.187	5.721	8.845
0.42	7.326	5.812	9.030
0.43	7.465	5.910	9.232
0.44	7.598	6.044	9.317
0.45	7.731	6.163	9.472
0.46	7.864	6.277	9.593
0.47	7.997	6.373	9.748
0.48	8.130	6.434	9.939
0.49	8.265	6.572	10.013
0.50	8.399	6.733	10.126
0.51	8.534	6.825	10.224
0.52	8.669	6.916	10.390
0.53	8.803	6.991	10.604
0.54	8.937	7.181	10.666
0.55	9.070	7.282	10.754
0.56	9.204	7.453	10.852
0.57	9.338	7.543	10.941
0.58	9.471	7.644	11.089
0.59	9.606	7.847	11.135
0.60	9.741	7.997	11.201
0.61	9.875	8.171	11.287
0.62	10.010	8.335	11.424
0.63	10.144	8.435	11.576
0.64	10.281	8.593	11.641
0.65	10.418	8.769	11.700
0.66	10.554	8.890	11.794
0.67	10.691	8.960	11.899
0.68	10.828	9.047	12.039
0.69	10.918	9.200	12.111
0.70	11.009	9.346	12.209
0.70	11.009	9.346	12.209
0.71	11.099	9.476	12.315
0.72	11.190	9.558	12.440
0.73	11.281	9.625	12.591
0.74	11.352	9.694	12.678
0.75	11.424	9.741	12.760
0.76	11.496	9.790	12.860
0.77	11.567	9.842	12.983
0.78	11.639	9.865	13.110
0.79	11.709	9.903	13.173
0.80	11.779	9.954	13.262
0.81	11.849	10.018	13.361
0.82	11.919	10.062	13.460
0.83	11.989	10.132	13.571
0.84	12.059	10.195	13.637
0.85	12.128	10.250	13.704
0.86	12.197	10.326	13.775
0.87	12.267	10.351	13.863
0.88	12.336	10.402	14.006
0.89	12.407	10.465	14.067
0.90	12.479	10.588	14.155
0.91	12.550	10.670	14.218
0.92	12.621	10.753	14.310
0.93	12.692	10.805	14.390
0.94	12.762	10.896	14.460
0.95	12.831	10.967	14.518
0.96	12.900	11.043	14.590
0.97	12.970	11.115	14.686