CranSLIK v1.0: stochastic prediction of oil spill transport and fate using approximation methods

Snow, B. J.; Moulitsas, I.; Kolios, A. J.; De Dominicis, M.

doi:https://doi.org/10.5194/gmd-7-1507-2014

Articles | Volume 7, issue 4

https://doi.org/10.5194/gmd-7-1507-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/gmd-7-1507-2014

© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 7, issue 4

Model description paper

|

22 Jul 2014

Model description paper |

| 22 Jul 2014

CranSLIK v1.0: stochastic prediction of oil spill transport and fate using approximation methods

B. J. Snow, I. Moulitsas, A. J. Kolios, and M. De Dominicis

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Total article views: 4,323 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
2,864	1,290	169	4,323	199	172

HTML: 2,864
PDF: 1,290
XML: 169
Total: 4,323
BibTeX: 199
EndNote: 172

Views and downloads (calculated since 20 Dec 2013)

Month	HTML	PDF	XML	Total
Dec 2013	53	8	1	62
Jan 2014	24	9	3	36
Feb 2014	22	19	3	44
Mar 2014	12	17	0	29
Apr 2014	13	15	2	30
May 2014	12	14	1	27
Jun 2014	8	11	2	21
Jul 2014	65	55	1	121
Aug 2014	59	43	5	107
Sep 2014	17	24	2	43
Oct 2014	21	14	0	35
Nov 2014	20	24	2	46
Dec 2014	17	26	1	44
Jan 2015	12	20	0	32
Feb 2015	15	8	0	23
Mar 2015	7	12	0	19
Apr 2015	17	6	3	26
May 2015	12	6	3	21
Jun 2015	38	12	0	50
Jul 2015	26	8	0	34
Aug 2015	9	15	5	29
Sep 2015	4	9	0	13
Oct 2015	16	5	1	22
Nov 2015	16	5	0	21
Dec 2015	5	14	0	19
Jan 2016	28	12	0	40
Feb 2016	20	9	1	30
Mar 2016	13	8	0	21
Apr 2016	9	6	0	15
May 2016	18	16	1	35
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Oct 2016	15	4	2	21
Nov 2016	10	6	3	19
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Jan 2017	25	13	3	41
Feb 2017	16	3	4	23
Mar 2017	27	5	5	37
Apr 2017	34	8	5	47
May 2017	40	10	3	53
Jun 2017	30	7	2	39
Jul 2017	15	4	0	19
Aug 2017	3	4	0	7
Sep 2017	9	7	0	16
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Dec 2017	8	5	1	14
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Jul 2018	22	10	0	32
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Sep 2018	19	6	0	25
Oct 2018	21	9	0	30
Nov 2018	31	15	0	46
Dec 2018	15	6	1	22
Jan 2019	23	9	1	33
Feb 2019	9	2	0	11
Mar 2019	16	8	0	24
Apr 2019	14	5	1	20
May 2019	6	3	0	9
Jun 2019	10	7	0	17
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Aug 2019	14	4	0	18
Sep 2019	16	5	1	22
Oct 2019	19	7	0	26
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Jan 2020	19	5	3	27
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Apr 2022	35	10	1	46
May 2022	38	8	1	47
Jun 2022	37	6	1	44
Jul 2022	28	8	0	36
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Oct 2022	43	4	0	47
Nov 2022	41	13	1	55
Dec 2022	49	6	2	57
Jan 2023	35	8	1	44
Feb 2023	40	5	0	45
Mar 2023	51	4	3	58
Apr 2023	41	7	1	49
May 2023	37	10	0	47
Jun 2023	39	3	1	43
Jul 2023	45	5	0	50
Aug 2023	43	4	1	48
Sep 2023	38	4	0	42
Oct 2023	42	3	2	47
Nov 2023	23	3	0	26
Dec 2023	42	4	2	48
Jan 2024	42	2	0	44
Feb 2024	41	13	1	55
Mar 2024	43	2	0	45
Apr 2024	53	13	3	69
May 2024	18	5	5	28
Jun 2024	11	4	3	18
Jul 2024	8	4	0	12
Aug 2024	16	12	3	31
Sep 2024	10	1	0	11
Oct 2024	15	5	0	20
Nov 2024	9	5	1	15
Dec 2024	6	17	1	24
Jan 2025	10	7	2	19
Feb 2025	22	5	1	28

Cumulative views and downloads (calculated since 20 Dec 2013)

Month	HTML	PDF	XML	Total
Dec 2013	53	8	1	62
Jan 2014	24	9	3	36
Feb 2014	22	19	3	44
Mar 2014	12	17	0	29
Apr 2014	13	15	2	30
May 2014	12	14	1	27
Jun 2014	8	11	2	21
Jul 2014	65	55	1	121
Aug 2014	59	43	5	107
Sep 2014	17	24	2	43
Oct 2014	21	14	0	35
Nov 2014	20	24	2	46
Dec 2014	17	26	1	44
Jan 2015	12	20	0	32
Feb 2015	15	8	0	23
Mar 2015	7	12	0	19
Apr 2015	17	6	3	26
May 2015	12	6	3	21
Jun 2015	38	12	0	50
Jul 2015	26	8	0	34
Aug 2015	9	15	5	29
Sep 2015	4	9	0	13
Oct 2015	16	5	1	22
Nov 2015	16	5	0	21
Dec 2015	5	14	0	19
Jan 2016	28	12	0	40
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Jul 2016	15	9	5	29
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Oct 2016	15	4	2	21
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Jan 2017	25	13	3	41
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Apr 2018	21	7	1	29
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Oct 2018	21	9	0	30
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Oct 2020	18	8	0	26
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Nov 2021	9	26	0	35
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Feb 2022	13	14	2	29
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Apr 2022	35	10	1	46
May 2022	38	8	1	47
Jun 2022	37	6	1	44
Jul 2022	28	8	0	36
Aug 2022	41	7	0	48
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Oct 2022	43	4	0	47
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Dec 2022	49	6	2	57
Jan 2023	35	8	1	44
Feb 2023	40	5	0	45
Mar 2023	51	4	3	58
Apr 2023	41	7	1	49
May 2023	37	10	0	47
Jun 2023	39	3	1	43
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Oct 2023	42	3	2	47
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Jan 2024	42	2	0	44
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Mar 2024	43	2	0	45
Apr 2024	53	13	3	69
May 2024	18	5	5	28
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Oct 2024	15	5	0	20
Nov 2024	9	5	1	15
Dec 2024	6	17	1	24
Jan 2025	10	7	2	19
Feb 2025	22	5	1	28

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CranSLIK v1.0: stochastic prediction of oil spill transport and fate using approximation methods

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5 citations as recorded by crossref.

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