Page 458 - Livro - Economia Azul

10.1080/1755876X.2015.1022055. 2019 Northeast Brazil Oil Spill: Scenarios. and tides for the representation of the The REMO ocean data assimilation system
MARTIN, M. J. Suitability of satellite sea Anais da Academia Brasileira de Ciên- Cape São Tomé Eddies. 2020. Ocean into HYCOM (RODAS_H): General des-
surface salinity data for use in assessing cias – AABC, 2022 (no prelo). Dynamics, 70, 77–94. DOI: https://doi. cription and preliminary results. Atmos-
and correcting ocean forecasts. Remote OKE, P.R.; LARNICOL, G.; JONES, E. M.; org/10.1007/s10236-019-01307-w. pheric and Oceanic Science Letters, 7,
Sensing of Environment, 180305-319, KOURAFALOU, V.; SPERREVIK, A. K.; CAR- SCHILLER, A.; DAVIDSON, F.; DIGIACO- 464-470. 2014. DOI: 10.3878/j.issn.1674-
2016. DOI: https://doi.org/10.1016/j. SE, F.; TANAJURA, C. A. S.; MOURRE, B.; MO, P. M.; WILMER-BECKER, K. Better 2834.14.0011.
rse.2016.02.004. TONANI, M.; BRASSINGTON, G. B.; LE Informed Marine Operations and Mana- TANAJURA C.A.S., A.N. SANTANA; F.B.
MELLO, R. L.; FREITAS, A. C. N.; RUSSO, L.; HENAFF, M.; HALLIWELL JR., G. R.; ATLAS, gement: Multidisciplinary Efforts in Ocean COSTA; V.F.S. VIDAL; J. PEREIRA; A.T. MA-
OLIVEIRA, J. F.; TANAJURA, C. A. S.; ALVA- R.; MOORE, A. M.; EDWARDS, C. A.; Forecasting Research for Socioeconomic TIAS; GOMES, R. Assimilation of SMOS
RENGA, J. B. R. Ocean forecasts in the Sou- MARTIN, M. J.; SELLAR, A. A.; ALVAREZ, Benefit. Bul. Amer. Met. Soc. 2016. 97 SSS into HYCOM with the REMO Ocean
thwaestern Atlantic: Impact of diferent sour- A.; DE MEY, P.; ISKANDARANI, M. Asses- (9), 1553-1559. DOI: 10.1175/bams- Data Assimilation System in the South
ces of sea surface height in data assimilation. sing the impact of observations on ocean -d-15-00102.1. Atlantic. GODAE OceanView Sympo-
Rev. Bras. Geofis. 2013. 31, 243-255. forecasts and reanalyses: Part 2: Regional SCHILLER, A.; MOURRE, B.; DRILLET, sium OceanPredict’19, 6-10 de maio de
MIGNAC, D.; TANAJURA, C. A. S.; SAN- applications. J. of Oper. Oceanography. Y.; BRASSINGTON, G. An Overview of 2019. Halifax, Canada. 2019 Disponível
TANA, A. N.; LIMA, L. N.; XIE, J. Argo data 8 (sup1): s63-s79, 2015. DOI: https://doi. Operational Oceanography. GODAE em: https://www.godae.org/~godae-data/
assimilation into HYCOM with an EnOI org/10.1080/1755876X.2015.1022080. Oceanview International School in “New OP19/4.3.6-Tanajura_etal_OP19_fiinal.pdf.
method in the Atlantic Ocean. Ocean PEARLMAN, J. et al. Evolving and Sustai- Frontiers in Operational Oceanography”, TANAJURA, C. A. S., D. MIGNAC, A. N.
Science, 11:195-213, 2015. DOI: https:// ning Ocean Best Practices to Enable Intero- E. P. CHASSIGNET, A. PASCUAL, J. TIN- de SANTANA, F. B. COSTA, L. N. LIMA, K.
doi.org/10.5194/os-11-195-2015. perability in the UN Decade of Ocean Scien- TORÉ, J. VERRON, (eds.), 1-262018. DOI: P. BELYAEV, J. ZHU, 2020: Observing Sys-
MOLTMANN, T. et al. A Global Ocean Ob- ce for Sustainable Development. Frontiers 10.17125/gov2018.ch01. tem Experiments over the Atlantic Ocean
serving System (GOOS), Delivered Through in Marine Science, 8 (458), 2021. DOI: SOARES, M. O.; C. E. P. TEIXEIRA; L. E. A. with the REMO Ocean Data Assimilation
Enhanced Collaboration Across Regions, https/doir.org/10.3389/fmars.2021.619685 BEZERRA; E. F. RABELO; I. B. CASTRO; R. System (RODAS) into HYCOM. Ocean
Communities, and New Technologies. PENNY, S. G. et al. Observational Ne- M. CAVALCANTE. The most extensive oil Dynamics, 52, 123-132. DOI: https://doi.
Frontiers in Marine Science, 6 (291). eds for Improving Ocean and Coupled spill registered in tropical oceans (Brazil): org/10.1007/s10236-002-0013-8.
2019: DOI: 10.3389/fmars.2019.00291. Reanalysis, S2S Prediction, and Deca- the balance sheet of a disaster. Environ TOZER, B.; D. T. SANDWELL; W. H. F. SMI-
MOORE, A. M. et al. Synthesis of Ocean Ob- dal Prediction. Frontiers in Marine Sci Pollut Res, 29, 19869-198772022: TH; C. OLSON; J. R. BEALE; P. WESSEL.
servations Using Data Assimilation for Ope- Science, 6 (391). 2019. DOI: 10.3389/ DOI: 10.1007/s11356-022-18710-4. Global Bathymetry and Topography at
rational, Real-Time and Reanalysis Systems: fmars.2019.00391. TRANCHANT, B.; TESTUT, C. E.; RENAULT, 15 Arc Sec: SRTM15+. Earth and Space
A More Complete Picture of the State of REUL, N. et al. Sea Surface Salinity Obser- L.; FERRY, N.; BIROL, F.; BRASSEUR, P. Ex- Science, 6 (10), 1847-1864. 2019. DOI:
the Ocean. Frontiers in Marine Science, 6 vations from Space with the SMOS Satelli- pected impact of the future SMOS and https://doi.org/10.1029/2019EA000658.
(90). 2019 DOI: 10.3389/fmars.2019.00090. te: A New Means to Monitor the Marine Aquarius Ocean surface salinity missions in TRANCHANT, B.; E. REMY, E. GREINER, O.
MORROW R. et al. Global Observations of Branch of the Water Cycle. Surveys in the Mercator Ocean operational systems: LEGALLOUDEC. Data assimilation of Soil
Fine-Scale Ocean Surface Topography with Geophysics, 35 (3), 681-722, 2014. DOI: New perspectives to monitor ocean circu- Moisture and Ocean Salinity (SMOS) ob-
the Surface Water and Ocean Topography 10.1007/s10712-013-9244-0. lation. Remote Sensing of Environment, servations into the Mercator Ocean opera-
(SWOT) Mission. Front. Mar. Sci. 6:232, ROEMMICH, D. et al. On the Future of 2008. 112(4), 1476-1487. tional system: focus on the El Niño 2015
2019. DOI: 10.3389/fmars.2019.00232. Argo: A Global, Full-Depth, Multi-Dis- TANAJURA, C. A. S.; F. COSTA, R. R. da event. Ocean Sci., 2019:15 (3), 543-563.
NOBRE, P.; LEMOS, A. T.; GIAROLLA, E.; ciplinary Array. Frontiers in Marine SILVA et al. Assimilation of sea surface hei- DOI: 10.5194/os-15-543-2019.
CAMAYO, R.; NAMIKAWA, L.; KAMPEL, Science, 6 (439). 2019: DOI: 10.3389/ ght anomalies into HYCOM with an opti- VARONA, H. L.; D. VELEDA; M. SILVA; M.
M.; RUDORFF, N.; BEZERRA, D. X.; LOREN- fmars.2019.00439. mal interpolation scheme over the Atlantic CINTRA; M. ARAÚJO. Amazon River plu-
ZZETTI, J. A.; GOMES, J.; SILVA JR., M. B. SANTANA, R.; COSTA, F. B.; MIGNAC, D.; Ocean Metarea V. Rev. Bras. Geofis., 31, me influence on Western Tropical Atlantic
da; LAGE, C. P. M.; PAES, R. L.; BEISL, C.; SANTANA, A.N.; VIDAL,V. R. S.; ZHU J.; 257-270, 2013. dynamic variability. Dynam. Atmos. Oce-
LOBÃO, M. M.; BIGNELLI, P. A.; MOURA, TANAJURA, C.A.S. Model sensitivity expe- TANAJURA C.A.S.; A.N. SANTANA; D. ans, 2019. 851-15. DOI: 10.1016/j.dynat-
N. de; GALVÃO, W. S.; POLITO, P. S. The riments on data assimilation, downscaling MIGNAC; L.N.LIMA; K. BELYAEV; X.P. XIE,. moce.2018.10.002.

456 ECONOMIA AZUL Da Observação à Utilização de Dados 457