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network of universities and research insti-  nies such as Petrobras and Vale S.A., can   Oceans, 125, e2020JC016428, 2020. DOI:   LONNOY, E.; MATTHEWS, J. B. R.; MAY-
 tutes in Brazil that provide high-level educa-  improve even more the Brazilian initiatives   https://doi.org/ 10.1029/2020JC016428.  COCK, T. K.; WATERFIELD, T.; YELEKÇI, O.;
 tion in marine sciences is a successful mark   that are already underway, whose exam-  DRÉVILLON, M. et. al. Learning about   YU, R.;  ZHOU, B. (eds.). Climate Change
 for the emergence of such specialists in the   ples  described  in  this  chapter  prove  that   Copernicus Marine Environment Mon-  2021: The Physical Science Basis. Contri-
 community. This network of researchers,   Oceanography Operational, which is fun-  itoring Service « CMEMS »: A Practical   bution of Working Group I to the Sixth As-
 with the support of public institutions such   damental for the development of the Blue   Introduction to the Use of the European   sessment Report of the Intergovernmental
                                                           Panel on Climate Change. Cambridge Uni-
 as  the  Brazilian  Navy  and  private  compa-  Economy in Brazil, is active and promising.  Operational Oceanography Service. GODAE
                  Oceanview International School in “New   versity Press. In Press.
 References       Frontiers in Operational Oceanography”,   JOHANNESSEN, J. A.; LE TRAON, P.-Y.;
                  E. P. Chassignet, A. Pascual, J. Tintoré,   ROBINSON, I.; NITTIS, K.; BELL, M. J.;
 BAHUREL, P. et. al. Ocean monitoring and   Stream separation, penetration, and vari-  and J. Verron, Eds., 695-712, 2018. DOI:   PINARDI, N.; BAHUREL, P. Marine Envi-
 forecasting core services, the European   ability. J. Phys. Oceanogr, 47, 1999-2021,    10.17125/gov2018.ch25.  Ronment and Security for the European
 MyOcean example. Oceanob’s 2009. A. S.   2017. DOI: 10.1175/JPO-D-17-0031.1.  EDWARDS, C. A.; MOORE, A. M.; HOTEIT,   Area: Toward Operational Oceanography.
 Fischer, 2009.  CHASSIGNET, E.; VERRON, J. Ocean   I.; CORNUELLE, B. D. Regional Ocean Data   Bul. Amer. Met. Soc., 87 (8), 1081-1090,
 BELL, M. J.; LEFEBVRE, M.; LE TRAON, P-Y.;   Weather Forecasting: an Integrated View   Assimilation. Annual Review of Marine   2006. DOI:10.1175/BAMS-87-8-1081.
 SMITH, N.; WILMER-BECKER, K. GODAE:   of Oceanography. Springer, 577 p. 2006.  Science, 7 (1), 21-42, 2015. DOI: 10.1146/  LEA, D. J.; MARTIN, M. J.; OKE, P. R.
 The Global Ocean Data Assimilation Exper-  CUMMINGS, J. A.; BERTINO, L.; BRAS-  annurev-marine-010814-015821.  Demonstrating the complementarity of
 iment. Oceanography, 22: 14-21, 2009.  SEUR, P.; FUKUMORI, I.; KAMACHI, M.;   EVENSEN, G. The ensemble Kalman filter:   observations in an operational ocean fore-
 BELL, M. J.; SCHILLER, A.; LE TRAON,   MARTIN, M. J.; MOGENSEN K.; OKE, P.;   theoretical formulation and practical imple-  casting system. Quarterly Journal of the
 P.-Y.; SMITH, N. R.; DOMBROWSKY, E.;   TESTUT, C.E.; VERRON, J.; WEAVER, A.   mentation. Ocean Dyn, 53, 2003, 343-367.  Royal Meteorological Society, 2013.
 WILMER-BECKER, K. An introduction to   Ocean data assimilation systems for GO-  EVENSEN, G. Data assimilation: The en-  DOI: 10.1002/qj.2281.
 GODAE OceanView, J. of Oper. Ocean-  DAE. Oceanography, 22, 96-109, 2009.  semble Kalman filter. New York: Springer,   LE TRAON, P.-Y. et al.  Preparing the New
 ography, 8:sup1, s2-s11, 2015. DOI:   DALEY, R. Atmospheric Data Analysis.   2006. 307 p.  Phase of Argo: Scientific Achievements of
 10.1080/1755876X.2015.1022041.  Cambridge University Press, 1991. 450 p.   FERREIRA, M. B. The ZOPACAS and the   the NAOS Project. Frontiers in Marine
 BONADUCE, A.; BENKIRAN, M.; REMY, E.;   DAVIDSON, F.; ALVERA-AZCÁRATE, A.;   Maritime Safety in the South Atlantic. Joint   Science, 7 (838), 2020. DOI: 10.3389/
 TRAON, P. Y. L.; GARRIC, G. Contribution   BARTH, A.; BRASSINGTON, G. B. et. al.   Force Quarterly, NDUPress, 2022. (no prelo)  fmars.2020.577408.
 of future wide-swath altimetry missions to   Synergies in Operational Oceanography:   FOX-KEMPER, B. et al. Challenges and   LIMA, J. A.; MARTINS, R. P.; TANAJURA,
 ocean analysis and forecasting. Ocean Sci-  The Intrinsic Need for Sustained Ocean   Prospects in Ocean Circulation Models.   C. A. S. et al. Design and implementation
 ence, 14(6), 1405-1421, 2018.  Observations. Front. Mar. Sci. 6:450,   Frontiers in Marine Science, 6 (65),   of the Oceanographic Modeling and Ob-
 CARVALHO, J. P. S.; COSTA, F. B.; MI-  2019. DOI: 10.3389/fmars.2019.00450.  2019. DOI: 10.3389/fmars.2019.00065.  servation Network (REMO) for operational
 GNAC, D.; TANAJURA, C. A. S. Assessing   DAVIDSON, F. J. M.; ALLEN, A.; BRASSING-  FUJII Y.; RÉMY, E.; ZUO, H.; OKE, P. et al.   oceanography and ocean forecasting. Rev.
 the extended-range predictability of the   TON, G.; BREIVIK, Ø.; DANIEL, P.; KAMA-  Observing System Evaluation Based on   Bras. Geofis., 2013, 31, 209-228.
 Ocean Model HYCOM with the REMO   CHI, M.; SATO, S.; KING, B.; LEFEVRE, F.;   Ocean Data Assimilation and Prediction   MANSFIELD, K. L. ; MENDILAHARSU, M.
 Ocean Data Assimilation System (RO-  SUTTON, M.; KANEKO, H. Applications of   Systems: On-Going Challenges and a Fu-  L.; PUTMAN, N. F.; MARCOVALDI, M. A.
 DAS) in the South Atlantic. J. of Oper.   GODAE ocean current forecasts to search   ture Vision for Designing and Supporting   G. dei; SACCO, A. E.; LOPEZ, G.; PIRES,
 Oceanography, v.13, p.1-11. 2019: DOI:   and rescue and ship routing. Oceanogra-  Ocean Observational Networks. Front.   T.; SWIMMER, Y. First satellite tracks of
 10.1080/1755876x.2019.1606880.  phy 22: 176-181, 2009.  Mar. Sci. 6:417, 2019. DOI: 10.3389/  South Atlantic sea turtle ‘lost years’: sea-
 CHASSIGNET, E. P. et al. US GODAE Global   DORFSCHÄFER, G. S.; TANAJURA, C. A.   fmars.2019.00417.  sonal variation in trans-equatorial move-
 ocean prediction with the Hybrid Coordi-  S.; COSTA, F. B.; SANTANA, R. C. A new   IPCC, 2021. Summary for Policymakers. In:   ment. Proc. R. Soc. B, 284, 20171730,
 nate Ocean Model (HYCOM). Oceanogra-  approach for estimating salinity in the   MASSON-DELMOTTE, V.; ZHAI, P.; PIRANI,   2017. DOI: http://dx.doi.org/10.1098/
 phy, vol 22, 64-75, 2009.  Southwest Atlantic and its application   A.; CONNORS, S. L.; PÉAN, C.; BERGER,   rspb.2017.1730.
 CHASSIGNET, E. P.; XU, X. Impact of hor-  in a data assimilation evaluation experi-  S.; CAUD, N.; CHEN, Y.; GOLDFARB, L.;   MARTIN, M. J. et al. Status and future of data
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 izontal resolution (1/12  to 1/50 ) on Gulf   ment. Journal of Geophysical Research:   GOMIS, M. I.; HUANG, M.; LEITZELL, K.;   assimilation in operational oceanography.
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