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Artigo de periodico
Air quality modeling intercomparison and multiscale ensemble chain for Latin America (2024)
Pachón, Jorge E.; Opazo, Mariel A.; Lichtig, Pablo ; Huneeus, Nicolas; Bouarar, Idir; Brasseur, Guy ; Li, Cathy W. Y ; Flemming, Johannes ; Menut, Laurent ; Menares, Camilo; Gallardo, Laura ; Gauss, Michael; Sofiev, Mikhail ; Kouznetsov, Rostislav ; Palamarchuk, Julia; Uppstu, Andreas; Dawidowski, Laura; Rojas, Nestor Y. ; Andrade, Maria de Fátima ; Gavidia-Calderón, Mario E. ; Peralta, Alejandro H. Delgado ; Schuch, Daniel
Source: Geoscientific Model Development. Unidade: IAG
Subjects: POLUIÇÃO AMBIENTAL, QUALIDADE DO AR, OBSERVAÇÃO METEOROLÓGICA
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ABNT
PACHÓN, Jorge E. et al. Air quality modeling intercomparison and multiscale ensemble chain for Latin America. Geoscientific Model Development, v. 17, n. 20, p. 7467-7512, 2024Tradução . . Disponível em: https://doi.org/10.5194/gmd-17-7467-2024. Acesso em: 29 nov. 2025.
APA
Pachón, J. E., Opazo, M. A., Lichtig, P., Huneeus, N., Bouarar, I., Brasseur, G., et al. (2024). Air quality modeling intercomparison and multiscale ensemble chain for Latin America. Geoscientific Model Development, 17( 20), 7467-7512. Recuperado de https://doi.org/10.5194/gmd-17-7467-2024
NLM
Pachón JE, Opazo MA, Lichtig P, Huneeus N, Bouarar I, Brasseur G, Li CWY, Flemming J, Menut L, Menares C, Gallardo L, Gauss M, Sofiev M, Kouznetsov R, Palamarchuk J, Uppstu A, Dawidowski L, Rojas NY, Andrade M de F, Gavidia-Calderón ME, Peralta AHD, Schuch D. Air quality modeling intercomparison and multiscale ensemble chain for Latin America [Internet]. Geoscientific Model Development. 2024 ; 17( 20): 7467-7512.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-17-7467-2024
Vancouver
Pachón JE, Opazo MA, Lichtig P, Huneeus N, Bouarar I, Brasseur G, Li CWY, Flemming J, Menut L, Menares C, Gallardo L, Gauss M, Sofiev M, Kouznetsov R, Palamarchuk J, Uppstu A, Dawidowski L, Rojas NY, Andrade M de F, Gavidia-Calderón ME, Peralta AHD, Schuch D. Air quality modeling intercomparison and multiscale ensemble chain for Latin America [Internet]. Geoscientific Model Development. 2024 ; 17( 20): 7467-7512.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-17-7467-2024
Artigo de periodico
A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes (2022)
Mello, Danilo César de ; Veloso, Gustavo Vieira ; Lana, Marcos Guedes de; Mello, Fellipe Alcantara de Oliveira ; Poppiel, Raul Roberto ; Cabrero, Diego Ribeiro Oquendo; Di Raimo, Luis Augusto Di Loreto ; Schaefer, Carlos Ernesto Gonçalves Reynaud; Fernandes Filho, Elpídio Inácio ; Leite, Emilson Pereira; Demattê, José Alexandre Melo
Source: Geoscientific Model Development. Unidade: ESALQ
Subjects: ALGORITMOS, APRENDIZADO COMPUTACIONAL, FRAMEWORKS, GEOFÍSICA, MODELAGEM DE DADOS, SENSOR, SOLOS
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ABNT
MELLO, Danilo César de et al. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes. Geoscientific Model Development, v. 15, p. 1219–1246, 2022Tradução . . Disponível em: https://doi.org/10.5194/gmd-15-1219-2022. Acesso em: 29 nov. 2025.
APA
Mello, D. C. de, Veloso, G. V., Lana, M. G. de, Mello, F. A. de O., Poppiel, R. R., Cabrero, D. R. O., et al. (2022). A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes. Geoscientific Model Development, 15, 1219–1246. doi:10.5194/gmd-15-1219-2022
NLM
Mello DC de, Veloso GV, Lana MG de, Mello FA de O, Poppiel RR, Cabrero DRO, Di Raimo LADL, Schaefer CEGR, Fernandes Filho EI, Leite EP, Demattê JAM. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes [Internet]. Geoscientific Model Development. 2022 ; 15 1219–1246.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-15-1219-2022
Vancouver
Mello DC de, Veloso GV, Lana MG de, Mello FA de O, Poppiel RR, Cabrero DRO, Di Raimo LADL, Schaefer CEGR, Fernandes Filho EI, Leite EP, Demattê JAM. A new methodological framework for geophysical sensor combinations associated with machine learning algorithms to understand soil attributes [Internet]. Geoscientific Model Development. 2022 ; 15 1219–1246.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-15-1219-2022
Artigo de periodico
Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion (2022)
Dolci, Daiane Iglesia ; Silva, Felipe A. G.; Peixoto, Pedro da Silva ; Volpe, Ernani Vitillo
Source: Geoscientific Model Development. Unidades: IME, EP
Assunto: ONDAS (OCEANOGRAFIA)
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ABNT
DOLCI, Daiane Iglesia et al. Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion. Geoscientific Model Development, v. 15, p. 5857–5881, 2022Tradução . . Disponível em: https://doi.org/10.5194/gmd-15-5857-2022. Acesso em: 29 nov. 2025.
APA
Dolci, D. I., Silva, F. A. G., Peixoto, P. da S., & Volpe, E. V. (2022). Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion. Geoscientific Model Development, 15, 5857–5881. doi:10.5194/gmd-15-5857-2022
NLM
Dolci DI, Silva FAG, Peixoto P da S, Volpe EV. Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion [Internet]. Geoscientific Model Development. 2022 ; 15 5857–5881.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-15-5857-2022
Vancouver
Dolci DI, Silva FAG, Peixoto P da S, Volpe EV. Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion [Internet]. Geoscientific Model Development. 2022 ; 15 5857–5881.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-15-5857-2022
Artigo de periodico
Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models (2021)
Santos, Luan da Fonseca ; Peixoto, Pedro da Silva
Source: Geoscientific Model Development. Unidade: IME
Subjects: MÉTODOS NUMÉRICOS, EQUAÇÕES DIFERENCIAIS, GEODÉSIA ESPACIAL
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ABNT
SANTOS, Luan da Fonseca e PEIXOTO, Pedro da Silva. Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models. Geoscientific Model Development, v. 14, n. 11, p. 6919-6944, 2021Tradução . . Disponível em: https://doi.org/10.5194/gmd-14-6919-2021. Acesso em: 29 nov. 2025.
APA
Santos, L. da F., & Peixoto, P. da S. (2021). Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models. Geoscientific Model Development, 14( 11), 6919-6944. doi:10.5194/gmd-14-6919-2021
NLM
Santos L da F, Peixoto P da S. Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models [Internet]. Geoscientific Model Development. 2021 ; 14( 11): 6919-6944.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-14-6919-2021
Vancouver
Santos L da F, Peixoto P da S. Topography-based local spherical Voronoi grid refinement on classical and moist shallow-water finite-volume models [Internet]. Geoscientific Model Development. 2021 ; 14( 11): 6919-6944.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-14-6919-2021
Artigo de periodico
The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America (2019)
Longo, Marcos; Knox, Ryan G; Levine, Naomi M; Swann, Abigail L. S; Medvigy, David M; Dietze, Michael C; Kim, Yeonjoo; Zhang, Ke; Bonal, Damien; Burban, Benoit; Camargo, Plinio Barbosa de ; Hayek, Matthew N; Saleska, Scott R; Silva, Rodrigo da ; Bras, Rafael L; Wofsy, Steven C; Moorcroft, Paul R
Source: Geoscientific Model Development. Unidade: CENA
Subjects: ÁGUA, BIOFÍSICA, CARBONO, CICLOS BIOGEOQUÍMICOS, ENERGIA, ECOSSISTEMAS TERRESTRES
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ABNT
LONGO, Marcos et al. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America. Geoscientific Model Development, v. 12, p. 4347-4374, 2019Tradução . . Disponível em: https://doi.org/10.5194/gmd-12-4347-2019. Acesso em: 29 nov. 2025.
APA
Longo, M., Knox, R. G., Levine, N. M., Swann, A. L. S., Medvigy, D. M., Dietze, M. C., et al. (2019). The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America. Geoscientific Model Development, 12, 4347-4374. doi:10.5194/gmd-12-4347-2019
NLM
Longo M, Knox RG, Levine NM, Swann ALS, Medvigy DM, Dietze MC, Kim Y, Zhang K, Bonal D, Burban B, Camargo PB de, Hayek MN, Saleska SR, Silva R da, Bras RL, Wofsy SC, Moorcroft PR. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America [Internet]. Geoscientific Model Development. 2019 ; 12 4347-4374.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-12-4347-2019
Vancouver
Longo M, Knox RG, Levine NM, Swann ALS, Medvigy DM, Dietze MC, Kim Y, Zhang K, Bonal D, Burban B, Camargo PB de, Hayek MN, Saleska SR, Silva R da, Bras RL, Wofsy SC, Moorcroft PR. The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America [Internet]. Geoscientific Model Development. 2019 ; 12 4347-4374.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-12-4347-2019
Artigo de periodico
VEIN v0.2.2: an R package for bottom–up vehicular emissions inventories (2018)
Ibarra-Espinosa, Sergio; Ynoue, Rita Yuri; O'Sullivan, Shane; Pebesma, Edzer; Andrade, Maria de Fátima; Osses, Mauricio
Source: Geoscientific Model Development. Unidade: IAG
Subjects: METEOROLOGIA AMBIENTAL, POLUIÇÃO ATMOSFÉRICA, VEÍCULOS AUTOMOTORES
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ABNT
IBARRA-ESPINOSA, Sergio et al. VEIN v0.2.2: an R package for bottom–up vehicular emissions inventories. Geoscientific Model Development, v. 11, n. 6, p. 2209-2229, 2018Tradução . . Disponível em: https://doi.org/10.5194/gmd-11-2209-2018. Acesso em: 29 nov. 2025.
APA
Ibarra-Espinosa, S., Ynoue, R. Y., O'Sullivan, S., Pebesma, E., Andrade, M. de F., & Osses, M. (2018). VEIN v0.2.2: an R package for bottom–up vehicular emissions inventories. Geoscientific Model Development, 11( 6), 2209-2229. doi:10.5194/gmd-11-2209-2018
NLM
Ibarra-Espinosa S, Ynoue RY, O'Sullivan S, Pebesma E, Andrade M de F, Osses M. VEIN v0.2.2: an R package for bottom–up vehicular emissions inventories [Internet]. Geoscientific Model Development. 2018 ; 11( 6): 2209-2229.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-11-2209-2018
Vancouver
Ibarra-Espinosa S, Ynoue RY, O'Sullivan S, Pebesma E, Andrade M de F, Osses M. VEIN v0.2.2: an R package for bottom–up vehicular emissions inventories [Internet]. Geoscientific Model Development. 2018 ; 11( 6): 2209-2229.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-11-2209-2018
Artigo de periodico
The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas (2017)
Freitas, Saulo Ribeiro de; Panetta, Jairo; Longo, Karla Maria; Rodrigues, Luiz F; Moreira, Demerval S; Rosário, Nilton E; Dias, Pedro Leite da Silva; Dias, Maria Assunção Faus da Silva; Souza, Enio P; Freitas, Edmílson Dias de; Camponogara, Gláuber
Source: Geoscientific Model Development. Unidade: IAG
Subjects: METEOROLOGIA AMBIENTAL, METEOROLOGIA
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ABNT
FREITAS, Saulo Ribeiro de et al. The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas. Geoscientific Model Development, v. 10, p. 189-222, 2017Tradução . . Disponível em: https://doi.org/10.5194/gmd-10-189-2017. Acesso em: 29 nov. 2025.
APA
Freitas, S. R. de, Panetta, J., Longo, K. M., Rodrigues, L. F., Moreira, D. S., Rosário, N. E., et al. (2017). The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas. Geoscientific Model Development, 10, 189-222. doi:10.5194/gmd-10-189-2017
NLM
Freitas SR de, Panetta J, Longo KM, Rodrigues LF, Moreira DS, Rosário NE, Dias PL da S, Dias MAF da S, Souza EP, Freitas ED de, Camponogara G. The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas [Internet]. Geoscientific Model Development. 2017 ; 10 189-222.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-10-189-2017
Vancouver
Freitas SR de, Panetta J, Longo KM, Rodrigues LF, Moreira DS, Rosário NE, Dias PL da S, Dias MAF da S, Souza EP, Freitas ED de, Camponogara G. The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas [Internet]. Geoscientific Model Development. 2017 ; 10 189-222.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-10-189-2017
Artigo de periodico
Analysing amazonian forest productivity using a new individual and trait-based model (TFS v.1) (2014)
Fyllas, N. M.; Gloor, E.; Mercado, L. M.; Sitch, S.; Quesada, C. A.; Domingues, Tomas Ferreira ; Galbraith, D. R.; Torre-Lezama, A.; Vilanova, E.; Ramírez-Angulo, H.; Higuchi, Niro ; Neill, D. A.; Silveira, M.; Ferreira, L.; Aymard, G. A.; Malhi, Y.; Phillips, O. L.; Lloyd, J.
Source: Geoscientific Model Development. Unidade: FFCLRP
Subjects: BIOMASSA, ECOLOGIA VEGETAL
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ABNT
FYLLAS, N. M. et al. Analysing amazonian forest productivity using a new individual and trait-based model (TFS v.1). Geoscientific Model Development, v. 7, p. 1251-1269, 2014Tradução . . Disponível em: https://doi.org/10.5194/gmd-7-1251-2014. Acesso em: 29 nov. 2025.
APA
Fyllas, N. M., Gloor, E., Mercado, L. M., Sitch, S., Quesada, C. A., Domingues, T. F., et al. (2014). Analysing amazonian forest productivity using a new individual and trait-based model (TFS v.1). Geoscientific Model Development, 7, 1251-1269. doi:10.5194/gmd-7-1251-2014
NLM
Fyllas NM, Gloor E, Mercado LM, Sitch S, Quesada CA, Domingues TF, Galbraith DR, Torre-Lezama A, Vilanova E, Ramírez-Angulo H, Higuchi N, Neill DA, Silveira M, Ferreira L, Aymard GA, Malhi Y, Phillips OL, Lloyd J. Analysing amazonian forest productivity using a new individual and trait-based model (TFS v.1) [Internet]. Geoscientific Model Development. 2014 ; 7 1251-1269.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-7-1251-2014
Vancouver
Fyllas NM, Gloor E, Mercado LM, Sitch S, Quesada CA, Domingues TF, Galbraith DR, Torre-Lezama A, Vilanova E, Ramírez-Angulo H, Higuchi N, Neill DA, Silveira M, Ferreira L, Aymard GA, Malhi Y, Phillips OL, Lloyd J. Analysing amazonian forest productivity using a new individual and trait-based model (TFS v.1) [Internet]. Geoscientific Model Development. 2014 ; 7 1251-1269.[citado 2025 nov. 29 ] Available from: https://doi.org/10.5194/gmd-7-1251-2014

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