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| Author | Title | Year | Publication | Volume | Pages |
|---|---|---|---|---|---|
| Shin, D.W.; Ahn, J.B. | Adaptive Use of TRMM Observations for Tropical Precipitation Forecasts | 2002 | Journal of the Meteorological Society of Japan | 80 | 85-97 |
| Coleman, F.C.; Chanton, J.P.; Chassignet, E.P. | Ecological Connectivity in Northeastern Gulf of Mexico – The Deep-C Initiative | 2014 | International Oil Spill Conference Proceedings | 2014 | 1972-1984 |
| Dukhovskoy, D; Bourassa, M | Comparison of ocean surface wind products in the perspective of ocean modeling of the Nordic Seas | 2011 | OCEANS 2011 | ||
| Bourassa, MA; Weissman, DE | The development and application of a sea surface stress model function for the QuikSCAT and ADEOS-II SeaWinds scatterometers | 2003 | IEEE International Symposium on Geoscience and Remote Sensing (IGARSS) | 239-241 | |
| Nyadjro, E.S.; Jensen, T.G.; Richman, J.G.; Shriver, J.F. | On the Relationship Between Wind, SST, and the Thermocline in the Seychelles-Chagos Thermocline Ridge | 2017 | IEEE Geoscience and Remote Sensing Letters | 14 | 2315-2319 |
| Holbach, H.M.; Bourassa, M.A. | Platform and Across-Swath Comparison of Vorticity Spectra From QuikSCAT, ASCAT-A, OSCAT, and ASCAT-B Scatterometers | 2017 | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing | 10 | 2205-2213 |
| Cintro, R.; de Campos Velho, H.; Cocke, S. | Tracking the model: Data assimilation by artificial neural network | 2017 | 2016 International Joint Conference on Neural Networks (IJCNN) | 403-410 | |
| Cintra, R; Velho, HD; Cocke, S | Tracking the model: data assimilation by artificial neural network | 2016 | IEEE International Joint Conference on Neural Networks (IJCNN) | 403-410 | |
| Ali, M.M.; Bourassa, M.A.; Bhowmick, S.A.; Sharma, R.; Niharika, K. | Retrieval of Wind Stress at the Ocean Surface From AltiKa Measurements | 2016 | IEEE Geoscience and Remote Sensing Letters | 13 | 821-825 |
| Cintra, R.; de Campos Velho, H.; Anochi, J.; Cocke, S. | Data assimilation by artificial neural networks for the global FSU atmospheric model: Surface pressure | 2015 | Computational Intelligence (LA-CCI), 2015 Latin America Congress on |
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