F. Aires \nResolution des probl\u00e8mes inverses en sciences de l’atmosphere : de l’observation a l’analyse,\u00a0<\/i><\/span> \nTh\u00e8se de HDR, 856 pages, 2012.<\/li>\n
F. Aires \nProbl\u00e8mes inverses et reseaux de neurones : application a l’interferometre haute resolution IASI et a l’analyse de series temporelles,\u00a0<\/i><\/span> \nTh\u00e8se de doctorat, 183 pages, 1999.<\/li>\n<\/ul>\n\n
BOOKS:<\/strong><\/h4>\n
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148 – Fassoni-Andrade, Santos Fleischmann, Papa, Paiva, Wongchuig, Melak, Moreira, Paris Ruhoff, Barbosa, Maciel, Novo, Durand, Frappart, Aires<\/strong>, Abrah\u00e3o, Ferreira-Ferreira, Esnipoza, Laipelt, Cost, Espinoza-Villar, Calmant, Pellet, Hidrologia da Amaz\u00f4nia vista do espa\u00e7o – Avan\u00e7os cientificos e desafios futuros<\/span><\/em>, ISBN 978-85-88686-48-9, 2024.<\/li>\n
147 – Aires<\/strong>, Atmospheric water vapour profiling over ocean\/land and for clear\/cloudy situations using microwave observations<\/em><\/span>, pp. 215-255, in Remote Sensing of Clouds and Precipitation, Ed. C. Andronache, 277 p., ISBN 978-3-319-72582-6, 2018.<\/i><\/li>\n
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\u00a0146 – Prigent, Lettenmaier, Aires<\/strong>, Papa, Toward a high-resolution monitoring of continental surface water extent and dynamics, at global scale: from GIEMS (Global Inundation Extent from Multi-Satellites) to SWOT (Surface Water Ocean Topography)<\/em><\/span>, May 2016, in book “Remote Sensing and Water Resources”.<\/div>\n<\/div>\n<\/div>\n<\/li>\n<\/ul>\n\n
ARTICLES:<\/strong><\/h4>\n
2026:<\/strong><\/h3>\n
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144 – Chen, Ciais, Hugelius, Aires<\/strong>, PeatCover: Towards a peat mapping at 90m using satellite remote sensing and a priori inventories<\/span><\/em>, RSE, in preparation, 2026.<\/li>\n
143 – Boucher, Aires<\/strong>, Doutriaux-Boucher, Introducing a New Partial Convolutional Neural Network for IASI Cloud Classification. JGR Atmospheres<\/span><\/em>, in review, 2026.<\/li>\n
142 – Dinh, Aires<\/strong>, Pellet, Convolutional Neural Network retrieval of intraday soil moisture from ASCAT observations<\/span><\/em>, submitted to J. of Hydrology, 2026.<\/li>\n
141 – Khairoun, Ciais, Nguyen, Qiu, Aires<\/strong>, Veraverbeke, Delcourt, Zhen, Chuvieco, Large scale assessment of fire impacts on Siberian peatlands carbon<\/em><\/span>, Science Advances, accepted, 2026.<\/li>\n<\/ul>\n
2025:<\/strong><\/h3>\n
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140 – Pellet, Aires<\/strong>, Boucher, Volden, Enhancing soil moisture retrieval capacity from SMOS using advanced neural networks<\/span><\/em>. <\/span><\/em>J. Applied Meteorology and Climatology, 10.1175\/JAMC-D-25-0041.1, 64, 12, 2025.<\/li>\n
139 – Heberger, Aires<\/strong>, Pellet, I<\/em>mproving Satellite Remote Sensing Estimates of the Global Terrestrial Hydrologic Cycle via Neural Network Modeling<\/em><\/span>, Journal of Hydrology, v. 662, Part B, 133825, https:\/\/doi.org\/10.1016\/j.jhydrol.2025.133825, 2025.<\/li>\n
138 – Dinh, Aires<\/strong>, Rahn, Climate change impact on Robusta coffee production in Vietnam<\/em><\/span>, Environmental Research Letter, 10.1088\/1748-9326\/ae14d1, Vol 20, Nb11, 114059, 2025.<\/li>\n<\/ul>\n
2024:<\/strong><\/h3>\n
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137 – Nguyen, and Aires<\/strong>, A new surface waters downscaling approach applicable at global scale<\/em><\/span>, Remote Sensing, 16(24), 10.3390\/ts16244664, 2024.<\/li>\n
136 – Pellet, Aires<\/strong>, Baez Villabuena, Filippucci, Estimating the Ebro river discharge at 1~km\/daily resolution using indirect satellite observations<\/span><\/em>, Environmental Research Communications, 6(9), 10.1088\/2515-7620\/ad7adb, 2024.<\/li>\n
135 – Normandin, Frappart, Bourrel, Blarel, Biancamaria, Wigneron, Galenon, Bernard, Coulon, Lubac, Marieu, Vantrepotte, Pham-Duc, Toan Do, Prigent, Aires<\/strong>, Yamazaki, & Ciais, <\/span>Sharp decline in surface water resources for agriculture and fisheries in the Lower Mekong Basin over 2000-2020<\/span><\/em>, Science of the Total Environment, 950, 10.1016\/j.scitotenv.2024.175259, 2024.<\/li>\n
134 – Lehner<\/i><\/span>, Anand<\/span>, Fluet-Chouinard<\/span>, Tan<\/span>, Aires<\/span><\/strong>, Allen<\/span>, Bousquet<\/span>, Canadell<\/span>, Davidson<\/span>, Finlayson<\/span>, Gumbricht<\/span>, Hilarides<\/span>, Hugelius<\/span>, Jackson<\/span>, Korver<\/span>, McIntyre<\/span>, Nagy<\/span>, Olefeldt<\/span>, Pavelsky<\/span>, Pekel<\/span>, Poulter<\/span>, Prigent<\/span>, Wang<\/span>, Worthington<\/span>, Yamazaki<\/span>, & Thieme, <\/span>Mapping the world’s inland surface waters: an update to the Global Lakes and Wetlands Database (GLWD v2)<\/span><\/em>, Earth System Science Data, 10.5194\/essd-2024-204, 2024.<\/li>\n
133 – Aires<\/strong>, Pellet, Introducing physical expert knowledge into AI models: An hybrid approach to close the water budget from satellite observations<\/span><\/em>, J. of Hydrometeorology, 10.1175\/JHM-D-23-0001.1<\/a>, 2024.<\/li>\n