• F. Aires
    Resolution des problèmes inverses en sciences de l’atmosphere : de l’observation a l’analyse, 
    Thèse de HDR, 856 pages, 2012.
  • F. Aires
    Problèmes inverses et reseaux de neurones : application a l’interferometre haute resolution IASI et a l’analyse de series temporelles, 
    Thèse de doctorat, 183 pages, 1999.


  • 141 – Aires, Atmospheric water vapour profiling over ocean/land and for clear/cloudy situations using microwave observations, pp. 215-255, in Remote Sensing of Clouds and Precipitation, Ed. C. Andronache, 277 p., ISBN 978-3-319-72582-6, 2018.
  •  140 – Prigent, Lettenmaier, Aires, 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), May 2016, in book “Remote Sensing and Water Resources”.



  • 139 – Aires, Weston, de Rosnay, Fairbairn, Statistical approaches to assimilate ASCAT soil moisture information: Part II Evaluation and potential for assimilation, QJRMS, submitted, 2024.
  • 138 – Boucher, Aires, Doutriaux-Boucher, Introducing a New Partial Convolutional Neural Network for IASI Cloud Classification. RSE, submitted, 2024.
  • 137 – Heberger, Aires, Pellet, Improving Satellite Remote Sensing Estimates of the Global Terrestrial Hydrologic Cycle via Neural Network Modeling, submitted, 2024.
  • 136 – Nguyen, Aires, Satellite retrieval and downscaling of the peatlands using machine learning, IEE Transactions on Geoscience and Remote Sensing, Submitted, 2024.
  • 135 – Dinh, Aires, Rahn, Climate change impact on coffee production over Vietnam and Brazil, submitted to Earth’s Future, 2024.
  • 134 – Nguyen, Aires, A Downscaling of surface waters at global scale, submitted Remote Sensing, 2024.
  • 133 – Aires, Pellet, Introducing physical expert knowledge into AI models: An hybrid approach to close the water budget from satellite observations, J. of Hydrometeorology, in review, 2024.
  • 132 – Hascoet, Pellet, Aires, Learning global evapotranspiration dataset corrections from a water cycle closure supervision,  Remote Sensing, 2024, 16(1), 170,  10.3390/rs16010170.


  • 131 – Pellet, Aires, TA physical/statistical data-fusion for the dynamical downscaling of GRACE data at daily and 1 km resolution, J. of Hydrology, Vol. 628, 2024, 10.1016/j.jhydrol.2023.130565, 2023.
  • 130 – Dinh, Aires, Revisiting the bias correction of climate models for impact studies, Climate Change, 176, 140 (2023). 10.1007/s10584-023-03597-y, 2023.
  • 129 – Nguyen, Aires, A global topography-based floodability index for the downscaling, analysis and data-fusion of surface water datasets, J. of Hydrology, 10.1016/j.jhydrol.2023.129406, vol 620, Part A, 129406, 2023.
  • 128 – Boucher, Aires, Towards a new generation of AI-based IASI retrievals of surface temperature: Part II: Assessment, QJRMS, 10.1002/qj.4472, Vol 149, 754, pp 1593-1611,2023.
  • 127 – Boucher, Aires, Pellet, Towards a new generation of AI-based IASI retrievals of surface temperature: Part I: Methodology, QJRMS, 10.1002/qj.4447, Vol 149, 753, pp 1180-1196, 2023.
  • Aires, Ciais, Qiu, Wang, A Neural Network Classification Framework for Monthly and High Spatial Resolution Surface Water Mapping in the Qinghai–Tibet Plateau from Landsat Observations, J. of Hydrometeorology, 24, 10, 10.1175/JHM-D-22-0211.1, 2023.
  • 125 – Fluet-Chouinard, Stocker, Zhang, Malhotra,  Melton, Poulter, Kaplan, Goldewijk, Siebert, Minayeva, Hugelius, Prigent, Aires, Hoyt, Davidson, Finlayson, Lehner, Jackson, McIntyre, Reconstruction of three centuries of wetland loss, Nature Geoscience, 614, 281-286, 10.1038/s41586-022-05572-6, 2023.
  • 124 – Boucher, Aires, Improving remote sensing of extreme cases using AI methods – Application to IASI, Environmental Research Letter, 10.1088/1748-9326/acb3e3, 18, 024025, 2023.
  • 123 – Ran, Aires, Ciais, Qiu, Hu, Fu, Xue, Wang, The Status and Influencing Factors of Surface Water Dynamics on the Qinghai-Tibet Plateau During 2000–2020, IEEE Trans. on Geoscience & Remote Sensing, 61, 1-14, 4200114, 10.1109/TGRS.2022.3231552, 2023.


  • 122 – Dinh, Aires, Rahn, Statistical analysis of the weather impact on Robusta coffee yield in Vietnam, Frontiers in Environmental Science, Sec. Interdisciplinary Climate Studies,, 20 June 2022, 2022.
  • 121 – Pellet, Aires, Yamazaki, Zhou, A first continuous and distributed satellite-based mapping of river discharge over the Amazon, J. of Hydrology, 614, Par 1,, 2022.
  • 120 – Fleischmann, Papa, Fassoni-Andrade, Melack, Wongchuig, Paiva, Hamilton, Fluet-Chouinard, Aires, Al Bitar, Bonnet, Coe, Ferreira-Ferreira, Barbedo, Hess, Jensen, McDonald, Ovando, Park, Parrens, Pinel, Prigent, Resende, Revel, Rosenqvist, Rosenqvist, Rudorff, Silva, Yamazaki, Collischonn, How much inundation occurs in the Amazon River basin?, RSE,, 2022.
  • 119 – Dinh, Aires, Nested leave-two-out cross-validation for the optimal crop yield model selection, Geoscientific Model Development, 15, 3519-3535, 10.5194/gmd-2021-218, 2022.


  • 118 – Bouillon, Safieddine, Whitburn, Clarisse, Aires, Pellet, Lezeaux, Scott, Clerbaux, Time evolution of the temperature profiles retrieved from 13 years of IASI data using an artificial neural network, Atmospheric Measurements Techniques, 10.5194/amt-2021-302, 2021
  • 117 – Fassoni-Andrade, Fleischmann, Papa, Wongchuig, Paiva, Moreira, Paris, Ruhoff, Barbosa, Maciel, Novo, Durand, Frappart, Aires, Ferreira-Ferreira, Espinoza, Laipelt, Melack, Stephane,  Espinoza-Villar, Pellet, Amazon hydrology from Space: Scientific advances and future challenges, Reviews of Geophysics, 10.1029/2020FG000728, 2021
  • 116 – Aires, Boucher, Pellet, Convolutional Neural Networks for satellite remote sensing at coast resolution. Application for the SST retrieval using IASI, RSE, 263, 112553, 10.1016/j.rse.2021.112553, 2021
  • 115 – Pellet, Aires, Yamazaki, Papa, Satellite monitoring of the water cycle over the Amazon using upstream/downstream dependency. Part~1: Methodology and initial evaluation, Water Resources Research, 57,5, 10.1029/2020WR028648, 2021.
  • 114 – Pellet, Aires, Yamazaki, Papa, Satellite monitoring of the water cycle over the Amazon using upstream/downstream dependency. Part~2: Mass-conserved reconstruction of total water storage change and river discharge, Water Resources Research, 57,5, 10.1029/2020WR028648, 2021.
  • 113 – Dorigo, Dietrich, Aires, Brocca, Dunkerley, Enomoto, Guntner, Hegglin, Hollmann, Hurst, Johannessen, Kummerow, Lee, Luojus, Looser, Miralles, Pellet, Recknagel, Vargas, Schenider, Schroder, Tapper, Vuglinsky, Wagner, Yu, Zappa, Zemp, Aich, Consistent monitoring of global water cycle variability across scales: What are we missing?, BAMS, 10.1175/BAMS-D-19-0316.1, 2021.
  • 112 – Aires, Weston, Fairbairn, De Rosnay, Statistical approaches to assimilate ASCAT soil moisture information: Part I Methodolgoies and first assessment, QJRMS, Vol 147, 746, pages 1823-1852, 10.1002/qj.3997, 2021.


  • 111 – Safieddine, Parracho, George, Aires, Pellet, Clarisse, Whitburn, Lezeaux, Thépaut, Hersbach, Radnoti, Goettsche, Martin, Doutriaux-Boucher, Coppens, August, Zhou, Clerbeaux, Artificial Neural Network to retrieve land and sea skin temperature from IASI, Remote Sensing, 12(17),10.3390/rs12172777, 2020.
  • 110 – Prigent, Kilic, Aires, Heygter, Pellet, Jimenez, Estimation of Sea Ice Concentration from multi-channel passive microwave satellite observations. Part 2: evaluation of a new methodology optimized for the Copernicus Imaging Microwave Radiometer, Remote Sensing, 12(10), 1594, 10.3390/rs12101590, 2020.
  • 109 – Kilic, Prigent, Aires, Heygster, Pellet, Jimenez, Ice concentration retrieval from the analysis of microwaves: a new methodoloy designed for the Copernicus Imaging Microwave Radiometer (CIMR), Remote Sensing,12(7):1060, 10.3390/rs12071060, 2020.
  • 108 – Fleischmann, Paiva, Collischonn, Siqueira, Paris, Moreira, Papa, Bitar, Parrens, Aires, Garambois, Trade-offs between 1D and 2D regional river hydrodynamic models, Water Resources Research, 56(8), 10.1029/2019WR026812, 2020.
  • 107 – Aires, Venot, Massuel, Gratiot, Pham-Duc, Prigent, Surface water evolution (2001-2017) at the Cambodia/Vietnam border in the Upper Mekong Delta using satellite MODIS observations, Remote Sensing, 12(5), 8000,, 2020.
  • 106 – Aires, and Pellet, Estimating retrieval errors from neural network inversion schemes – Application to the retrieval of temperature profiles from IASI, IEEE TGRS, p. 1-11, 10.1109/TGRS.2020.3026944, 2020.
  • 105 – Pellet, Aires, Papa, Munier, Decharme, Long-term total water storage change from a SAtellite Water Cycle (SAWC) reconstruction over large South Asian basins, Hydrol. Earth Syst. Sci., 24, 3033–3055, 2020,
  • 104 – Wang, Zhuang, Aires, Prigent, Yu, Keller, Bridgham, Simulating Holocen peat soil carbon accumulation in North America, JGR-Biosphere,, 2020.
  • 103 – Aires, F., Surface water maps de-noising and missing-data filling using determinist spatial filters based on several a priori information, RSE, i237 111481,, 2020.


  • 102 – Rodriguez-Fernandez, de Rosnay, Albergel, Richaume, Aires, Prigent, Kerr, SMOS neural network soil moisture data assimilation in a land surface model and atmospheric impact, Rem. Sens., 11, 1334, 10.3390/rs11111334, 2019.
  • 101 – Daskin, F. Aires , A.C. Staver, Determinants of tree cover in tropical floodplains: climate, fire, and hydrology, PNASS, 286, 1914, ,, 2019.
  • 100 – Dinh, L-A, and F. Aires, River discharge estimation based on satellite water extent and topography at high spatial resolution – An application over the Amazon, J. of Hydrometeorology, 10.1175/JHM-D-18-0206.1, 2019.
  • 99 – Favrichon, S., C. Prigent, C. Jimenez, and F. Aires, Detecting cloud contamination in passive microwave satellite measurements over land, Atmos. Meas. Tech., 12, 1531-1543, 10.5194/amt-12-1531-2019, 2019.
  • 98 – Kilic, L., P. Catherine, F. Aires, J. Boutin, G. Heygster, R. Tonboe, H. Roquet, Expected performances of the Copernicus Imaging Microwave Radiometer (CIMR) for an all-weather and high spatial resolution estimation of ocean and sea ice parameters, JGR-Oceans, 123(10), 7564-7580, 10.1029/2018JC014408, 2019.
  • 97 – Pellet, V., F. Aires, S. Munier, D. Fernández Prieto, G. Jordá, W.A. Dorigo, J. Polcher, and L. BroccaOptimisation of satellite observations to study the water cycle over the Mediterranean region, 23(1), Hydrol. Earth Syst. Sci., 465-491, doi: 10.5194/hess-23-465-2019, 2019.
  • 96 – Pham-Duc, B., F. Papa, C. Prigent, F. Aires, S. Biancamaria, and F. FrappartVariations of surface and subsurface water storage in the Lower Mekong Basin (Vietnam and Cambodia) from Multisatellite Observations, Water, 11, 75, 23(1), doi: 10.3390/w11010075, 2019.


  • 95 – Aires, F., C. Prigent, F. Papa, E. Fluet-Chuinard, B. Lehner, and D. Yamazaki, Comparison of visible (G3WBM and GSWO) and multi-satellite (GIEMS-D3) global inundation datasets at high-spatial resolution, RSE, 216, 427-441, 10.1016/j.rse.2018.06.015, 2018.
  • 94 – Pellet, V., and F. Aires, Analyzing the Mediterranean water cycle via satellite data integration, Pure Appl. Geophys, 10.1007/s00024-018-1912-z, 1-29, 2018.
  • 93 – Aires, F., C. Prigent, S. Buehler, M. Milz, P. Eriksson, and S. Crewell, Towards more realistic hypotheses for the information content analysis of cloudy/precipitating situations – Application to the hyper-spectral instrument in the microwaves, QJRMS, 10.1002/qj.3315, 2018.
  • 92 – Alemohammad, S.H., Kolassa, J., Prigent, C., Aires, F. and Gentine, P. Global Downscaling of Remotely-Sensed Soil Moisture using Neural Networks, HESS, 10.5194/hess-2017-680, 2018.
  • 91 – Pellet, V., F. AiresBottleneck channels algorithm for satellite dimension reduction: A case study for IASI, IEEE TGRS, 56, 10, 6069-6081, 10.1109/TGRS.2018.2830123, 2018.
  • 90 – Mathieu, J., and F. AiresSUsing neural network classifier approach for statistically forecasting extreme corn yield losses in Eastern United States, Earth and Space Science, 10.1029/2017EA000343, 2018.
  • 89 – Mathieu, J., and F. Aires, Impact of agro-climatic indices to improve crop yield forecasting, Agriculture and Forest Meteorology, 253-254, 15-30, 2018.


  • 88 – Munier, S., F. AiresA new global method of satellite dataset merging and quality characterization constrained by the terrestrial water cycle budget, RSE, 205:119-130, 10.1016/J.rse.2017.11.008, 2017.
  • 87 – Alemohammad, S.H., B. Fang, A.G. Konings, J.K. Green, J. Kolassa, C. Prigent, F. Aires, D. Miralles, and P. Gentine, Water, energy, and carbon with artificial neural networks (WECANN): A statistically-based estimate of global surface turbulent fluxes using solar-induced fluorescence, Biogeosciences, 14, 4101-4124, 10.5194/bg-14-4101-2017, 2017.
  • 86 – Wang, D., C. Prigent, L. Killic, S. Fox, C. Jimenez, F. Aires, C. Grassoti, and F. Karbou, Surface emissivity at microwaves to millimeter waves over polar regions: parameterization and evaluation with aircraft experiments, J. Atmos. and Ocean. Technology, 34(5), 10.1175/JTECH-D-16-0188.1, 2017.
  • 85 – Salameh, E., F. Frappart, F. Papap, A. Guntner, V. Venugopal, A. Getirana, C. Prigent, F. Aires, D. Labat, and B. Laignel, Fifteen years (1993-2007) of surface freshwater storage variability in the Ganges-Brahmaputra River basin using multi-satellite observations, Water, 9(4), 245; 10.3390/w9040245, 2017.
  • 84 – Kolassa, J., P. Gentine, F. Aires, and C. Prigent,  Remote sensing of soil moisture using AMSR-E and ASCAT synergy. Part 2: Product Evaluation, RSE, 195:202-217, 10.1016/j.rse.2017.04.020, 2017.
  • 83 – Pham-Duc, B., C. Prigent, F. AiresSurface water monitoring in the Mekong delta over a year with Sentinel-1 SAR observations, Water, 9, 6, 366, 10.3390/w9060366, 2017.
  • 82 – Prigent, C., F. Aires, D. Wang, S. Fow, S. Harlow, Sea-surface emissivity parameterization from microwaves to millimeter waves, QJRMS, 143, 702, 596–605, 10.1002/qj.2953, 2017.
  • 81 – Pham-Duc, B., C. Prigent, F. Aires, and F. Papa, Comparisons of global terrestrial surface water datasets over 15 years, J. of Hydrometeorology, 10.1175/JHM-D-16-0206.1, 2017.
  • 80 – Aires, F., L. Miolane, C. Prigent, E. Fluet-Chouinard, B. Lehner, and F. Papa, A global, long-term and high spatial resolution inundation extent databaseJ. Hydrometeorology, 10.1175/JHM-D-16-0155.1, 2017.


  • 79 – Wang, D., C. Prigent, F. Aires, and C. Jimenez, A statistical retrieval of cloud parameters for millimeter wave Ice Cloud Imager on board Metop-SG, IEEE TGRS, 99, 10.1109/ACCESS.2016.2625742, 2016.
  • 77 – Mathieu, J., and F. AiresStatistical impact models for agriculture: an application of mixed-effects and neural networks for corn over USA, J. Appl. Meteor. Climatol., 10.1175/JAMC-D-16-0055.1, 2016.
  • 76 – Prigent, C., C. Jimenez, F. AiresTowards an “all-weather”, long record, and real-time surface temperature retrievals from microwave satellite observations, JGR, 10.1002/2015JD024402, 2016.
  • 75 – Pellet, V., and F. Aires, F., Dimension reduction of satellite observations for remote sensing, Part II: Illustration using hyper-spectral microwave observations, QJRMS, 10.1002/qj.2857, 2016.
  • 74 – Aires, F., V. Pellet, C. Prigent, J.-L. Moncet, Dimension reduction of satellite observations for remote sensing, Part I: A comparison of compression, channel selection, and bottleneck channel approaches, QJRMS, 10.1002/qj.2855, 2016.
  • 73 – Kolassa, J., P. Gentine, C. Prigent, and F. Aires,  Remote sensing of soil moisture using AMSR-E and ASCAT observations, RSE, 1-73, 1-14, 2016.
  • 72 – Prigent, C., Lettenmeyer, F. Aires and F. Papa, Challenges in satellite remote sensing of continental hydrology, Surveys in Geophysics, 10.1007/s10712-015-9339, 37 (2), pp 339–3552015, 2016.


  • 71 – Pan, M., C.K. Fisher, N.W. Chaney, W. Zhan, F. Aires, W.T. Crow, D. Entekhavi, and E. Wood, Triple collocation: Beyond three estimates and separation of structural/non-structural errors, RSE, 171, 299-310, 2015.
  • 70 – Birman, C., J.-F. Mahfouf, F. Aires, C. Prigent, E. Orlandi, and M. Milz, Information content on temperature and water vapour from an hyper-spectral microwave sensor, QJRMS, 10.1002/qj.2608, 2015.
  • 69 – Rodriguez-Fernandez, N.J., F. Aires, P. Richaume, F. Cabot, C. Jimenez, J. Kerr, J. Kolassa, A. Mahmoodi, C. Prigent, and M. Drush, Soil moisture retreival from SMOS observations using neural networks, IEEE TGRS, 53, 11, 10.1109/TGRS.2015.2430845, 2015.
  • 68 – Lipton, A.E., P Liang, C. Jimenez, J.-L. Moncet, F. Aires, C. Prigent, R. Lynch, J.F. Galantowicz, R.P. d’Entremont and G. Uymin, Sources of discrepancies between satellite-derived and land surface model estimates of latent heat fluxes, JGR, 120, 2324-2341, 10.1002/2014JD022641, 2015.
  • 67 – Prigent, C., P. Liang, Y. Tian, F. Aires, J.-L. Moncet, and S.-A. Boukabara, Evaluating modeled microwave emissivity, JGR, 120, 2706-2718, 10.1002/2014JD021817, 2015.
  • 66 – Aires, F., C. Prigent, E. Orlandi, M. Miltz, P. Eriksson, and S. Crewell, Microwave hyper-spectral measurements for temperature and humidity atmospheric profiling – Par I: Clear-sky case, JGR, 120, 21, 11,334-11,351, 10.1002/2015JD023331, 2015.
  • 65 – Papa, F., F. Frappart, Y. Malbeteau, M. Shamsudduha, V. Venugopal, M. Sekhar, G. Ramillien, C. Prigent, F. Aires, R.K. Pandey, S. Bala, and S. Calmant, Satellite-derived surface and sub-surface water storage in the Ganges-Brahmaputra river basin, JoH: Regional studies, 10.1016/j.ejrh.2015.03.004, 2015.
  • 64 – Munier, S., F. Aires, S. Schlaffer, C. Prigent, F. Papa, P. Maisongrande, and M. Pan, Combining datasets of satellite retrieved products. Part II: Evaluation on the Mississippi Basin and closure correction model, JGR, 10/2014, 10.1002/2014JD021953, 2015.
  • 63 – Prigent, C., F. Aires, C. Jimenez, F. Papa and J. Roger, Multi-angle backscattering observations of continental surfaces in Ku band (13 GHz) from satellites: understanding the signals, especially in arid regions, IEEE Trans. on Geoscience and Rem. Sens., 53, 3, 2015.


  • 62 – Matsui, T., J. Santanello, J. Shi, W-K Tao, D. Wu, C. Peters-Lidard, E. Kemp, M. Chin, D. Starr, M. Sekigushi, and F. AiresIntroducing multisensor satellite radiance-based evaluation for regional Earth system modeling, JGR, 119: 10.1002/jgrd.v119.13, 8450-8475, 2014.
  • 61 – Paul, M., and F. AiresUsing Shannon’s entropy to sample heterogeneous and high-dimensional atmospheric datasets, QJRMS, 10.1002/qj.2373, 2014.
  • 60 – Aires, F. Combining datasets of satellite retrieved products. Part I: Methodology and water budget closure, J. of Hydrometeor., 10.1175/JHM-D-13-0148.1, 2014.
  • 59 – Aires, F., F. Papa, C. Prigent, J.-F. Crétaux and M. Berge-Nguyen, Characterization and downscaling of the inundation extent over the Inner Niger delta using a multi-wavelength retrievals and Modis data, J. of Hydrometeoroloy, 27, 1958-1979, 10.1175/JCLI-D-13-00161.1, 2014.
  • 58 – Aires, F., P. Gentine, K. Findell, B.R. Lintner, and C. Kerr, Neural network-based sensitivity analysis of summertime convection over continental US, J. of Clim., 27, 1958-1979, 10.1175/JCLI-D-13-00161.1, 2014.


  • 57 – Papa, F., F. Frappart, A. Guntner, C. Prigent, F. Aires, W.B. Rossow, A. Getirana, and R. Maurer, Surface freshwater storage and variability in the Amazon basin from multi-satellite observations, 1993-2007, JGR, 118, 21, 11.951-11.965, 10.1002/2013JD020500, 2013.
  • 56 – Foley, E., A. Friend, D. Dalmonech, F. Aires, A. Archibald, P. Bartlein, L. Bopp, J. Chappellaz, P. Cox, N. Edwards, G. Feulner, P. Friedlingtein, S. P. Harrison, P.O. Hopcroft, C.D. Jones, J. Kolassa, J. Levine, I.C. Prentice, J. Pyle, N. Vazquez Riveiros, E. Wolff, S. Zaehle, Improving constraints on biopheric feedbacks in Earth system models, Biogeosciences Discuss, 10, 10937-10995, 10.5194/bgd-10-10937-2013, 2013.
  • 55 – Jimenez, C., D.B. Clark, J. Kolassa, F. Aires, C. Prigent, and E. Blyth, A joint analysis of modeled soil moisture fields and satellite observations, JGR, 118, 12, 6771-6782, 2013.
  • 54 – Prigent, C., F. Aires, F. Bernardo, J.-C. Orlhac, J.-M. Goutoule, H. Roquet, and C. Donlon, Analysis of the potential and limitation of microwave radiometry for the retrieval of Sea Surface Temperature: Definition of new mission concepts, JGR, 118, 6, 3074-3086, 10.1002/jgrc.20222, 2013.
  • 53 – Tian, Y., C.D. Peters-Lidard, K.W. Harrison, C. Prigent, H. Norouzi, F. Aires, S.-A. Boukabara, F.A. Furuzawa, and H. Masunaga, Quantifying uncertainties in land surface microwave emissivity retrievals, IEEE TGRS, 99, 10.1109/TGRS.2013.2244214, 2013.
  • 52 – Aires, F., F. Papa and C. Prigent, A long-term, high-resolution wetland dataset over the Amazon basin, downscaled from a multi-wavelength retrieval using SAR, J. of Hydrometeorology, 14, 594-6007, 2013.
  • 51 – Kolassa, J., F. Aires, J. Polcher, C. Prigent, C. Jimenez, and J.M. Pereira, Soil moisture retrieval from multi-instrument observations: Part I – Information content analysis and retrieval methodology, JGR, 118, 10, 4847-4859, 10.1029/2012JD018150, 2013.


  • 50 – Aires, F., O. Aznay, C. Prigent, M. Paul, F. Bernardo, Synergetic multi-wavelegnth remote sensing versus a posteriori combination of retrieved products: Application for the retrieval of atmospheric profiles using MetOp measurements, JGR, 117, D18304, 10.1029/2011JD017188, 2012.
  • 49 – Ferraro, R., C. Peters-Lidard, C. Hernandez, F.J. Turk, F. Aires, C. Prigent, W. Lon, S-A. Boukabara, F. Furuzawa, K.Gopalan, K. Harrison, F. Karbou, L. Li, C. Liu, H. Masunaga, L. Moy, S.Ringerud, G. Skofronick-Jackson, Y. Tian, N-Y. Wang, An evaluation of microwave land surface emissivities over the continental UnitedStates to benefit GPM-era precipitation algorithms. IEEE Trans. on Geosci. and Rem. Sens., 99, 1-31, 10.1109/TGRS.2012.2199121, 2012.
  • 48 – Aires, F., Using random-effect models to build impact indices when the available historical record is short, J. Appl. Meteorol. and Climat., 51, 1994-2004, 10.1175/JAMC-D-11-0125.1, 2012.
  • 47 – Paul, M., F. Aires, and C. Prigent, An innovative physical scheme to retrieve simultaneously surface temperature and emissivities based on a high-resolution infrared emissivity interpolator, JGR, 117, D11302, 10.1029/2011JD017296, 2012.
  • 46 – Prigent, C., F. Papa, F. Aires, C. Jimenez, W.B. Rossow, E. Matthews, Changes in land surface water dynamics since the 1990s and relation to population pressure, GRL, 39, L08403, 10.1029/2012GL051276, 2012.
  • 45 – Bernardo, F., F. Aires, and C. Prigent, Atmospheric water vapour retrieval from microwave instruments – Part II : Evaluation for the Megha-Tropiques mission, QJRMS, 10.1002/qj.1946, 2012.
  • 44 – Aires, F., Bernardo, F., and C. Prigent, Atmospheric water vapour retrieval from microwave instruments – Part I : Methodology, QJRMS, 10.1002/qj.1888, 2012.


  • 43 – Prigent, C., J. Catherinot, R. Maurer, F. Papa, C. Jimenez, F. Aires, and W.B. Rossow, Evaluation of ‘all weather’ microwave-derived land surface temperatures with in situ CEOP measurements, JGR, 116, D23105, 10.1029/2011JD016439, 2011.
  • 42 – Prigent, C., N. Rochetin, F. Aires, E. Defer, J-Y Grandpeix, C. Jimenez, F. Papa, Impact of the inundated areas on the deep convection at continental scale from satellite observations and modeling experiments, JGR, 116, D24118, 10.1029/2011JD16311, 2011.
  • 41 – Aires, F., Marquisseau, F., Prigent, C., and Seze, G., A land and ocean microwave cloud classification derived from AMSU-A and -B, calibrated on MSG-SEVIRI infrared and visible observations, MWR, 139, 2347-2366, http://dx/, 2011.
  • 40 – Aires, F., C. Prigent, F. Bernardo, C. Jimenez, R. Sounders, and P. Brunel, A Tool to Estimate Land Surface Emissivities in the Microwaves (TELSEM) for use in numerical weather prediction schemes. QJRMS, 137: 690-699, 10.1002/qj.803, 2011.
  • 39 – Aires, F., Measure and exploitation of multi-sensor and multi-wavelength Synergy for remote sensing: Part I – Theoretical considerations, JGR, 116, D02301, 10.1029/2010JD014701, 2011.
  • 38 – Aires, F., M. Paul, C. Prigent, B. Rommen, and M. Bouvet, Measure and exploitation of multi-sensor and multi-wavelength Synergy for remote sensing: Part II – An application for the retrieval of atmospheric temperature and water vapour from METOP, JGR, 116, D02302, 10.1029/2010JD014702, 2011.


  • 37 – Aires, F., F. Bernardo, H. Brogniez, and C. Prigent, Calibration for the inversion of satellite observations, J. of Applied Meteorology and Climatology, 49, 12, 2458-2473, 2010.
  • 36 – Papa, F., C. Prigent, C. Jimenez, F. Aires, W.B. Rossow, and E. Matthews, Interannual variability of surface water extent at global scale, 1993-2004, JGR, 115, D12111, 10.1029/2009JD012674., 2010.


  • 35 – Jimenez, C., C. Prigent and F. AiresToward an estimation of global land surface heat fluxes from multisatellite observation, JGR, 114, D06305, 10.1029/2008JD011392, 2009.
  • 34 – Cheruy F., and F. AiresCluster analysis of cloud properties over the Southern Europe Mediterranean area in observations and a model, MWR, 137, 10, 3161-3176, 2009.


  • 33 – Decharme B., H. Douville, C. Prigent, F. Papa, and F. AiresA new river flooding scheme for global climate applications: Off-line evaluation over South America, JGR, 113, D11110, 10.1029/2007JD009376, 2008.
  • 32 – Defer, E., C. Prigent, F. Aires, J.R. Pardo, C.J. Walden, O.-Z. Zanife, J.-P. Chaboureau and J.-P Pinty, Development of precipitation retrievals at millimeter and submillimeter wavelengths for geostationary satellites. JGR, 113, D08111, 10.1029/2007JD008673, 2008.
  • 31 – Prigent, C., E. Jaumouille, F. Chevallier, and F. AiresA parameterization of the microwave land surface emissivity between 19 and 100 GHz, anchored to satellite-derived estimates, IEEE Trans. on Geosci. and Rem. Sens., 46, 344-352, 2008.


  • 30 – Aires, F., and C. Prigent, Sampling Techniques in High-Dimensional Spaces for Satellite Remote Sensing Databases Generation. JGR, 112, D20301, 10.1029/2007JD008391, 2007.
  • 29 – Prigent, C., F. Papa, F. Aires, and W.B. Rossow Global inundation dynamics inferred from multiple satellite observations, JGR, 112, D12107, 10.1029/2006JD007847, 2007.


  • 28 – Aires, F., and C. Prigent, F. Aires Toward a new generation of satellite surface products? JGR, 111, D22S10, 10.1029/2006JD007362, 2006.
  • 27 – Prigent, C., F. Aires, and W.B. Rossow Land Surface Microwave Emissivities over the Globe for a Decade. Bulletin of the American Meteorological Society, 10.1175/BAMS-87-11-1573, 1572-1584, 2006.
  • 26 – Cordisco, E., C. Prigent, and F. AiresSnow characterization at a global scale with passive microwave satellite observations. JGR, 10.1029/2005JD006773, 111, D19, D19301, 2006.
  • 25 – Chen, Y., F. Aires, J.A. Francis, and G.L. Russell, Observed relationships between longwave cloud forcing and cloud parameters at SHEBA using a neural network. J. of Climate, 10.1175/JCLI3839.1, 19, 16, 4087-4104, 2006.


  • 24 – Aires, F., Prigent, C., and Rossow, W.B., Soil moisture at a global scale. II – Global statistical relationships. JGR, 110, D11, D11103, 10.1029/2004JD005094, 2005.
  • 23 – Prigent, C., Aires, F., and Rossow, W.B., Soil moisture at a global scale. I – Presentation of the satellite observations and analysis of their relations with in situ soil moisture measurements. JGR, 110, D7, D07110,10.1029/2004JD005087, 2005.
  • 22 – Prigent, C., Tegen, I., Aires, F., Marticorena, B., and Zribi, M., Estimation of the aerodynamic roughness length in arid and semi-arid regions over the globe with the ERS scatterometer. JGR, 110, D9, D09205 10.1029/2004JD005370, 2005.
  • 21 – Karbou, F., Aires, F., Prigent, C., Retrieval of temperature and water vapor atmospheric profiles over Africa using AMSU microwave observations. JGR, 110, D7, D07109 10.1029/2004JD005318, 2005.


  • 20 – Aires, F., Neural network uncertainty assessment using Bayesian statistics with application to remote sensing: 1. Network weights. JGR, 109, D10303, 10.1029/2003JD004173, 2004.
  • 19 – Aires, F., C. Prigent, and W.B. Rossow, Neural network uncertainty assessment using Bayesian statistics with application to remote sensing: 2. Output errors. JGR, 109, D10304, 10.1029/2003JD004174, 2004.
  • 18 – Aires, F., C. Prigent, and W.B. Rossow, Neural network uncertainty assessment using Bayesian statistics with application to remote sensing: 3. Network Jacobians. JGR, 109, D10305, 10.1029/2003JD004175, 2004.
  • 17 – Aires, F., C. Prigent, and W.B. Rossow, Temporal interpolation of global surface skin temperature diurnal cycle over land under clear and cloudy conditions. JGR, 109, D04313, 10.1029/2003JD003527, 2004.
  • 16 – Aires, F., C. Prigent, and W.B. Rossow, Neural network uncertainty assessment using Bayesian statistics: A remote sensing application. Neural Computation, 16, 2415-2458, 2004.


  • 15 – Aires, F., and W.B. Rossow, Inferring instantaneous, multivariate and nonlinear sensitivities for the analysis of feedback processes in a dynamical system: The Lorenz model case study. QJRMS, 129, 239-275, 2003.
  • 14 – Chen, Y., J.R. Miller, J.A. Francis, G.L. Russell, and F. AiresObserved and modeled relationships among Arctic climate variables. JGR, 108, D24, 4799, 10.1029/2003JD003824, 2003.
  • 13 – Prigent, C., F. Aires, and W.B. Rossow, Retrieval of surface and atmospheric geophysical variables over snow from microwave satellite observations. JAM, 42, 368-380, 10.1175/1520-0450(2003) 042<0368:ROSAAG>2.0.CO;2, 2003.
  • 12 – Prigent, C., F. Aires, and W.B. Rossow, Land surface skin temperatures from a combined analysis of microwave and infrared satellite observations for an all-weather evaluation of the differences between air and skin temperatures. JGR, 108, D10, 4310, 10.1029/2002JD002301, 2003.


  • 11 – Aires, F., W.B. Rossow, and A. Chédin, Rotation of EOFs by the Independent Component Analysis: Towards a Solution of the Mixing Problem in the Decomposition of Geophysical Time Series, JAS, 59, 1, 111-123, 2002.
  • 10 – Aires, F., W.B. Rossow, N. Scott, and A. Chédin, Remote sensing from the IASI instrument. 1 Compression, de-noising, and first-guess retrieval algorithms, JGR, 107, no. D22, 4619, 10.1029/2001JD000955, 2002.
  • 9 – Aires, F., W.B. Rossow, N. Scott, and A. Chédin, Remote sensing from the IASI instrument. 2 Simultaneous retrieval of temperature, water vapor and ozone atmospheric profiles, JGR, 107, D22, 4620, 10.1029/2001JD001591, 2002.
  • 8 – Aires, F., A. Chedin, N. Scott, and W.B. Rossow,
    A regularized neural network approach for retrieval of atmospheric and surface temperatures with the IASI instrument, JAM, 41, 2, 144-159, 2002.


  • 7 – Prigent, C., E. Matthews, F. Aires, and W. B. Rossow, Remote sensing of global wetland dynamics with multiple satellite data sets, GRL, 28 , 24 , 4,631-4,634, 2001.
  • 6 – Prigent, C., F. Aires, W. B. Rossow, and E. Matthews, Joint characterization of the vegetation by satellite observations from visible to microwavelengths: a sensitivity analysis, JGR, 106, D18, 20,665-20,685, 2001.
  • 5 – Aires, F. C. Prigent, W.B. Rossow, and M. Rothstein, A new neural network approach including first-guess for retrieval of atmospheric water vapor, cloud liquid water path, surface temperature and emissivities over land from satellite microwave observations, JGR, 106, D14, 14,887-14,907, 2001.


  • 4 – Aires F., Chédin A. and Nadal J.-P. Independent component analysis of multivariate time series. Application to the tropical SST variability. JGR, 105 , D13, 17,437-17,455, 2000.
  • 3 – Nadal J.-P., Korutcheva E. and Aires F., Blind source separation in the presence of weak sources, Neural Networks, 13, 6, 589-596, 2000.


  • 2 – Aires F., Chédin A. and Nadal J.-P. Analysis of geophysical time series and information theory: Independent Component Analysis, CRAS IIa, 328, 569-575, 1999.
  • 1 – Aires, F., M. Schmitt, N. Scott and A. Chédin, The Weight Smoothing regularisation for MLP for resolving the input contribution’s errors in functional interpolations. IEEE Trans. on Neural networks, 10, 6, 1502-1510, 1999.