top of page

Journal Articles:​

  1. A. Afshar, M.A. Mariño, A. Ebtehaj, Moosavi J., (2007), "Rule-based fuzzy systems for assessing groundwater vulnerability" ASCE, J. of Environ. Eng., 133(5), 532-540.

  2. Ebtehaj, A., H. Moradkhani, and H. V. Gupta (2010), "Improving the robustness of hydrologic parameter estimation by the use of moving block bootstrap resampling", Water Resour. Res., 46, W07515, doi:10.1029/2009WR007981

  3. Ebtehaj, A., and E. Foufoula-Georgiou (2010), "Orographic signature on multiscale statistics of extreme rainfall: A storm-scale study", J. Geophys. Res., 115, D23112, doi:10.1029/2010JD014093.

  4. Ebtehaj, A., and E. Foufoula-Georgiou (2011), "Statistics of precipitation reflectivity images and cascade of gaussian scale mixtures", J. Geophys. Res., 116, D14110, doi:10.1029/2010JD015177.

  5. Ebtehaj, A., E. Foufoula-Georgiou (2011), "Adaptive fusion of multi-sensor precipitation using Gaussian scale mixtures in the wavelet domain", J. Geophys. Res.,116,D22110,  doi:10.1029/2011JD016219.

  6. Ebtehaj, A., E. Foufoula-Georgiou, G. Lerman (2012),"Sparse regularization for precipitation downscaling", J. Geophys. Res., 117, D08107, doi:10.1029/2011JD017057. [MATLAB codes]

  7. Ebtehaj, A., E. Foufoula-Georgiou (2013), "On variational downscaling, fusion, and assimilation of hydro-meteorological states: A unified framework via regularization", Water Resour. Res., vol. 49, 1–20, doi:10.1002/wrcr.20424, 2013

  8. Foufoula-Georgiou E., A.M. Ebtehaj, S.Q. Zhang, A.Y. Hou (2013), "Downscaling satellite precipitation with emphasis on extremes: A variational l1-norm regularization in the derivative domain", Surv. in Geophysics, 10.1007/s10712-013-9264-9.

  9. Ebtehaj, A., M. Zupanski, G. Lerman, E. Foufoula-Georgiou (2014), "Variational data assimilation via sparse regularization", Tellus A, 2014, 66, 21789.

  10. Lipeng N., F. P. Carli, A. Ebtehaj, E. Foufoula-Georgiou, T.T. Georgiou (2014), "Coping with the model error in data assimilation using optimal mass transport", Water Resour. Res.,  doi: 10.1002/2013WR014966.

  11. Lin L., A. Ebtehaj, R. L. Bras, A. Flores, J. Wang (2015), "Dynamical precipitation downscaling for hydrologic applications via WRF 4D-var data assimilation with Implication in GPM era", J. Hydrometeorl, 16, 811-829.

  12. Ebtehaj, A., R.L. Bras, E. Foufoula-Georgiou (2015), "Shrunken locally linear embedding for passive microwave retrieval of precipitation", IEEE Trans. on Geosci. and Remote Sens., vol 53(7), doi:10.1109/TGRS.2014.2382436. [MATLAB codes]

  13. Ebtehaj, A, E. Foufoula-Georgiou, G. Lerman, R.L. Bras (2015), "Compressive earth observatory: An insight from AIRS/AMSU retrievals", Geophys. Res. Lett., 42, 362-369, doi:10.1002/2014GL062711. [MATLAB codes]

  14. Ebtehaj, A, R.L. Bras, E. Foufoula-Georgiou (2016), "Evaluation of ShARP passive rainfall retrievals over snow-covered land surfaces and coastal zones", J. Hydrometeor, 17, 1013–1029.doi: http://dx.doi.org/10.1175/JHM-D-15-0164.1

  15. Moghim S., S McKnight, K Zhang, A. Ebtehaj, R. Knox, R. Bras, M. Paul, J. Wang (2016), "A Bias-corrected Data set of Climate Model Outputs at Uniform Space-time Resolution for Land Surface Modeling over Amazonia", Int. J. of Climatology, doi -10.1002/joc.4728 SP 

  16. Lin L., A. Ebtehaj, R. L. Bras, and J. Wang (2017), "Soil Moisture Background Error Covariance and Data Assimilation in a Coupled Land-Atmosphere Model", Water Resour. Res., doi: 10.1002/2015WR017548

  17. Takbiri Z., A. Ebtehaj, and E. Foufoula-Georgiou (2017), "A Multi-sensor Data-driven methodology for all-sky Passive Microwave Inundation Retrieval", Hydrol. Earth Syst. Sci., 21, 2685-2700, https://doi.org/10.5194/hess-21-2685-2017, 2017.

  18. EbtehajA. and C. D. Kummerow (2017), "Microwave Retrievals of Terrestrial Precipitation over Snow Covered Surfaces: A Lesson from the GPM Satellite", Geophys. Res. Lett., doi: 10.1002/2017GL073451

  19. Lin L., A. Ebtehaj, L. Flores, S. Bastola, and R. L. Bras (2017), "Joint Variational Data Assimilation of Satellite Precipitation and Soil Moisture: A Case Study Using TRMM and SMOS Data", Mon. Weather Rev., https://doi.org/10.1175/MWR-D-17-0125.1

  20. Hassan-Esfahani L., A.M. Ebtehaj, A. Torres-Rua and M. McKee (2017), "Spatial Scale Gap Filling Using an Unmanned Aerial System: A Statistical Downscaling Method for Applications in Precision Agriculture", Sensor, http://www.mdpi.com/1424-8220/17/9/2106. 

  21. Stefan H. Ellis. C., Gulliver J., Hondzo M., Paolo C., Marr J., Hill K., Guala, M., Ebtehaj A., Voller, V., Erickson. A., Kozarek, J., Hansen A., The St. Anthony Falls Laboratory: 80 Years of Progress Part 2A., Transition to Environmental Research, World Environmental and Water Resources Congress 2018, https://ascelibrary.org/doi/10.1061/9780784481394.016.

  22. Takbiri Z.*, A. Ebtehaj, E Foufoula-Georgiou, P. E. Kirstetter, J. Turk (2018), A Prognostic Retrieval Approach for Microwave Precipitation Phase Detection over Snow Cover, J. of Hydrometeor, https://doi.org/10.1175/JHM-D-18-0021.1.

  23. Ebtehaj, A., R. L. Bras (2019), A Physically Constrained Inversion for Super-resolved Passive Microwave Retrieval of Soil Moisture and Vegetation Water Content in L-band, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2019.111346, arxiv 1806.03298. [MATLAB codes]

  24. Tamang S.K.*, A. Ebtehaj, A. F. Prein, A. J. Heymsfield (2019), Linking Global Changes of Snowfall and Wet-bulb Temperature, Journal of Climate, https://doi.org/10.1175/JCLI-D-19-0254.1., arxiv 1905.07776.

  25. Ebtehaj. A , C. D. Kummerow, F. J. Turk (2019), Metric Learning for Approximation of Microwave Channel Error Covariance: Application for Satellite Retrieval of Drizzle and Light SnowfallIEEE Trans. on Geosci. and Remote Sens., doi:10.1109/TGRS.2019.2941682. 

  26. Sadeghi M.*, A. Ebtehaj, W. T. Crow, L. Gao, A. J. Purdy, J. B. Fisher, S. B. Jones, E. Babaeian, and M. Tuller (2019), Global Estimates of Land Surface Water Fluxes from SMOS and SMAP Satellite Soil Moisture Data, J. of Hydrometeorology   https://doi.org/10.1175/JHM-D-19-0150.1

  27. Gao L.*, M. Sadeghi*, A. Ebtehaj (2020), Microwave Retrievals of Soil Moisture and Vegetation Optical Depth with Improved Resolution using a Combined Constrained Inversion Algorithm: Application for SMAP Satellite, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2020.111662[MATLAB codes]. 

  28. Sadeghi M.*, L. Gao*, A. Ebtehaj, J.P. Wigneron. W.T. Crow. J.T. Reager. A.W. Warrick (2020), Retrieving Global Surface Soil Moisture from GRACE Satellite Gravity DataJournal of Hydrology, https://doi.org/10.1016/j.jhydrol.2020.124717 [DATA https, ftp]

  29. Tamang S.K.*, A. Ebtehaj, D. Zou, G. Lerman (2020), Regularized Variational Data Assimilation for Bias Treatment using the Wasserstein MetricQuarterly Journal of the Royal Meteorological Society, https://doi.org/10.1002/qj.3794. arXiv:2003.02421

  30. Gao L.*, M. Sadeghi*, A. F. Feldman, A. Ebtehaj (2020), A Spatially Constrained Multi-Channel Algorithm for Inversion of a First-Order Microwave Emission Model at L-BandIEEE Trans. on Geosci. and Remote Sens., doi:10.1109/TGRS.2020.2987490.

  31. Gao L.*, M. Sadeghi*, A. Ebtehaj, J. P. Wigneron (2020), A Temporal Polarization Ratio Algorithm for Calibration-free Retrieval of Soil Moisture at L-bandRemote Sensing of Environment, https://doi.org/10.1016/j.rse.2020.112019.

  32. Tamang S. K.*, A. Ebtehaj, P. J. Van Leeuwen, D. Zou, G. Lerman (2021), Ensemble Riemannian Data Assimilation over the Wasserstein Space, Nonlin. Processes Geophys., 28, 295–309, 2021, https://doi.org/10.5194/npg-28-295-2021 [CODES].

  33. Vahedizadeh S.*, A. Ebtehaj, Y. You, S. E. Ringerud, and F. J. Turk (2021), Passive Microwave Signatures and Retrieval of High-latitude Snowfall over Open Oceans and Sea Ice: Insights from Coincidences of GPM and CloudSat SatellitesIEEE Trans. on Geosci. and Remote Sens., doi: 10.1109/TGRS.2021.3071709.

  34. Turk F.J., S. E. Ringerud, Y. You, A. Camplani, D. Casella, G. Panegrossi, P. Sanò, A. Ebtehaj, C. Guilloteau, N. Utsumi, C. Prigent, C. Peters-Lidard (2021), Adapting Passive Microwave-Based Precipitation Algorithms to Variable Microwave Land Surface Emissivity to Improve Precipitation Estimation from the GPM Constellation, J. of Hydrometeor, https://doi.org/10.1175/JHM-D-20-0296.1.

  35. Turk F.J., S. E Ringerud, A. Camplani, D. Casella, R. J. Chase, A. Ebtehaj, J. Gong, M. Kulie, G. Liu, L. Milani, G. Panegrossi, R. Padulles, J. Rysman, P. Sano, S.Vahedizade, N. Wood (2021), Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset, Remote Sensing, 13, 2264. https://doi.org/ 10.3390/rs13122264

  36. Sadeghi M.*, A. Ebtehaj, M. Guala., J.  Wang (2021), Physical Connection of Sensible and Ground Heat Flux, Journal of Hydrology, 602, 126687,  https://doi.org/10.1016/j.jhydrol.2021.126687.

  37. Gao L.*, A. Ebtehaj, M.J. Chaubell, M. Sadeghi*, X. Li, J. P.  Wigneron (2021), Reappraisal of SMAP Inversion Algorithms for Soil Moisture and Vegetation Optical DepthRemote Sensing of Environment, 264112627https://doi.org/10.1016/j.rse.2021.112627. 

  38. Ebtehaj A., M. Durand, M. Tedesco (2021), Constrained Inversion of a Microwave Snowpack Emission Model using Dictionary Matching: Applications for GPM Satellite, IEEE Trans. on Geosci. and Remote Sens., 10.1109/TGRS.2021.3115663. [MATLAB codes], 

  39. Tamang S. K.*, A. Ebtehaj, P. J. Van Leeuwen, G. Lerman, E Foufoula-Georgiou (2022), Ensemble Riemannian Data Assimilation: Towards High-dimensional ImplementationNonlin. Processes Geophys., 29, 77–92, 2022, https://doi.org/10.5194/npg-29-77-2022.

  40.  Lia X., J.P Wigneron, L. Fan, F. Frappart, S. H. Yueh, A. Colliander, A. Ebtehaj, L. Gao*, R. Fernandez-Morane, X. Liu, M. Wang, H. Ma, C. Moisy, P. Ciaish (2022), A new SMAP soil moisture and vegetation optical depth product (SMAP-IB): algorithm, assessment and inter-comparison, Vol 271, 112921, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2022.112921.

  41. Gao L.*, A. Ebtehaj, J. Cohen, J. P. Wigneron (2022), Variability and Changes of Unfrozen Soils below Snowpack, Geophys. Res. Lett. doi: 10.1029/2021GL095354. 

  42. Gao L.*, Q. Gao, H. Zhang, X. Lif, M. Julian Chaubellg, A. Ebtehaj, L. Shen, J.P. Wigneron (2022), A Deep Neural Network Based SMAP Soil Moisture ProductRemote Sensing of Environment, 277, 13059, https://doi.org/10.1016/j.rse.2022.113059

  43. Rahimi R.*, A. Ebtehaj, G. Panegrossi, L. Milani, S. E. Ringerud, F. J. Turk (2022), Vulnerability of Passive Microwave Snowfall Retrievals to Physical Properties of Snowpack: A Perspective from Dense Media Radiative Transfer Theory, IEEE Trans. on Geosci. and Remote Sens., doi: 10.1109/TGRS.2022.3184530.

  44. Vahedizade S.*, A. Ebtehaj, S. Tamang, Y. You, G. Panegrossi, S. Ringerud, F. J. Turk (2022), On the Effects of Cloud Water Content on Passive Microwave Snowfall RetrievalsRemote Sensing of Environment, https://doi.org/10.1016/j.rse.2022.113187

  45. Kumawat D*., M. Olyaei*, L. Gao, A. Ebtehaj (2022), Passive Microwave Retrieval of Soil Moisture below Snowpack at L-band using SMAP Observations, IEEE Trans. on Geosci. and Remote Sens., 10.1109/TGRS.2022.3216324 [Live codes on GitHub] [HTML]

  46. M. Olyaei*, A. Ebtehaj, and J. Hong (2022), Optical Detection of Marine Debris using Deep Knock-offIEEE Trans. on Geosci. and Remote Sens. DOI: 10.1109/TGRS.2022.3228638

  47. You Y., G. Huffman, V. Petkovic, L. Milani, J. X Yang, A. Ebtehaj, S. Vahedizade*, G. Gu (2023), Evaluation of Snowfall Retrieval Performance of GPM Constellation Radiometers Relative to Spaceborne Radars, J. of Hydrometeor., https://doi.org/10.1175/JHM-D-22-0052.1. 

  48. Kumawat D.*, A. Ebtehaj (2023), Passive Microwave Retrieval of Vegetation Optical Depth and Soil Permittivity Over Snow Covered Surfaces at L-Band, DOI: 10.1109/IGARSS52108.2023.10282460.

  49. M. Olyaei*, A. Ebtehaj (2023),  Uncovering Plastic Litter Spectral Signatures: A Comparative Study of Hyperspectral Band Selection Algorithms, Remote Sens. 2024, 16(1), 172; https://doi.org/10.3390/rs16010172.

  50. Kumawat D*, A. Ebtehaj, M. Schwank, J.P. Wigneron, X. Li (2024), Global Estimates of L-band Vegetation Optical Depth and Soil Permittivity over Snow-covered Boreal Forests and Permafrost using SMAP Satellite Data, Remote Sensing of Environment, Vol 306,114145, https://doi.org/10.1016/j.rse.2024.114145 [GitHub Codes and Data].

  51. Rahimi R*, P. Ravirathinam, A. Ebtehaj, A. Behrangi, J. Tan, and V. Kumar (2024), Global Precipitation Nowcasting of Integrated Multi-satellitE Retrievals for GPM: A U-Net Convolutional LSTM Architecture, J. of Hydrometeor., https://doi.org/10.1175/JHM-D-23-0119.1  [GitHub Codes].

  52. Yao X., X. Li, L. Fan, G.D. Lannoy, J. Peng, F. Frappart, A. Ebtehaj, P. Rosnay, Z. Xing, L. Yu, G. Dong, S. H. Yueh, A. Colliander, J.P. Wigneron, (2024), Optimal model-based temperature inputs for global soil moisture and vegetation optical depth retrievals from SMAP, Remote Sensing of Environment, Vol 311, 114240, https://doi.org/10.1016/j.rse.2024.114240. 

  53. Kumawat D.*, A. Ebtehaj, X. Xu, A. Colliander, V. Kumar (2024),  An Autoencoder Architecture for L-band Passive Microwave Retrieval of Landscape Freeze-Thaw Cycle, https://arxiv.org/abs/2407.04119 [GitHub] â€‹

  54. Kumawat D.*, A. Ebtehaj (2024), Deep Learning of the Soil Freeze-Thaw Cycle Using Satellite L-Band Radiometry, IGARSS, IEEE International Geoscience and Remote Sensing Symposium, DOI: 10.1109/IGARSS53475.2024.10641878.

  55. M. Olyaei*, A. Ebtehaj, and C. Ellis (2024), A Hyperspectral Reflectance Database of Plastic Debris with Different Fractional Abundance in River Systems, Nature, Scientific Data, accepted. 

  56. Kang  H.*, A. Ebtehaj (2024), Machine Learning for Explanation of Sub-grid Convective Precipitation: A Case Study over CONUS using a Convection-allowing Model, Artificial Intelligence for the Earth Systems, Under revision.

  57. Rahimi R.*, A. Ebtehaj, L. Milani (2024), Advancing Passive Microwave Retrievals of Precipitation using CloudSat and GPM Coincidences: Integration of Machine Learning with a Bayesian Algorithm, J. Hydrometeor., under revision.

Book Chapters:

  1. Sadeghi, M., E. Babaeian, A. Ebtehaj. S.B. Jones, M. Tuller (2018), Remote Sensing of Environmental Variables and Fluxes. In: “Handbook of Environmental Engineering”, edited by Myer Kutz. John Wiley & Sons, Inc., Hoboken, New Jersey. In press

colab.png
view_on_GitHub.png
view_on_GitHub.png
bottom of page