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Publications

Peer-reviewed 

  • Brocca, L., Barbetta, S., Camici, S., Ciabatta, L., Dari, J., Filippucci, P., Massari, C., Modanesi, S., Tarpanelli, A., Bonaccorsi, B., Mosaffa, H., Wagner, W., ... & Fernandez, D. (2024). A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations. Frontiers in Science, 1, 1190191.https://doi.org/10.3389/fsci.2023.1190191.

  • Mosaffa, H., Filippucci, P., Massari, C., Ciabatta, L., & Brocca, L. (2023). SM2RAIN-Climate, a monthly global long-term rainfall dataset for climatological studies. Scientific Data, 10(1), 749.https://doi.org/10.1038/s41597-023-02654-6.

  • Brocca, L., Gaona, J., Bavera, D., Fioravanti G., Puca G., Ciabatta L., Paolo Filippucci., Mosaffa H., Esposito G., Roberto P., Dari J., Vreugdenhil M., & Wagner, W. Exploring the actual spatial resolution of 1 km satellite soil moisture products. Journal of Hydrology. (Under review)

  • Kossieris, P., Tsoukalas I ., Brocca L., Mosaffa H., Makropoulos , C., & Anghelea., A. Merging multiple precipitation products via machine learning: revisiting conceptual and technical aspects. Journal of Hydrology. (Under review)

  • Saeedi, M., Kim, H., Nabaei, S., Brocca, L., Lakshmi, V., & Mosaffa, H. (2022). A comprehensive assessment of SM2RAIN-NWF using ASCAT and a combination of ASCAT and SMAP soil moisture products for rainfall estimation. Science of The Total Environment, 156416. https://doi.org/10.1016/j.scitotenv.2022.156416.

  • Mallakpour, I., Sadeghi, M., Mosaffa, H., Asanjan, A. A., Sadegh, M., Nguyen, P., Sorooshian, S. & AghaKouchak, A. (2022). Discrepancies in changes in precipitation characteristics over the contiguous United States based on six daily gridded precipitation datasets. Weather and Climate Extremes, 36, 100433. https://doi.org/10.1016/j.wace.2022.100433.

  • Sadeghi, M., Shearer, E. J., Mosaffa, H., Gorooh, V. A., Rahnamay Naeini, M., Hayatbini, N., Katiraie-Boroujerdy, P., Analui, B., & Sorooshian, S. (2021). Application of remote sensing precipitation data and the CONNECT algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019). Journal of Hydrology, 600, 126569. https://doi.org/10.1016/j.jhydrol.2021.126569.

  • Mosaffa, H., Sadeghi, M., Hayatbini, N., Afzali Gorooh, V., Akbari Asanjan, A., Nguyen, P., & Sorooshian, S. (2020). Spatiotemporal Variations of Precipitation over Iran Using the High-Resolution and Nearly Four Decades Satellite-Based PERSIANN-CDR Dataset. Remote Sensing, 12(10), 1584. https://doi.org/10.3390/rs12101584

  • Mosaffa, H., Shirvani, A., Khalili, D., Nguyen, P., & Sorooshian, S. (2020). Post and near real-time satellite precipitation products skill over Karkheh River Basin in Iran. International Journal of Remote Sensing, 41(17), 6484-6502https://doi.org/10.1080/01431161.2020.1739352

  • Mosaffa, H., & Sepaskhah, A. R. (2019). Performance of irrigation regimes and water salinity on winter wheat as influenced by planting methods. Agricultural Water Management, 216, 444-456. https://doi.org/10.1016/j.agwat.2018.10.027

Chapter Book

  • Mosaffa, H., Sadeghi, M., Mallakpour, I., Jahromi, M. N., & Pourghasemi, H. R. (2022). Application of machine learning algorithms in hydrology. In Computers in Earth and Environmental Sciences (pp. 585-591). Elsevier.

  • Jahromi, M. N., Miralles, D., Koppa, A., Rains, D., Zand-Parsa, S., Mosaffa, H., & Jamshidi, S. (2022). Ten Years of GLEAM: A Review of Scientific Advances and Applications. Computational Intelligence for Water and Environmental Sciences, 525-540.

Conference Papers

  • Mosaffa, H., & Brocca, L. (2023). Enhancing NMME Precipitation Forecast Accuracy Using SM2RAIN-Climate: A Case Study Over Europe. In Proceedings of the HEPEX Workshop 2023 – Forecasting across Spatial Scales and Time Horizons (pp. 1). Norrköping, Sweden: September 13-15, 2023.

  • Mosaffa, H., Filippucci, P., Ciabatta, L., Massari, C., & Brocca, L. (2023). Application of deep convolutional neural networks for precipitation estimation through both top-down and bottom-up approaches (No. EGU23-15575). Copernicus Meetings.

  • Tsoukalas, I., Kossieris, P., Brocca, L., Barbetta, S., Mosaffa, H., & Makropoulos, C. (2023). Can machine learning help us to create improved and trustworthy satellite-based precipitation products? (No. EGU23-13852). Copernicus Meetings.

  • Shearer, E. J., Sadeghi, M., Mosaffa, H., Afzali Gorooh, V., Rahnamay Naeini, M., Hayatbini, N., ... & Sorooshian, S. (2022, December). Spring-time Heavy Precipitation and Flooding in Iran linked to Atmospheric River Conditions: An 18-year Climatology and Case Study of 2019. In AGU Fall Meeting Abstracts (Vol. 2022, pp. A55M-1283).

  • Mosaffa, H., Filippucci, P., Massari, C., Ciabatta, L., & Brocca, L. (2022). Long-term climatological SM2RAIN datasets for rainfall spatiotemporal analysis (No. IAHS2022-526). Copernicus Meetings.

  • Mosaffa, H., Filippucci, P., Massari, C., Ciabatta, L., & Brocca, L. (2022). Long-term climatological SM2RAIN dataset for drought monitoring (No. EGU22-4547). Copernicus Meetings.

  • Brocca, L., Ciabatta, L., Massari, C., Camici, S., Barbetta, S., Tarpanelli, A., ... & Mosaffa, H. (2022). High resolution (1 km) soil moisture and precipitation for developing a Digital Twin Earth for hydrology (No. EGU22-1883). Copernicus Meetings.

  • Mosaffa, H., Shirvani, A., Khalili, D., Nguyen, P., & Sorooshian, S. (2018, December). Assessment of Satellite-Based Extreme Precipitation Estimates in a Semi-Arid Region (Karkheh River Basin in Iran). In AGU Fall Meeting Abstracts.

  • Gorooh, V. A., Nguyen, P., Shearer, E. J., Mosaffa, H., Ombadi, M., Hsu, K., & Sorooshian, S. (2021, January). A Comprehensive Analysis of the New Near Real-Time PERSIANN product (PDIR-Now) over the Russian River Basin in California. In 101st American Meteorological Society Annual Meeting. AMS.

  • Mallakpour, I., Sadeghi, M., Mosaffa, H., Sadegh, M., & Aghakouchak, A. (2019, Jun). Analysis of changes in precipitation characteristics over the contiguous USA in recent decades. In 12th International Precipitation Conference (IPC12) Abstracts

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