GPM Refereed Publications
Ebtehaj, A. M., R. L. Bras, E. Foufoula-Georgiou,
: Shrunken locally linear embedding for passive microwave retrieval of precipitation. IEEE Trans. on Geosci. and Remote Sens., 53(7), 3720 - 3736, doi:10.1109/TGRS.2014.2382436.
Ebtehaj, A., C. Kummerow, and J. Turk,
: Metric Learning for Approximation of Microwave Channel Error Covariance: Application for Satellite Retrieval of Drizzle and Light Snowfall. IEEE Transactions on Geoscience and Remote Sensing, 58(2), 903-912, doi:10.1109/TGRS.2019.2941682.
Ebtehaj, A., M. Durand, and M. Tedesco,
: Constrained Inversion of a Microwave Snowpack Emission Model Using Dictionary Matching: Applications for GPM Satellite. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-14, doi:10.1109/TGRS.2021.3115663.
Ebtehaj, M. and C. D. Kummerow,
: Microwave retrievals of terrestrial precipitation over snow-covered surfaces: A lesson from the GPM satellite. Res. Lett., 44, 6154–6162, doi:10.1002/2017GL073451.
Eckert, E., D. Hudak, É. Mekis, P. Rodriguez, B. Zhao, Z. Mariani, S. Melo, K. Strong, and K. A. Walker,
: Validation of the Final Monthly Integrated Multisatellite Retrievals for GPM (IMERG) Version 05 and Version 06 with Ground-Based Precipitation Gauge Measurements across the Canadian Arctic. J. Hydrometeorology, 23(5), 715–731, doi:10.1175/JHM-D-21-0040.1.
Edrich, A.-K., A. Yildiz, R. Roscher, A. Bast, F. Graf, and J. Kowalski,
: A modular framework for FAIR shallow landslide susceptibility mapping based on machine learning. Natural Hazards, 120(9), 8953–8982, doi:10.1007/s11069-024-06563-8.
Eghdami, M., and A. P. Barros,
: Vertical Dependence of Horizontal Scaling Behavior of Orographic Wind and Moisture Fields in Atmospheric Models. Earth and Space Science, 6(10), 1957-1975, doi:10.1029/2018EA000513.
Eghdami, M., and A. P. Barros,
: Extreme Orographic Rainfall in the Eastern Andes Tied to Cold Air Intrusions. Front. Environ. Sci., 7, 101, doi:10.3389/fenvs.2019.00101.
Ehsani, M. R., A. Behrangi, A. Adhikari, Y. Song, G. J. Huffman, and D. T. Bolvin,
: Assessment of the Advanced Very High Resolution Radiometer (AVHRR) for Snowfall Retrieval in High Latitudes Using CloudSat and Machine Learning. J. Hydrometeor., 22(6), 1591–1608, doi:10.1175/JHM-D-20-0240.1.
Ehsani, M. R., A. Zarei, H. V. Gupta, K. Barnard, E. Lyons, and A. Behrangi,
: NowCasting-Nets: Representation Learning to Mitigate Latency Gap of Satellite Precipitation Products Using Convolutional and Recurrent Neural Networks. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-21, doi:10.1109/TGRS.2022.3158888.
Ehsani, M. R., and A. Behrangi,
: A comparison of correction factors for the systematic gauge-measurement errors to improve the global land precipitation estimate. J. Hydrology, 610, 127884, doi:10.1016/j.jhydrol.2022.127884.
Ehsani, M. R., and Coauthors,
: 2019-2020 Australia Fire and Its Relationship to Hydroclimatological and Vegetation Variabilities. Water, 12, 3067, doi:10.3390/w12113067.
Ehsani, M. R., S. Heflin, C. B. Risanto, and A. Behrangi,
: How well do satellite and reanalysis precipitation products capture North American monsoon season in Arizona and New Mexico?. Weather and Climate Extremes (Science Direct), 38, 100521, doi:10.1016/j.wace.2022.100521.
Eidhammer, T., A. Gettelman, K. Thayer-Calder, D. Watson-Parris, G. Elsaesser, H. Morrison, M. van Lier-Walqui, C. Song, and D. McCoy,
: An extensible perturbed parameter ensemble for the Community Atmosphere Model version 6. Geoscientific Model Development, 17(21), 7835–7853, doi:10.5194/gmd-17-7835-2024.
Ejaz, N., and J. Bahrawi,
: Assessment of Drought Severity and Their Spatio-Temporal Variations in the Hyper Arid Regions of Kingdom of Saudi Arabia: A Case Study from Al-Lith and Khafji Watersheds. Atmosphere, 13(8), 1264, doi:10.3390/atmos13081264.
El-Bouhali, A., K. E. O. Ech-Chahdi, M. Y. Ztait, M. Amyay, and M. El Mazi ,
: Performance Evaluation of IMERG Satellite-Based Precipitation Estimates Against Rain Gauge Records in the Sebou Watershed, Morocco. Rem. Sens. in Earth Sys. Sci., 9(13), 13, doi:10.1007/s41976-025-00262-z.
ElSadaani, M., W. F. Krajewski, and D. L. Zimmerman,
: River network based characterization of errors in remotely sensed rainfall products in hydrological applications. Rem. Sens. Letts., 9(8), 743-752, doi:10.1080/2150704X.2018.1475768.
Elsaesser, G. S., C. W. O'Dell, M. D. Lebsock, R. Bennartz, T. J. Greenwald, and F. J. Wentz,
: The Multisensor Advanced Climatology of Liquid Water Path (MAC-LWP). J. Climate, 30(24), 10193–10210, doi:10.1175/JCLI-D-16-0902.1.
Elsaesser, G. S., R. Roca, T. Fiolleau, A. D. Del Genio, and J. Wu,
: A Simple Model for Tropical Convective Cloud Shield Area Growth and Decay Rates Informed by Geostationary IR, GPM, and Aqua/AIRS Satellite Data. JGR Atmospheres, 127(10), e2021JD035599, doi:10.1029/2021JD035599.
Elsaesser, Gregory S., M. Van Lier‐Walqui, Q. Yang, M. Kelley, A. S. Ackerman, A. M. Fridlind, G. V. Cesana, G. A. Schmidt, J. Wu, A. Behrangi, S. J. Camargo, B. De, K. Inoue, N. M. Leitmann‐Niimi, Nicolas M., and J. D. O. Strong,
: Using Machine Learning to Generate a GISS ModelE Calibrated Physics Ensemble (CPE). Journal of Advances in Modeling Earth Systems, 17(4), e2024MS004713, doi:10.1029/2024MS004713.