GPM Refereed Publications
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, 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.
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.
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.
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.
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.
Emberson, R., D. Kirschbaum, and T. Stanley,
: New global characterisation of landslide exposure. Nat. Hazards Earth Syst. Sci., 20, 3413–3424, doi:10.5194/nhess-20-3413-2020.
Emberson, R., D. Kirschbaum, and T. Stanley,
: Global connections between El Nino and landslide impacts. Nature Communications, 12, Article 2262, doi:10.1038/s41467-021-22398-4.
Emberson, R., D. Kirschbaum, and T. Stanley,
: Landslide Hazard and Exposure Modelling in Data-Poor Regions: The Example of the Rohingya Refugee Camps in Bangladesh. Earth's Future, 9, 2, doi:10.1029/2020EF001666.
En-nagre, K., M. Aqnouy, A. Bouadila, C. Et-Takaouym, M. Chahid, I. Bouizrou, I. Hilal, J. E. S. El Messari, and A. Tariq,
: Assessment of three satellite precipitation products for hydrological studies in a data-scarce context: Ouarzazate basin, southern Morocco. Natural Hazards Research, , S2666592125000216, doi:10.1016/j.nhres.2025.02.008.
Endsley, K. A., M. Zhao, J. S. Kimball, T. Albrethsen, and S. Devadiga,
: Improved Global Estimates of Terrestrial Evapotranspiration Using the MODIS and VIIRS Sensors. J. Hydrometeorology, 26(6), 817–833, doi:10.1175/JHM-D-24-0145.1.
Engsig, M., A. Tejedor, Y. Moreno, E. Foufoula-Georgiou and C. Kasmi,
: DomiRank Centrality reveals structural fragility of complex networks via node dominance. Nature Communications, 15(56), , doi:10.1038/s41467-023-44257-0.