GPM Refereed Publications
Panda, S. K., A. K. Mandal, B. P. Shukla, N. Jaiswal, C. M. Kishtawal, and A. K. Varma,
: A study of rapid intensification of tropical cyclone Ockhi using C-band polarimetric radar. Meteorology and Atmospheric Physics, 134, Article No. 86, doi:10.1007/s00703-022-00921-6.
Panegrossi G., D. Casella, S. Dietrich, A.C. Marra, P. Sanò, A. Mugnai, L. Baldini, N. Roberto, E. Adirosi, R. Cremonini, R. Bechini, G. Vulpiani, M. Petracca, and F. Porcù,
: Use of the GPM constellation for monitoring heavy precipitation events over the Mediterranean region. IEEE J. of Sel. Topics in Appl. Earth Obs. and Rem. Sens., 9, 2733-2753, doi:10.1109/JSTARS.2016.2520660.
Panegrossi, G., J.-F. Rysman, D. Casella, A. C. Marra, P. ano, and M. S. Kulie,
: CloudSat-Based Assessment of GPM Microwave Imager Snowfall Observation Capabilities. Rem. Sens., 9, 1263, doi:10.3390/rs9121263.
Pang, Z., Y. Zhang, C. Shi, J. Gu, Q. Yang, Y. Pan, Z. Wang, and B. Xu,
: A Comprehensive Assessment of Multiple High-Resolution Precipitation Grid Products for Monitoring Heavy Rainfall during the “7.20” Extreme Rainstorm Event in China. Rem. Sens., 15(21), 5255, doi:10.3390/rs15215255.
Panici, D., G. L. Bennett, R. J. Boothroyd, C. Abancó, R. D. Williams, F. Tan, and M. Matera,
: Observations and computational multi-phase modelling in tropical river settings show complex channel changes downstream from rainfall-triggered landslides. Earth Surface Processes and Landforms, 49(8), 2498-2516, doi:10.1002/esp.5841.
Pantillon, F., S. Davolio, E. Avolio, C. Calvo-Sancho, D. S. Carrió, S. Dafis, E. S. Gentile, J. J. Gonzalez-Aleman, S. Gray, M. M. Miglietta, P. Patlakas, I. Pytharoulis, D. Ricard, A. Ricchi, C. Sanchez, and E. Flaounas,
: The crucial representation of deep convection for the cyclogenesis of Medicane Ianos. Weather and Climate Dynamics, 5(3), 1187–1205, doi:10.5194/wcd-5-1187-2024.
Papa, K.-M., and A. G. Koutroulis,
: Evaluation of precipitation datasets over Greece. Insights from comparing multiple gridded products with observations. Atmos. Res., 315, 107888, doi:10.1016/j.atmosres.2024.107888.
Papacharalampous, G., H. Tyralis, A. Doulamis, and N. Doulamis,
: Comparison of Tree-Based Ensemble Algorithms for Merging Satellite and Earth-Observed Precipitation Data at the Daily Time Scale. Hydrology, 10(2), 50, doi:10.3390/hydrology10020050.
Papacharalampous, G., H. Tyralis, N. Doulamis, and A. Doulamis,
: Combinations of distributional regression algorithms with application in uncertainty estimation of corrected satellite precipitation products. Machine Learning with Applications, 19, 100615, doi:10.1016/j.mlwa.2024.100615.
Papacharalampous, G., H. Tyralis, N. Doulamis, and A. Doulamis,
: Ensemble learning for uncertainty estimation with application to the correction of satellite precipitation products. Machine Learning Earth, 1(1), 015004, doi:10.1088/3049-4753/add93b.
Papacharalampous, G., H. Tyralis, N. Doulamis, and A. Doulamis,
: Uncertainty estimation of machine learning spatial precipitation predictions from satellite data. Machine Learning: Science and Technology, 5(3), 035044, doi:10.1088/2632-2153/ad63f3.
Papacharalampous, G., H. Tyralis, N. Doulamis, and A. Doulamis,
: Ensemble Learning for Blending Gridded Satellite and Gauge-Measured Precipitation Data. Rem. Sens., 15(20), 4912, doi:10.3390/rs15204912.
Papageorgiou, E., M. Foumelis, and A. Mouratidis,
: Earth Observation Data Synergy for the Enhanced Monitoring of Ephemeral Water Bodies to Anticipate Karst-Related Flooding. GeoHazards, 4(2), 197-216, doi:10.3390/geohazards4020012.
Papalexiou, S. M., A. AghaKouchak, and E. Foufoula-Georgiou,
: A Diagnostic Framework for Understanding Climatology of Tails of Hourly Precipitation Extremes in the United States. Water Resources Research, 54(9), 6725-6738, doi:10.1029/2018WR022732.
Papalexiou, S. M., A. AghaKouchak, K. E. Trenberth, and E. Foufoula-Georgiou,
: Global, Regional, and Megacity Trends in the Highest Temperature of the Year: Diagnostics and Evidence for Accelerating Trends. Earth's Future, 6(1), 71-79, doi:10.1002/2017EF000709.
Papalexiou, S. M., C. R. Rajulapati, K. M. Andreadis, E. Foufoula-Georgiou, M. P. Clark, and K. E. Trenberth,
: Probabilistic Evaluation of Drought in CMIP6 Simulations. Earth's Future, 9(10), e2021EF002150, doi:10.1029/2021EF002150.
Papalexiou, S. M., Y. Markonis, F. Lombardo, A. AghaKouchak, and E. Foufoula-Georgiou,
: Precise Temporal Disaggregation Preserving Marginals and Correlations (DiPMaC) for Stationary and Nonstationary Processes. Water Resources Research, 54(10), 7435-7458, doi:10.1029/2018WR022726.
Parajuli, S. P., G. L. Stenchikov, A. Ukhov, H. Morrison, I. Shevchenko, and S. Mostamandi,
: Simulation of a Dust-And-Rain Event Across the Red Sea Using WRF-Chem. JGR Atmospheres, 128(14), e2022JD038384, doi:10.1029/2022JD038384.
Parajuli, S. P., G. L. Stenchikov, A. Ukhov, S. Mostamandi, P. A. Kucera, D. Axisa, W. I. Gustafson Jr., and Y. Zhu,
: Effect of dust on rainfall over the Red Sea coast based on WRF-Chem model simulations. Atmos. Chem. Physics, 22(13), 8659–8682, doi:10.5194/acp-22-8659-2022.
Paramanik, M. M. R., K. M. G. Rabbani, A. Imran, M. J. Islam, and I. M. Syed,
: Prediction of lightning activity over Bangladesh using diagnostic and explicit lightning parameterizations of WRF model. Natural Hazards, 120, 4399–4422, doi:10.1007/s11069-023-06355-6.