GPM Refereed Publications
Ghomlaghi, A., M. Nasseri, and B. Bayat,
: Large-scale precipitation monitoring network re-design using ground and satellite datasets: coupled application of geostatistics and meta-heuristic optimization algorithms. Stochastic Environmental Research and Risk Assessment, 37, 4445–4458, doi:10.1007/s00477-023-02517-x.
Ghomlaghi, A., M. Nasseri, and B. Bayat,
: Comparing and contrasting the performance of high-resolution precipitation products via error decomposition and triple collocation: An application to different climate classes of the central Iran. J. Hydrology, 612(Part C), 128298, doi:10.1016/j.jhydrol.2022.128298.
Ghosh, A., A. K. Varma, S. Shah, B. S. Gohil, and P. K. Pal,
: Rain identification and measurement using Oceansat-II scatterometer observations. Remote Sensing of Environment, 142, 20-32, doi:10.1016/j.rse.2013.10.033.
Giangrande, S. E., S. Collis, A. K. Theisen, and A. Tokay,
: Precipitation Estimation from the ARM Distributed Radar Network during the MC3E Campaign. J. Appl. Meteor. Climatol., 53, 2130-2147, doi:10.1175/JAMC-D-13-0321.1.
Gilbert, E., D. Pishniak, J. A. Torres, A. Orr, M. Maclennan, N. Wever, and K. Verro,
: Extreme precipitation associated with atmospheric rivers over West Antarctic ice shelves: insights from kilometre-scale regional climate modelling. The Cryosphere, 19(2), 597–618, doi:10.5194/tc-19-597-2025.
Gilewski, P., and M. Nawalany,
: Inter-Comparison of Rain-Gauge, Radar, and Satellite (IMERG GPM) Precipitation Estimates Performance for Rainfall-Runoff Modeling in a Mountainous Catchment in Poland. Water, 10, 1665, doi:10.3390/w10111665.
Gilmour, H., R. Chadwick, J. L. Catto, K. Halladay, N. C. G. Hart, and A.a Rehbein,
: Mesoscale Convective Systems over South America: Representation in Kilometer-Scale Met Office Unified Model Climate Simulations. J. Climate, 39(1), 225–247, doi:10.1175/JCLI-D-24-0754.1.
Girishkumar, M. S., V. R. Sherin, and E. P. R. Rao,
: The causes of the difference in marine heat wave conditions during the summers of 2019 and 2020 in the Northern Bay of Bengal. Climate Dynamics, 63, 315, doi:10.1007/s00382-025-07824-3.
Gisinger, S., M. Bramberger, A. Dörnbrack, and P. Bechtold,
: Severe Convectively Induced Turbulence Hitting a Passenger Aircraft and Its Forecast by the ECMWF IFS Model. Geophys. Res. Letts., 51(23), e2024GL113037, doi:10.1029/2024GL113037.
Glazer, R. H., E. Coppola, and F. Giorgi,
: Understanding Nocturnally Driven Extreme Precipitation Events over Lake Victoria in a Convection-Permitting Model. Mon. Wea. Rev., 153(6), 1085–1103, doi:10.1175/MWR-D-22-0339.1.
Godlee, J. L., C. M. Ryan, A. Siampale, and K. G. Dexter,
: Tree species diversity drives the land surface phenology of seasonally dry tropical woodlands. Journal of Ecology, 112(9), 1978-1991, doi:10.1111/1365-2745.14366.
Godoy, M. R. V., Y. Markonis, J. R. Thomson, A. S. Ballarin, S. Perri, A. Molini, C. Miao, Q. Sun, M. Hanel, S. M. Papalexiou, C. Kummerow, and T. Oki,
: Which Precipitation Dataset to Choose for Hydrological Studies of the Terrestrial Water Cycle?. Bull. Amer. Meteor. Soc., 106(9), E2000–E2016, doi:10.1175/BAMS-D-24-0306.1.
Goffin, B. D., and V. Lakshmi,
: Global Evaluation of the Wettest Days Contributing to 50% of Annual Precipitation (WD50). Geophys. Res. Letts., 52(12), e2025GL114859, doi:10.1029/2025GL114859.
Gohil, B. S., R. M. Gairola, A. K. Mathur, A. K. Varma, C. Mahesh, R. K. Gangwar and P. K. Pal,
: Algorithms for retrieving geophysical parameters from the MADRAS and SAPHIR sensors of the Megha-Tropiques satellite: Indian scenario. Quarterly Journal of Royal Meteorological Society, 139(673), 954-963, doi:10.1002/qj.2041.
Golam Rabbani, K. Md., Md J. Islam, A. O. Fierro, E. R. Mansell, and P. Paul,
: Lightning forecasting in Bangladesh based on the lightning potential index and the electric potential. Atmos. Res., 267, 105973, doi:10.1016/j.atmosres.2021.105973.
Goldenstern, E., and C. D. Kummerow,
: Predicting Region-Dependent Biases in a GOES-16 Machine Learning Precipitation Retrieval. J. Appl. Meteor. Climatol., 62(7), 873–885, doi:10.1175/JAMC-D-22-0089.1.
Golian, S., M. Javadian, and A. Behrangi,
: On the use of satellite, gauge, and reanalysis precipitation products for drought studies. Environ. Res. Lett., 14, 075005, doi:10.1088/1748-9326/ab2203.
Golian, S., S. Moazami, P. E. Kirstetter, Y. Hong,
: Merging Multiple Satellite Rainfall Estimate Algorithms over a Complex Terrain. Water Resources Management, 29, 4885-4901, doi:10.1007/s11269-015-1096-6.
Gomez, F. J., K. Jafarzadegan, H. Moftakhari, and H. Moradkhani,
: Probabilistic flood inundation mapping through copula Bayesian multi-modeling of precipitation products. Natural Hazards and Earth System Sciences, 24(8), 2647–2665, doi:10.5194/nhess-24-2647-2024.
Gomez-Morales, D. A., and O. Acevedo-Charry,
: Satellite remote sensing of environmental variables can predict acoustic activity of an orthopteran assemblage. PeerJ, 10, e13969, doi:10.7717/peerj.13969.