GPM Refereed Publications
Battaglia, A., P. Kollias, R. Dhillon, K. Lamer, M. Khairoutdinov, and D. Watters,
: Mind the gap – Part 2: Improving quantitative estimates of cloud and rain water path in oceanic warm rain using spaceborne radars. Atmos. Meas. Tech., 13, 4865–4883, doi:10.5194/amt-13-4865-2020.
Battaglia, A., M. O. Ajewole, and C. Simmer,
: Evaluation of Radar Multiple-Scattering Effects from a GPM Perspective. Part II: Model Results. J. Appl. Meteor. Climatol., 45, 1648-1664, doi:10.1175/JAM2425.1.
Battaglia, A., M. O. Ajewole, and C. Simmer,
: Evaluation of Radar Multiple-Scattering Effects from a GPM Perspective. Part I: Model Description and Validation. J. Appl. Meteor. Climatol., 45, 1634-1647, doi:10.1175/JAM2424.1.
Battaglia, A., K. Mroz, T. Lang, F. Tridon, S. Tanelli, L. Tian and G. Heymsfield,
: Using a multi-wavelength suite of microwave instruments to investigate the microphysical structure of deep convective cores. J. Geophys. Res. Atmos., 121(16), 9356-9381, doi:10.1002/2016JD025269.
Battaglia, A., K. Mroz, S. Tanelli, F. Tridon, and P. E. Kirstetter,
: Multiple-Scattering-Induced "Ghost Echoes" in GPM DPR Observations of a Tornadic Supercell. J. Appl. Meteor. Climatol., 55, , doi:1653-1666.
Battaglia, A., K. Mroz, D. Watters, and F. Ardhuin,
: GPM-Derived Climatology of Attenuation Due to Clouds and Precipitation at Ka-Band. IEEE Transactions on Geoscience and Remote Sensing, , 1–9, doi:10.1109/TGRS.2019.2949052.
Battaglia, A., K. Mroz, and D. Cecil,
: Chapter 9 - Satellite hail detection Author links open overlay panel. Precipitation Science Measurement, Remote Sensing, Microphysics and Modeling, , 257-286, doi:10.1016/B978-0-12-822973-6.00006-8 Get rights and content.
Battaglia, A., F. E. Scarsi, K. Mroz, and A. Illingworth,
: In-orbit cross-calibration of millimeter conically scanning spaceborne radars. Atmos. Meas. Tech., 16(12), 3283–3297, doi:10.5194/amt-16-3283-2023.
Bartuska, E., R. E. Beighley, K. J. Pieper, and C. N. Jones,
: Quantifying Improvements in Derived Storm Events from Version 07 of GPM IMERG Early, Late, and Final Data Products over North Carolina. Rem. Sens., 17(15), 2567, doi:10.3390/rs17152567.
Bartuska, E., and R. E. Beighley,
: Assessing precipitation event characteristics throughout North Carolina derived from GPM IMERG data products. Front. Water., 6, 1296586, doi:10.3389/frwa.2024.1296586 .
Barton, E. J., C. M. Taylor, A. K. Mitra, and A. Jayakumar,
: Systematic daytime increases in atmospheric biases linked to dry soils in irrigated areas in Indian operational forecasts. Atmospheric Science Letters, 24(9), e1172, doi:10.1002/asl.1172.
Barros, A. P., O. Prat, and F. Testik,
: Size distribution of raindrops. Nature Physics, 6, 232, doi:10.1038/nphys1646.
Barros, A. P. and M. Arulraj,
: Automatic Detection and Classification of Orographic Precipitation using Machine Learning. ESSOAr, , , doi:10.1002/essoar.10502701.1.
Barros, A. P.,
: Reply to comment by Qingyun Han on “Metrics to describe the dynamical evolution of atmospheric moisture: Intercomparison of model (NARR) and observations (ISCCP)” by Tao and Barros (2008). J. Geophys. Res., 115, D14125, doi:10.1029/2009JD013562.
Barros A.P. and M. Arulraj,
: Remote Sensing of Orographic Precipitation. In: Levizzani V., Kidd C., Kirschbaum D., Kummerow C., Nakamura K., Turk F. (eds) Satellite Precipitation Measurement. Advances in Global Change Research, 69, , doi:10.1007/978-3-030-35798-6_6.
Barreyat, M., P. Chambon, J.-F. Mahfouf, G. Faure, and Y. Ikuta,
: A 1D Bayesian Inversion Applied to GPM Microwave Imager Observations: Sensitivity Studies. J. Meteor. Soc. Japan, 99(4), 1045-1070, doi:10.2151/jmsj.2021-050.
Barraza, R. L., M. T. A. Herrera, A. E. M. Celestino, A. D. B. Jáquez, and D. A. M. Cruz,
: Evaluation of the Extreme Precipitation and Runoff Flow Characteristics in a Semiarid Sub-Basin Based on Three Satellite Precipitation Products. Hydrology, 12(4), 89, doi:10.3390/hydrology12040089.
Barma, S. D., S. B. Uttarwar, P. Barane, N. Bhat, and A. Mahesha,
: Evaluation of ERA5 and IMERG precipitation data for risk assessment of water cycle variables of a large river basin in South Asia using satellite data and archimedean copulas. Water Conservation and Management, 6, 61-69, doi:10.26480/wcm.01.2022.61.69.
Barber, K. A., C. D. Burleyson, Z. Feng, and S. M. Hagos,
: The Influence of Shallow Cloud Populations on Transitions to Deep Convection in the Amazon. J. Atmos. Sci., 79(3), 723–743, doi:10.1175/JAS-D-21-0141.1.
Bao, J., S. Bony, D. Takasuka, and C. Muller,
: Tropics-wide intraseasonal oscillations. Proceedings of the National Academy of Sciences, 122(48), e2511549122, doi:10.1073/pnas.2511549122.