GPM Refereed Publications
Baki, H., C. Balaji, and B. Srinivasan,
: Impact of data assimilation on a calibrated WRF model for the prediction of tropical cyclones over the Bay of Bengal. Current Science, 122(5), 569, doi:10.18520/cs/v122/i5/569-583.
Baki, H., S. Chinta, C. Balaji, and B. Srinivasan,
: Parameter Calibration to Improve the Prediction of Tropical Cyclones over the Bay of Bengal Using Machine Learning–Based Multiobjective Optimization. J. Appl. Meteor. Climatol., 61(7), 819–837, doi:10.1175/JAMC-D-21-0184.1.
Baki, H., S. Chinta, C. Balaji, and B. Srinivasan,
: Determining the sensitive parameters of the Weather Research and Forecasting (WRF) model for the simulation of tropical cyclones in the Bay of Bengal using global sensitivity analysis and machine learning. Geoscientific Model Development, 15(5), 2133–2155, doi:10.5194/gmd-15-2133-2022.
Baladima, F., J. L. Thomas, D. Voisin, M. Dumont, C. Junquas, R. Kumar, C. Lavaysse, L. Marelle, M. Parrington, and J. Flemming,
: Modeling an Extreme Dust Deposition Event to the French Alpine Seasonal Snowpack in April 2018: Meteorological Context and Predictions of Dust Deposition. JGR Atmospheres, 127(8), e2021JD035745, doi:10.1029/2021JD035745.
Balogun, R. A., I. A. Balogun, V. O. Ajayi, R. Alexander, B. Pickering, and Z. Ahmed,
: Evolution, destination and characteristics of three westward propagating storms with associated impacts over Nigeria during August 2017 Atlantic hurricane season. Natural Hazards, 117, 2647–2674, doi:10.1007/s11069-023-05960-9.
Balsamo, G., A. Agusti-Panareda, C. Albergel, G. Arduini, A. Beljaars, J. Bidlot, N. Bousserez, S. Boussetta, A. Brown, R. Buizza, C. Buontempo, F. Chevallier, M. Choulga, H. Cloke, M.F. Cronin, M. Dahoui, P. de Rosnay, P.A. Dirmeyer, M. Drusch, E. Dutra, M.B. Ek, P. Gentine, H. Hewitt, S.P. Keeley, Y. Kerr, S. Kumar, C. Lupu, J.-F. Mahfouf, J. McNorton, S. Mecklenburg, K. Mogensen, J. Muñoz-Sabater, R. Orth, F. Rabier, R. Reichle, B. Ruston, F. Pappenberger, I. Sandu, S.I. Seneviratne, S. Tietsche, I.F. Trigo, R. Uijlenhoet, N. Wedi, R.I. Woolway, ,
: Satellite and in situ observations for advancing global earth surface modelling: A review. Rem. Sens., 10, 2038, doi:10.3390/rs10122038.
Bang, S. , S. Stough, T. Lang, and P. Gatling,
: The Multiplatform Precipitation Feature (MPF) Database: A Storm-Centric Synthesis of Space- and Ground-Based Precipitation and Lightning Data Sets for Convective Studies. Earth and Space Science, 10(11), e2023EA003137, doi:10.1029/2023EA003137.
Bang, S. D. and E. J. Zipser,
: Tropical Oceanic Thunderstorms Near Kwajalein and the Roles of Evolution, Organization, and Forcing in Their Electrification. JGR Atmospheres, 124(2), 544-562, doi:10.1029/2018JD029320.
Bang, S. D., and D. J Cecil,
: Testing Passive Microwave-Based Hail Retrievals Using GPM DPR Ku-Band Radar. J. of Appl. Meteor. and Climatol., 60(3), 255–271, doi:10.1175/JAMC-D-20-0129.1.
Bang, S. D., and D. J. Cecil,
: Constructing a Multi-Frequency Passive Microwave Hail Retrieval and Climatology in the GPM Domain. J. Appl. Meteor. Climatol., 52, , doi:10.1175/JAMC-D-19-0042.1.
Bang, S. D., B. R. Scarino, K. F. Itterly, K. M. Bedka, and D. J. Cecil,
: Challenges in Satellite Remote Sensing of Hail: Evaluating IR and Passive-Microwave Satellite Hail Retrievals Using Aqua Observations and a Deep Neural Network. J. Appl. Meteor. Cliamtol., 64(12), 2037–2058, doi:10.1175/JAMC-D-25-0053.1.
Bao, J., B. Stevens, L. Kluft, and C. Muller,
: Intensification of daily tropical precipitation extremes from more organized convection. Science Advances, 10(8), eadj6801, doi:10.1126/sciadv.adj6801.
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.
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.
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.
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.
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.
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.
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,
: Automatic Detection and Classification of Orographic Precipitation using Machine Learning. ESSOAr, , , doi:10.1002/essoar.10502701.1.