GPM Refereed Publications
Manzione, R. L.,
: Detection of spatial and temporal precipitation patterns using remotely sensed data in the Paranapanema River Basin, Brazil from 2000 to 2021. Discover Water, 3(11), , doi:10.1007/s43832-023-00035-z.
Mantoani, M. C., A. P.M. Emygdio, C. Degobbi, C. R. Sapucci, L. C.C. Guerra, M. A.F.S. Dias, P. L.S. Dias, R. H.S. Zanetti, F. Rodrigues, G. G. Araujo, D. M.C. Silva, V. B. Duo Filho, S. M. Boschilia, J. A. Martins, F. Carotenuto, T. Šantl-Temkiv, C. E. Morris, and F. L.T. Gonçalves,
: Rainfall effects on vertical profiles of airborne fungi over a mixed land-use context at the Brazilian Atlantic Forest biodiversity hotspot. Agricultural and Forest Meteorology, 331, 109352, doi:10.1016/j.agrformet.2023.109352.
Manoj J, A., R. K. Guntu, and A. Agarwal,
: Spatiotemporal dependence of soil moisture and precipitation over India. J. Hydrology, 610, 127898, doi:10.1016/j.jhydrol.2022.127898.
Mania, R., S. Cesca, T. R. Walter, I. Koulakov, and S. L. Senyukov,
: Inflating Shallow Plumbing System of Bezymianny Volcano, Kamchatka, Studied by InSAR and Seismicity Data Prior to the 20 December 2017 Eruption. Frontiers in Earth Science, 9, 765668, doi:10.3389/feart.2021.765668.
Mangla, R., J. Indu, P. Chambon, and J.-F. Mahfouf,
: First steps towards an all-sky assimilation framework for tropical cyclone event over Bay of Bengal region: Evaluation and assessment of GMI radiances. Atmos. Res., 257, 105564, doi:10.1016/j.atmosres.2021.105564.
Mangla, R., J. Indu, and V. Lakshmi,
: Evaluation of convective storms using spaceborne radars over the Indo-Gangetic Plains and western coast of India. Meteorological Applications, 27(3), e1917, doi:10.1002/met.1917.
Mandement, M., P. E. Kirstetter, H. Reeves,
: Intercomparison between Ground-Based and Spaceborne Radars’ Echo-Top Heights: Application to the Multi-Radar Multi-Sensor and the Global Precipitation Measurement. J. Appl. Meteor. Climatol., 62(8), 917–928, doi:10.1175/JAMC-D-22-0146.1.
Mandapaka, P. V., and E. Y. M. Lo,
: Evaluation of GPM IMERG Rainfall Estimates in Singapore and Assessing Spatial Sampling Errors in Ground Reference. J. Hydrometeorology, 21(12), 2963–2977, doi:10.1175/JHM-D-20-0135.1.
Mandal, N., P. Das, and K. Chanda,
: Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data. Earth System Science Data, 17(6), 2575–2604, doi:10.5194/essd-17-2575-2025.
Manaster, A., C. W. O’Dell, and G. Elsaesser,
: Evaluation of Cloud Liquid Water Path Trends Using a Multidecadal Record of Passive Microwave Observations. J. Climate, 30(15), 5871–5884, doi:10.1175/JCLI-D-16-0399.1.
Mamgain, A., E. N. Rajagopal, A. K. Mitra, and S. Webster,
: Short-Range Prediction of Monsoon Precipitation by NCMRWF Regional Unified Model with Explicit Convection. Pure and Applied Geophysics, 175, 1197–1218, doi:10.1007/s00024-017-1754-0.
Mamalakis, A., J.-Y. Yu, J.T. Randerson, A. AghaKouchak, and E. Foufoula-Georgiou,
: A new interhemispheric teleconnection increases predictability of winter precipitation in southwestern US. Nature Communications, 9(1), 2332, doi:10.1038/s41467-018-04722-7.
Mamalakis, A., J.-Y. Yu, J. T. Randerson, A. AghaKouchak, and E. Foufoula-Georgiou,
: Reply to: A critical examination of a newly proposed interhemispheric teleconnection to Southwestern US winter precipitation. Nature Communications, 10, 2918 (2019), doi:10.1038/s41467-019-10531-3.
Mamalakis, A., J. T. Randerson, J.-Y. Yu, M. S. Pritchard, G. Magnusdottir, P. Smyth, P. A. Levine, S. Yu, and E. Foufoula-Georgiou,
: Zonally contrasting shifts of the tropical rain belt in response to climate change. Nature Climate Change, 11, 143–151, doi:10.1038/s41558-020-00963-x.
Mamalakis, A., A. AghaKouchak, J. T. Randerson, and E. Foufoula-Georgiou,
: Hotspots of Predictability: Identifying Regions of High Precipitation Predictability at Seasonal Timescales From Limited Time Series Observations. Water Resources Research, 58(5), e2021WR031302, doi:10.1029/2021WR031302.
Mamalakis, A. and E. Foufoula-Georgiou ,
: A multivariate probabilistic framework for tracking the intertropical convergence zone: Analysis of recent climatology and past changes. Geophys. Res. Letts., 45(23), 13,080-13,089, doi:10.1029/2018GL079865.
Malik, I., D. S. Chuphal, U. Vegad, and V. Mishra,
: Was the extreme rainfall that caused the August 2022 flood in Pakistan predictable?. Environmental Research: Climate, 2(4), 041005, doi:10.1088/2752-5295/acfa1a.
Malik, H., S. Abbas, F. Naeem, N. Habib, and N. Akhtar,
: Assessment of Long-Term Relationship of Tropospheric NO2 with Meteorological Parameters for Sustainability in Pakistan. International Journal of Innovations in Science & Technology, 6(6), 240-256, doi:https://journal.50sea.com/index.php/IJIST/article/view/841.
Malamos, N., T. Iliopoulou, P. Dimitriadis, and D. Koutsoyiannis,
: Comparative Analysis of IMERG Satellite Rainfall and Elevation as Covariates for Regionalizing Average and Extreme Rainfall Patterns in Greece by Means of Bilinear Surface Smoothing. Geosciences, 15(6), 212, doi:10.3390/geosciences15060212.
Majurec, N., J. T. Johnson, S. Tanelli, and S. L. Durden,
: Ku and Ka-band near nadiral normalized radar cross section of the sea surface: Comparison of measurements and models. IEEE Trans. Geosci. Remote Sens., 52, 5320-5332, doi:.