GPM Refereed Publications
Sarkar, A., K. K. Amal, T. Sarkar, J. Panda, and D. Paul,
: Variability in air-pollutants, aerosols, and associated meteorology over peninsular India and neighboring ocean regions during COVID-19 lockdown to unlock phases. Atmospheric Pollution Research, 12(12), 101231, doi:10.1016/j.apr.2021.101231.
Sarkar, D., A. Kesarkar, J. Bhate, P. Goriparthi, and A. Chandrasekar,
: Synoptic forcing and thermo-dynamical processes during cloudburst event over Sauni Binsar, Uttarakhand, India. Atmos. Res., 310, 107626, doi:10.1016/j.atmosres.2024.107626.
Sarkar, S., and S. Narbar,
: Operational high-resolution Global Forecast System (GFS) T1534 model fidelity in capturing the monsoon onset over Kerala. Meteorology and Atmospheric Physics, 137(3), 29, doi:10.1007/s00703-025-01076-w.
Sarmiento, D. P., K. Slinski, A. McNally, J. P. Jacob, C. Funk, P. Peterson, and C. D. Peters-Lidard,
: Daily Precipitation Frequency Distributions Impacts on Land-Surface Simulations of CONUS. Frontiers in Water, 3, , doi:10.3389/frwa.2021.640736.
Sasanka, T., K. Priya, K. K. Osuri, and D. Niyogi,
: Thunderstorm detection from GPM IMERG rainfall: Climatology of dynamical and thermodynamical processes over India. Int'l J. of Climatology, 43(14), 6686-6705, doi:10.1002/joc.8228.
Sateesh, M., C. Khadke, V. S. Prasad, and S. Goyal,
: Validation of satellite estimated convective rainfall products : A case study for the summer cyclone season of 2020. MAUSAM, 72(1), 229-236, doi:10.54302/mausam.v72i1.137.
Satgé, F., A. Xavier, R. Pillco Zolá, Y. Hussain, F. Timouk, J. Garnier, and M.-P. Bonnet,
: Comparative Assessments of the Latest GPM Mission’s Spatially Enhanced Satellite Rainfall Products over the Main Bolivian Watersheds. Rem. Sens., 9(4), 369, doi:10.3390/rs9040369.
Satgé, F., Y. Hussain, M.-P. Bonnet, B. Hussain, H. Martinez-Carvajal, G. Akhter, and R. Uagoda,
: Benefits of the Successive GPM Based Satellite Precipitation Estimates IMERG–V03, –V04, –V05 and GSMaP–V06, –V07 Over Diverse Geomorphic and Meteorological Regions of Pakistan. Rem. Sens., 10(9), 1373, doi:10.3390/rs10091373.
Sattar, A., et. al.,
: The Sikkim flood of October 2023: Drivers, causes, and impacts of a multihazard cascade. Science, 387(6740), eads2659, doi:10.1126/science.ads2659.
Saunders, A., B. Tellman, E. Benami, K. Anchukaitis, S. Hossain, A. Bennett, A. K. M. Saiful Islam, and J. Giezendanner,
: Sensitivity to Data Choice for Index-Based Flood Insurance. Earth's Future, 13(9), e2025EF005966, doi:10.1029/2025EF005966.
Savarin, A., and S. S. Chen,
: Land-Locked Convection as a Barrier to MJO Propagation Across the Maritime Continent. JAMES, 15(6), e2022MS003503, doi:10.1029/2022MS003503.
Savarin, A., and S. S. Chen,
: Pathways to Better Prediction of the MJO: 2. Impacts of Atmosphere-Ocean Coupling on the Upper Ocean and MJO Propagation. JAMES, 14(6), e2021MS002929, doi:10.1029/2021MS002928.
Sawada, M., and K. Ueno,
: Heavy Winter Precipitation Events with Extratropical Cyclone Diagnosed by GPM Products and Trajectory Analysis. J. Meteor. Soc. Japan, 99(2), 473-496, doi:10.2151/jmsj.2021-024.
Sazonov, D. S.,
: Algorithm Adjustment for Recovering Precipitation Based on MTVZA-GYa No. 2-2 Measurements. Izvestiya, Atmospheric and Oceanic Physics, 60(12), 1471-1477, doi:10.1134/s0001433825700136.
Sazonov, D. S.,
: Studying the Possibility of Precipitation Intensity Recovery from MTVZA-GYa Measurements. Izvestiya, Atmospheric and Oceanic Physics, 59, 1337–1347, doi:10.1134/S0001433823120204.
Sazonov, D. S., and I. N. Sadovsky,
: Geographical Reference Adjustment of Frequency Channels 52–91 GHz of the MTVZA-GYa Satellite Microwave Radiometer. Izvestiya, Atmospheric and Oceanic Physics, 60(9), 1172–1182, doi:10.1134/s0001433824701135.
Sazonov, D. S., and I. N. Sadovsky,
: Geographical reference adjustment of MTVZA-GYa satellite microwave radiometer frequency channels 52–91 GHz. Исследования Земли из космоса, 2, 88-100, doi:10.31857/S0205961424020082.
Scarino, B., K. Itterly, K. Bedka, C. R. Homeyer, J. Allen, S. Bang, and D. Cecil,
: Deriving Severe Hail Likelihood from Satellite Observations and Model Reanalysis Parameters Using a Deep Neural Network. Artif. Intell. Earth Syst., 2(4), , doi:10.1175/AIES-D-22-0042.1.
Schiro, K. A., H. Su, F. Ahmed, N. Dai, C. E. Singer, P. Gentine, G. S. Elsaesser, J. H. Jiang, Y.-S. Choi, and J. D. Neelin,
: Model spread in tropical low cloud feedback tied to overturning circulation response to warming. Nature Communications, 13(1), 7119, doi:10.1038/s41467-022-34787-4.
Schmitt, A. U., F. Ament, A.o C. de Araújo, M. Sá, and P. Teixeira,
: Modeling atmosphere–land interactions at a rainforest site – a case study using Amazon Tall Tower Observatory (ATTO) measurements and reanalysis data. Atmospheric Chemistry and Physics, 23(16), 9323–9346, doi:10.5194/acp-23-9323-2023.