GPM Refereed Publications
Majumdar, S., R. Smith, B. D. Conway, and V. Lakshmi,
: Advancing remote sensing and machine learning-driven frameworks for groundwater withdrawal estimation in Arizona: Linking land subsidence to groundwater withdrawals. Hydrological Processes, 36(11), e14757, doi:10.1002/hyp.14757.
Maitra, A., G. Rakshit, and S. Jana,
: Three-Parameter Rain Drop Size Distributions From GPM Dual-Frequency Precipitation Radar Measurements: Techniques and Validation With Ground-Based Observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1-11, doi:10.1109/TGRS.2022.3227622.
Mahmud, H. B., and T. Osawa ,
: Enhanced precipitation prediction through the integration of gauge observations with satellite-based precipitation prediction models utilizing the Bayesian model averaging (BMA) technique in Kelantan, Malaysia. Proceedings Volume 13262, Remote Sensing of the Atmosphere, Clouds, and Precipitation VIII, , 3, doi:10.1117/12.3038111.
Mahdavi, T.,
: Comparison of Two Products of Satellite Precipitation (TRMM_3B42 v7-3-Hourly—Research Grade) and GPM-IMERG (V06-Half-Hourly—Early) in the East of Lake Urmia, Iran. Journal of the Indian Society of Remote Sensing, 51(1), 43–60, doi:10.1007/s12524-022-01620-w.
Mahakur, M., S. Shige, and M. Hirose,
: Chapter 1 - Multi-scale manifestation of tropical precipitation as evidenced from recent satellite observations. Multi-Scale Precipitation Variability Over the Tropics, , 1-33, doi:https://linkinghub.elsevier.com/retrieve/pii/B9780443140303000012.
Magi, B. I., T. Winesett, and D. J. Cecil,
: Estimating lightning from microwave remote sensing data. J. Appl. Meteor. Climatol., 55, 2021-2036, doi:10.1175/JAMC-D-15-0306.1.
Maghsood, F. F., Hashemi, H., Hosseini, S. H., and Berndtsson, R.,
: Ground Validation of GPM IMERG Precipitation Products over Iran. Rem. Sens., 12(1), 48, doi:10.3390/rs12010048.
Maggioni, V., M. R. P. Sapiano, R. F. Adler, Y. Tian, and G. J. Huffman,
: An Error Model for Uncertainty Quantification in High-Time-Resolution Precipitation Products. J. Hydrometeor., 15, 1274-1292, doi:10.1175/JHM-D-13-0112.1.
Maggioni, V., C. Massari, and C. Kidd,
: Chapter 13 - Errors and uncertainties associated with quasiglobal satellite precipitation products. Precipitation Science, , 377-390, doi:10.1016/B978-0-12-822973-6.00023-8.
Maggioni, V. and C. Massari,
: On the performance of satellite precipitation products in riverine flood modeling: A review. J. Hydrology, 558, 214–224, doi:10.1016/j.jhydrol.2018.01.039.
Machado, L. A., and Y. Hong,
: The Chuva Project: How Does Convection Vary across Brazil?. Bull. Amer. Meteor. Soc., 95, 1365-1380, doi:10.1175/BAMS-D-13-00084.1.
Ma, Z., Y. Lin, J. Fei, Y. Zheng, W. Chu, and H, Ye,
: Strengthening cold wakes lead to decreasing trend of tropical cyclone rainfall rates relative to background environmental rainfall rates. npj Climate and Atmospheric Science, 6(1), 131, doi:10.1038/s41612-023-00460-w.
Ma, Z., X. Tan, Y. Yang, X. Chen, G. Kan, X. Ji, H. Lu, J. Long, Y. Cui, and Y. Hong,
: The First Comparisons of IMERG and the Downscaled Results Based on IMERG in Hydrological Utility over the Ganjiang River Basin. Water, 10(10), 1392, doi:10.3390/w10101392.
Ma, Z., S. Zhang, Q. Liu, Y. Feng, Q. Guo, and H. Zhao,
: Using CYGNSS and L-Band Radiometer Observations to Retrieve Surface Water Fraction: A Case Study of the Catastrophic Flood of 2022 in Pakistan. IEEE Transactions on Geoscience and Remote Sensing, 62, 1-17, doi:10.1109/TGRS.2024.3367491.
Ma, Z., R. Yao, P. Sun, Z. Zhuang, C. Ge, Y. Zou, and Y. Lv,
: Quantitative Evaluation of Runoff Simulation and Its Driving Forces Based on Hydrological Model and Multisource Precipitation Fusion. Land, 12(3), 636, doi:10.3390/land12030636.
Ma, Z., Jintao Xu, Y. Ma, S. Zhu, K. He, S. Zhang, W. Ma, and X. Xu,
: AERA5-Asia: A Long-Term Asian Precipitation Dataset (0.1°, 1-hourly, 1951–2015, Asia) Anchoring the ERA5-Land under the Total Volume Control by APHRODITE. Bull. Amer. Meteor. Soc., 103(4), E1146–E1171, doi:10.1175/BAMS-D-20-0328.1.
Ma, Z., J. Xu, B. Dong, X. Hu, H. Hu, S. Yan, S. Zhu, K. He, Z. Shi, Y. Chen, X. Fang, Q. Zhang, S. Gu, and F. Weng,
: GMCP: A Fully Global Multisource Merging-and-Calibration Precipitation Dataset (1-Hourly, 0.1°, Global, 2000–the Present). Bull. Amer. Meteor. Soc., 106(4), E596–E624, doi:10.1175/BAMS-D-24-0051.1.
Ma, Y., V. Chandrasekar, and S. K. Biswas,
: A Bayesian Correction Approach for Improving Dual-frequency Precipitation Radar Rainfall Rate Estimates. J. Meteor. Soc. Japan, 98(3), 511-525, doi:10.2151/jmsj.2020-025.
Ma, Y., G. Tang, D. Long, B. Yong, L. Zhong, W. Wan, and Y. Hong,
: Similarity and Error Intercomparison of the GPM and Its Predecessor-TRMM Multisatellite Precipitation Analysis Using the Best Available Hourly Gauge Network over the Tibetan Plateau. Remote Sens., 8, 569, doi:10.3390/rs8070569.
Ma, X., L. Zhao, J. Sun, J. Chen, Y. Wang, J. Zhou, J. Liu, H. Lu, and K. Yang,
: Optimization of key land surface albedo parameter reduces wet bias of climate modeling for the Tibetan Plateau. Science China Earth Sciences, 68, 2653–2662, doi:10.1007/s11430-025-1635-0.