GPM Refereed Publications
Turk, F. J., R. Padullés, E. Cardellach, C. O. Ao, K.-N. Wang, D. D. Morabito, M. de la Torre Juarez, M. Oyola, S. Hristova-Veleva, and J. D. Neelin,
: Interpretation of the Precipitation Structure Contained in Polarimetric Radio Occultation Profiles Using Passive Microwave Satellite Observations. J. Atmos. Oceanic Technol., 38(10), 1727–1745, doi:10.1175/JTECH-D-21-0044.1.
Turk, F. J., R. Sikhakolli, P. Kirstetter, and S. L. Durden,
: Exploiting Over-Land OceanSat-2 Scatterometer Observations to Capture Short-Period Time-Integrated Precipitation. J. Hydrometeor., 16, 2519-2535, doi:10.1175/JHM-D-15-0046.1.
Turk, F. J., S. E. Ringerud, A. Camplani, D. Casella, R. J. Chase, A. Ebtehaj, J. Gong, M. Kulie, G. Liu, L. Milani, G. Panegrossi, R. Padullés, J.-F. Rysman, P. Sanò, S. Vahedizade, and N. Wood,
: Applications of a CloudSat-TRMM and CloudSat-GPM Satellite Coincidence Dataset. Remote Sens., 13(12), 2264, doi:10.3390/rs13122264.
Turk, F. J., S. E. Ringerud, Y. You, A. Camplani, D. Casella, G. Panegrossi, P. Sano, A. Ebtehaj, C. Guilloteau, N. Utsumi, C. Prigent, and C. Peters-Lidard,
: Adapting Passive Microwave-Based Precipitation Algorithms to Variable Microwave Land Surface Emissivity to Improve Precipitation Estimation from the GPM Constellation. J. Hydrometeor., 22(7), 1755-1781, doi:10.1175/JHM-D-20-0296.1.
Turk, F. J., S. Hristova-Veleva, S. L. Durden, S. Tanelli, O. Sy, G. D. Emmitt, S. Greco, and S. Q. Zhang,
: Joint analysis of convective structure from the APR-2 precipitation radar and the DAWN Doppler wind lidar during the 2017 Convective Processes Experiment (CPEX). Atmos. Meas. Tech., 13(8), 4521–4537, doi:10.5194/amt-13-4521-2020.
Turk, F. J., Z. S. Haddad and Y. You,
: Estimating Nonraining Surface Parameters to Assist GPM Constellation Radiometer Precipitation Algorithms. J. Atmos. Oceanic Technol., 33, 1333–1353, doi:10.1175/JTECH-D-15-0229.1.
Turk, F. J., Z. S. Haddad, and Y. You,
: Principal Components of Multifrequency Microwave Land Surface Emissivities. Part I: Estimation under Clear and Precipitating Conditions. J. Hydrometeor., 15, 3-19, doi:10.1175/JHM-D-13-08.1.
Turk, J., Z. Haddad, P. E. Kirstetter, S. Ringerud, Y. You,
: An observationally based method for stratifying a priori passive microwave observations in a Bayesian‐based precipitation retrieval framework. Q. J. R. Meteor. Soc., 144, 145-164, doi:10.1002/qj.3203.
Ueno, K., W. Mito, R. Kanai, Y. Ueji, K. Suzuki, H. Kobayashi, I. Tamagawa, M. K. Yamamoto, and S. Shige,
: Distribution of precipitation depending on synoptic scale disturbances with satellite estimate comparisons in the Japanese Alps area during warm seasons. Journal of Geography, 128, 31-47, doi:.
Ullrich, P. A., C. M. Zarzycki, E. E. McClenny, M. C. Pinheiro, A. M. Stansfield, and K. A. Reed,
: TempestExtremes v2.1: a community framework for feature detection, tracking, and analysis in large datasets. Geosci. Model Dev., 14(8), 5023–5048, doi:10.5194/gmd-14-5023-2021.
Upadhyaya, S., P. E. Kirstetter, J. J. Gourley, and R. J. Kuligowski,
: On the Propagation of Satellite Precipitation Estimation Errors: From Passive Microwave to Infrared Estimates. J. Hydrometeor., 21(6), 1367–1381, doi:10.1175/JHM-D-19-0293.1.
Upadhyaya, S., P. E. Kirstetter, R. Kuligowski, and M. Searls,
: Classifying precipitation from GEO satellite observations: Diagnostic model. Quart. Journal of the Royal Meteorological Society, 147(739), 3318-3334, doi:10.1002/qj.4130.
Upadhyaya, S., P. E. Kirstetter, R. Kuligowski, J. Gourley, and H. Grams,
: Classifying precipitation from GEO satellite observations: Prognostic model. Quart. Journal of the Royal Meteorological Society, 147(739), 3394-3409, doi:10.1002/qj.4134.
Upadhyaya, S., P.E. Kirstetter, R. Kuligowski, M. Searls,
: Towards improved precipitation estimation with the GOES-16 advanced baseline imager: Algorithm and evaluation. Quart. Journal of the Royal Meteoro. Soc., 148(748), 3406-3427, doi:10.1002/qj.4368.
Upadhyaya, S., P.E. Kirstetter, R. Kuligowski, M. Searls,
: Exploring the Temporal Information From GEO Satellites for Estimating Precipitation With Convolutional Neural Networks. IEEE Geoscience and Remote Sensing Letters, 19, 1005905, doi:10.1109/LGRS.2022.3189535.
Utsumi, N., and H. Kim,
: Warm Season Satellite Precipitation Biases for Different Cloud Types Over Western North Pacific. IEEE Geoscience and Remote Sensing Letters, 15, 808–812, doi:10.1109/LGRS.2018.2815590.
Utsumi, N., F. J. Turk, Z. S. Haddad, P.-E. Kirstetter, and H. Kim,
: Evaluation of Precipitation Vertical Profiles Estimated by GPM-Era Satellite-Based Passive Microwave Retrievals. J. Hydrometeor., 22(1), 95–112, doi:10.1175/JHM-D-20-0160.1.
Utsumi, N., H. Kim, F. J. Turk, and Z. S. Haddad,
: Improving Satellite-Based Subhourly Surface Rain Estimates Using Vertical Rain Profile Information. J. Hydrometeor., 20, 1015–1026, doi:10.1175/JHM-D-18-0225.1.
Utsumi, N., H. Kim, S. Kanae, and T. Oki,
: Which weather systems are projected to cause future changes in mean and extreme precipitation in CMIP5 simulations?. J. Geophys. Res., 121, 10,522–10,537, doi:10.1002/2016JD024939.
Utsumi, N., H. Kim, S. Kanae, and T. Oki,
: Relative contributions of weather systems to mean and extreme global precipitation. J. Geophys. Res., 122, 152–167, doi:10.1002/2016JD025222.