| An objective high-resolution hail climatology of the contiguous United States JL Cintineo, TM Smith, V Lakshmanan, HE Brooks, KL Ortega Weather and Forecasting 27 (5), 1235-1248, 2012 | 228 | 2012 |
| An empirical model for assessing the severe weather potential of developing convection JL Cintineo, MJ Pavolonis, JM Sieglaff, DT Lindsey Weather and Forecasting 29 (3), 639-653, 2014 | 99 | 2014 |
| The NOAA/CIMSS ProbSevere model: Incorporation of total lightning and validation JL Cintineo, MJ Pavolonis, JM Sieglaff, DT Lindsey, L Cronce, J Gerth, ... Weather and Forecasting 33 (1), 331-345, 2018 | 62 | 2018 |
| Development of a human–machine mix for forecasting severe convective events CD Karstens, J Correia, DS LaDue, J Wolfe, TC Meyer, DR Harrison, ... Weather and Forecasting 33 (3), 715-737, 2018 | 56 | 2018 |
| Evolution of severe and nonsevere convection inferred from GOES-derived cloud properties JL Cintineo, MJ Pavolonis, JM Sieglaff, AK Heidinger Journal of Applied Meteorology and Climatology 52 (9), 2009-2023, 2013 | 56 | 2013 |
| Spectrally Enhanced Cloud Objects—A generalized framework for automated detection of volcanic ash and dust clouds using passive satellite measurements: 1. Multispectral analysis MJ Pavolonis, J Sieglaff, J Cintineo Journal of Geophysical Research: Atmospheres 120 (15), 7813-7841, 2015 | 55 | 2015 |
| NOAA ProbSevere v2. 0—ProbHail, ProbWind, and ProbTor JL Cintineo, MJ Pavolonis, JM Sieglaff, L Cronce, J Brunner Weather and Forecasting 35 (4), 1523-1543, 2020 | 48 | 2020 |
| Geostationary Operational Environmental Satellite (GOES)-14 super rapid scan operations to prepare for GOES-R TJ Schmit, SJ Goodman, DT Lindsey, RM Rabin, KM Bedka, MM Gunshor, ... Journal of Applied Remote Sensing 7 (1), 073462-073462, 2013 | 43 | 2013 |
| Spectrally Enhanced Cloud Objects—A generalized framework for automated detection of volcanic ash and dust clouds using passive satellite measurements: 2. Cloud object … MJ Pavolonis, J Sieglaff, J Cintineo Journal of Geophysical Research: Atmospheres 120 (15), 7842-7870, 2015 | 37 | 2015 |
| A deep-learning model for automated detection of intense midlatitude convection using geostationary satellite images JL Cintineo, MJ Pavolonis, JM Sieglaff, A Wimmers, J Brunner, W Bellon Weather and Forecasting 35 (6), 2567-2588, 2020 | 30 | 2020 |
| Automated Detection of Explosive Volcanic Eruptions Using Satellite‐Derived Cloud Vertical Growth Rates MJ Pavolonis, J Sieglaff, J Cintineo Earth and Space Science 5 (12), 903-928, 2018 | 29 | 2018 |
| Remote sensing of volcanic ash with the GOES-R series MJ Pavolonis, JM Sieglaff, JL Cintineo The GOES-R Series, 103-124, 2020 | 13 | 2020 |
| ProbSevere LightningCast: A deep-learning model for satellite-based lightning nowcasting JL Cintineo, MJ Pavolonis, JM Sieglaff Weather and Forecasting 37 (7), 1239-1257, 2022 | 9 | 2022 |
| J9. 3 AN AUTOMATED SYSTEM FOR PROCESSING THE MULTI-YEAR REANALYSIS OF REMOTELY SENSED STORMS (MYRORSS) J Cintineo, T Smith, V Lakshmanan, S Ansari | 6 | 2011 |
| Transforming satellite data to products in the era of big data MJ Pavolonis, CC Calvert, J Cintineo, J Sieglaff Adding Value: Applications of Weather and Climate Services-Abstracts of the …, 2017 | 1 | 2017 |
| An objective radar-derived hail climatology for the contiguous United States JL Cintineo University of Oklahoma, 2011 | 1 | 2011 |
| Performance of a Probabilistic Cloud-to-Ground Lightning Prediction Algorithm J Cintineo, V Lakshmanan, T Smith | 1 | 2010 |
| NOAA’s ProbSevere LightningCast: Progress and Updates toward Transition-to-Operations JL Cintineo, M Pavolonis, SS Lindstrom, J Sieglaff 104th AMS Annual Meeting, 2024 | | 2024 |
| Exploring Severe Weather Nowcasting Predictions Using Atmospheric Observations and Deep Learning JL Cintineo, M Pavolonis, J Sieglaff 104th AMS Annual Meeting, 2024 | | 2024 |
| True Positive Convective Storms Without Lightning in ThunderCast SM Ortland, MJ Pavolonis, JL Cintineo 104th AMS Annual Meeting, 2024 | | 2024 |
