Schwerdtfeger Library Publications Database

Results: Found 3271 records (displaying records 301 through 325)

301. Cintineo, John L.; Pavolonis, M. J. and Sieglaff, J.. Preliminary evaluation of a fused algorithm for the prediction of severe storms. Boston, MA, American Meteorological Society, 2014, Abstract 7.1.

302. Cintineo, John L.; Pavolonis, M. J.; Sieglaff, J. and Brunner, J. C.. The impact of total lightning information in the NOAA/CIMSS ProbSevere model. Boston, MA, American Meteorological Society, 2016, Abstract 9.1.

303. Cintineo, John L.; Pavolonis, Michael J. and Sieglaff, Justin M.. ProbSevere LightningCast: a deep-learning model for satellite-based lightning nowcasting. Weather and Forecasting, Volume: 37, Issue: 7, 2022, pp.1239-1257. Reprint # 8869.
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304. Cintineo, John L.; Pavolonis, Michael J.; Sieglaff, Justin M. and Heidinger, Andrew K.. Evolution of severe and nonsevere convection inferred from GOES-derived cloud properties. Journal of Applied Meteorology and Climatology, Volume: 52, Issue: 9, 2013. Reprint # 7077.
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305. Cintineo, John L.; Pavolonis, Michael J.; Sieglaff, Justin M. and Lindsey, Daniel T.. An empirical model for assessing the severe weather potential of developing convection. Weather and Forecasting, Volume: 29, Issue: 3, 2014. Reprint # 7227.
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306. Cintineo, John L.; Pavolonis, Michael J.; Sieglaff, Justin M.; Cronce, Lee and Brunner, Jason. NOAA ProbSevere v2.0-ProbHail, ProbWind, and ProbTor. Weather and Forecasting, Volume: 35, Issue: 4, 2020, pp.1523-1543. Reprint # 8606.
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307. Cintineo, John L.; Pavolonis, Michael J.; Sieglaff, Justin M.; Wimmers, Anthony; Brunner, Jason and Bellon, Willard. A Deep-Learning Model for Automated Detection of Intense Midlatitude Convection Using Geostationary Satellite Images. Weather and Forecasting, Volume: 35, Issue: 6, 2020. Reprint # 8653.
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308. Cintineo, John; Pavolonis, Michael; Sieglaff, Justin; Brunner, Jason and Lindsey, Daniel. Next generation geostationary satellite observations in a multi-sensor severe weather nowcasting tool. Darmstadt, Germany, European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), 2017, Abstract 395.

309. Cintineo, Rebecca M.; Strabala, K. I.; Gumley, L. E.; Huang, A.; Borbas, E.; Weisz, E. and Pierce, B.. IMAPP: Supporting the Aqua and Terra operational community. Boston, MA, American Meteorological Society, 2015, Abstract 621.

310. Cintineo, Rebecca M.; Strabala, K. I.; Gumley, L. E.; Huang, A.; Davies, J. E.; Borbas, E.; Weisz, E. and Pierce, B.. IMAPP: Supporting the Aqua and Terra operational community. Boston, MA, American Meteorological Society, 2014, Abstract 341.

311. Cintineo, Rebecca; Davies, James; Pierce, Bradley; Weisz, Elisabeth; Smith, Nadia and Strabala, Kathy. IDEA-A air quality forecast software package: Aerosol, ozone, and carbon monoxide detection and trajectories. Madison, WI, University of Wisconsin-Madison, Space Science and Engineering Center, Cooperative Institute of Meteorological Satellite Studies (CIMSS), 2014. 7p.
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312. Cintineo, Rebecca; Davies, James; Pierce, Bradley; Weisz, Elisabeth; Smith, Nadia and Strabala, Kathy. IDEA-A air quality forecast software package: Aerosol, ozone, and carbon monoxide detection and trajectories. Madison, WI, University of Wisconsin-Madison, Space Science and Engineering Center, Cooperative Institute of Meteorological Satellite Studies (CIMSS), 2014, poster presentation. 1p.
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313. Clothiaux, E. E.; Ackerman, T. P.; Ackerman, S. A.; Minnis, P.; Miller, M. A.; Verlinde, J.; Berendes, T. A.; Di Girolamo, L.; Key, J.; Turner, D. D.; Frey, R. A.; Bachmann, C. M. and Nolin, A.. Cloud detection: One possible future in the ARM and EOS timeframes. Boston, MA, American Meteorological Society, 1999, pp.258-261. Reprint # 2585.

314. Clough, S. A.; Brown, P. D.; Liljegren, J. C.; Shippert, T. R.; Turner, D. D.; Knuteson, R. O.; Revercomb, H. E. and Smith, W. L.. Implications for atmospheric state specification from the AERI/LBLRTM Quality Measurement Experiment and the MWR/LBLRTM Quality Measurement Experiment. Washington, DC, US Department of Energy, Office of Energy Research, Office of Biological and Environmental Research, Environmental Sciences Division, 1997, pp.45-49. Reprint # 2375.

315. Clough, Shepard A.; Worsham, Robert D.; Smith, William L.; Revercomb, Henry E.; Knuteson, Robert O.; Anderson, Gail P.; Hoke, Michael L. and Knelzys, Francis X.. Validation of fascode calculations with HIS spectral radiance measurements. Hampton, VA, A. Deepak Pub., 1989, pp.376-379. Reprint # 1712.

316. Collard, A. D.; Ackerman, S. A.; Smith, W. L. and Feltz, W. F.. Analysis of errors in cirrus cloud particle size derivation using the Atmospheric Emitted Radiance Interferometer. Washington, DC, Optical Society of America, 1995, pp.87-89. Reprint # 2770.

317. Collard, A. D.; Ackerman, S. A.; Smith, W. L.; Ma, H. E.; Revercomb, H. E.; Knuteson, R. O. and Lee, S. -C.. Cirrus cloud properties derived from High Spectral Resolution Infrared Spectrometry during FIRE II. Part III: Ground-based HIS results. Journal of the Atmospheric Sciences, Volume: 52, Issue: 23, 1995, pp.4264-4275. Reprint # 2223.
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318. Collard, A. D.; Knuteson, R. O.; Ackerman, S. A.; Smith, W. L. and Revercomb, H. E.. Cloud microphysical and optical properties from the Atmospheric Emitted Radiance Interferometer at the April 1994 ARM CART intensive operations period. Washington, DC, Optical Society of America, 1995, pp.168-170. Reprint # 2773.

319. Connell, B.; Schmit, T.; Gurka, J.; Goodman, S.; Hillger, D. and Hill, S.. New training: GOES-R 101. Madison, WI, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2009, Abstract 33.
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320. Connell, Bernadette H.; Bikos, D.; Braun, J.; Bachmeier, A. S.; Lindstrom, S. S.; Mostek, A.; DeMaria, M. and Schmit, T. J.. Training for GOES-R directed toward forecasters. Boston, MA, American Meteorological Society (AMS), 2011, Abstract 626.

321. Connell, Bernadette H.; Bikos, D.; Braun, J.; Bachmeier, A. S.; Lindstrom, S.; Mostek, A.; Davison, M.; Caesar, K. A.; Castro, V.; Veeck, L.; DeMaria, M. and Schmit, T. J.. Satellite training activities: VISIT, SHyMet and WMO VLab Focus Group. Boston, MA, American Meteorological Society, 2012, Abstract 487.

322. Connell, Bernadette H.; Bikos, D.; Szoke, E. J.; Bachmeier, A. S.; Lindstrom S.; Mostek, A.; Motta, B.; Schmit, T. J.; Davison, M.; Caesar, K. A.; Castro, V. and Veeck, L.. Satellite training activities: VISIT, SHyMet and WMO VLab. Boston, MA, American Meteorological Society, 2014, Abstract 692.

323. Costa, Simone M. S.; Negri, Renato G.; Ferreira, Nelson J.; Schmit, Timothy J.; Arai, Nelson; Flauber, Wagner; Ceballos, Juan; Vila, Daniel; Rodrigues, Jurandir; Machado, Luiz A.; Pereira, Sergio; Bottino, Marcus Jorge; Sismanoglu, Raffi Agop and Langden, Pedro. A successful practical experience with dedicated Geostationary Operational Environmental Satellites GOES-10 and -12 supporting Brazil. Bulletin of the American Meteorological Society, Volume: 99, Issue: 1, 2018, pp.33-47. Reprint # 8232.
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324. Cousins, Dan and Smith, William L.. National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I). Bellingham, WA, SPIE-The International Society for Optical Engineering, 1997, pp.323-331. Reprint # 2720.

325. Cox, S. J.; Stackhouse, P. W.; Harvey, V. L.; Pierce, R. B. and Miskolczi, F. M.. Assessing dust and biomass aerosol radiative effects at Ilorin, Nigeria, from instruments and models. Washington, DC, American Geophysical Union, 2003, Abstract A12B-0095.