Justin Sieglaff



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Results: Found 18 records (displaying records 1 through 18)


1. Griffin, Sarah M.; Otkin, Jason A.; Rozoff, Christopher M.; Sieglaff, Justin M.; Cronce, Lee M. and Alexander, Curtis R. Methods for comparing simulated and observed satellite infrared brightness temperatures and what do they tell us?. Weather and Forecasting, Volume 32, Issue 1, 2017, pp.5-25. Reprint # 7824.
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2. Gravelle, Chad M.; Mecikalski, John R.; Line, William E.; Bedka, Kristopher M.; Petersen, Ralph A.; Sieglaff, Justin M.; Stano, Geoffrey T. and Goodman, Steven J. Demonstration of a GOES-R satellite convective toolkit to 'bridge the gap' between severe weather watches and warnings: An example from the 20 May 2013 Moore, Oklahoma, tornado outbreak. Bulletin of the American Meteorological Society, Volume 97, Issue 1, 2016, pp.69-84. Reprint # 7564.
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3. Schmit, Timothy J.; Goodman, Steven J.; Gunshor, Mathew M.; Sieglaff, Justin; Heidinger, Andrew K.; Bachmeier, A. Scott; Lindstrom, Scott S.; Terborg, Amanda; Feltz, Joleen; Bah,Kaba; Rudlosky, Scott; Lindsey, Daniel T.; Rabin, Robert M. and Schmidt, Christopher C. Rapid refresh information of significant events: Preparing users for the next generation of geostationary operational satellites. Bulletin of the American Meteorological Society, Volume 96, Issue 4, 2015, 561–576, supplement. Reprint # 7393.
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4. Pavolonis, Michael J.; Sieglaff, Justin and Cintineo, John. Spectrally Enhanced Cloud Objects - A generalized framework for automated detection of volcanic ash and dust clouds using passive satellite measurements: 2. Cloud object analysis and global application. Journal of Geophysical Research-Atmospheres, Volume 120, Issue 15, 2015, pp.7842-7870. Reprint # 7478.
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5. Pavolonis, Michael J.; Sieglaff, Justin and Cintineo, John. Spectrally Enhanced Cloud Objects - A generalized framework for automated detection of volcanic ash and dust clouds using passive satellite measurements: 1. Multispectral analysis. Journal of Geophysical Research-Atmospheres, Volume 120, Issue 15, 2015, pp.7813-7841. Reprint # 7477.
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6. Schmit, Timothy J.; Goodman, Steven J.; Gunshor, Mathew M.; Sieglaff, Justin; Heidinger, Andrew K.; Bachmeier, A. Scott; Lindstrom, Scott S.; Terborg, Amanda; Feltz, Joleen; Bah,Kaba; Rudlosky, Scott; Lindsey, Daniel T.; Rabin, Robert M. and Schmidt, Christopher C. Rapid refresh information of significant events: Preparing users for the next generation of geostationary operational satellites. Supplement. Bulletin of the American Meteorological Society, Volume 96, Issue 4, 2015, ES55-ES63. Reprint # 7393.
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7. Monette, Sarah A. and Sieglaff, Justin M. Probability of convectively induced turbulence associated with geostationary satellite-inferred cloud-top cooling. Journal of Applied Meteorology and Climatology, Volume 53, Issue 2, 2014, 429–436. Reprint # 7167.
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8. Sieglaff, Justin M.; Cronce, Lee M. and Feltz, Wayne F. Improving satellite-based convective cloud growth monitoring with visible optical depth retrievals. Journal of Applied Meteorology and Climatology, Volume 53, Issue 2, 2014, 506–520. Reprint # 7169.
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9. 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, 639–653. Reprint # 7227.
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10. Sieglaff, Justin M.; Hartung, Daniel C.; Feltz, Wayne F.; Cronce, Lee M. and Lakshmanan, Valliappa. A satellite-based convective cloud object tracking and multipurpose data fusion tool with application to developing convection. Journal of Atmospheric and Oceanic Technology, Volume 30, Issue 3, 2013, 510–525. Reprint # 6952.
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11. Pavolonis, Michael J.; Heidinger, Andrew K. and Sieglaff, Justin. Automated retrievals of volcanic ash and dust cloud properties from upwelling infrared measurements. Journal of Geophysical Research-Atmospheres, Volume 118, Issue 3, 2013, doi:10.1002/jgrd.50173. Reprint # 6961.
12. Hartung, Daniel C.; Sieglaff, Justin M.; Cronce, Lee M. and Feltz, Wayne F. An intercomparison of UW cloud-top cooling rates with WSR-88D radar data. Weather and Forecasting, Volume 28, Issue 2, 2013, 463–480. Reprint # 6972.
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13. 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, 2009–2023. Reprint # 7077.
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14. Bikos, Dan; Lindsey, Daniel T.; Otkin, Jason; Sieglaff, Justin; Grasso, Louie; Siewert, Chris; Correia, James Jr.; Coniglio, Michael; Rabin, Robert; Kain, John S. and Dembek, Scott. Synthetic satellite imagery for real-time high-resolution model evaluation. Weather and Forecasting, Volume 27, Issue 3, 2012, 784–795. Reprint # 6737.
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15. Denlinger, Roger P.; Pavolinis, Mike and Sieglaff, Justin. A robust method to forecast volcanic ash clouds. Journal of Geophysical Research-Atmospheres, Volume 117, 2012, doi:10.1029/2012JD017732. Reprint # 6790.
16. Sieglaff, Justin M.; Cronce, Lee M.; Feltz, Wayne F.; Bedka, Kristopher M.; Pavolonis, Michael J. and Heidinger, Andrew K. Nowcasting convective storm initiation using satellite-based box-averaged cloud-top cooling and cloud-type trends. Journal of Applied Meteorology and Climatology, Volume 50, Issue 1, 2011, pp.110-126. Reprint # 6404.
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17. Sieglaff, Justin M.; Schmit, Timothy J.; Menzel, W. Paul and Ackerman, Steven A. Inferring convective weather characteristics with geostationary high spectral resolution IR window measurements: A look into the future. Journal of Atmospheric and Oceanic Technology, Volume 26, Issue 8, 2009, pp.1527-1541. Reprint # 6096.
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18. Otkin, Jason A.; Greenwald, Thomas J.; Sieglaff, Justin and Huang, Hung-Lung. Validation of a Large-Scale Simulated Brightness Temperature Dataset Using SEVIRI Satellite Observations. Journal of Applied Meteorology and Climatology, Volume 48, Issue 8, 2009, pp.1613-1626. Reprint # 6110.
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