Rapid refresh information of significant events preparing users for the next generation of geostationary operational satellites

Bulletin of the American Meteorological Society

Volumn 96, Issue 4, 2015, Pages 561-576

  Schmit, Timothy J ^a   Goodman, Steven J ^b   Gunshor, Mathew M ^c   Sieglaff, Justin ^c   Heidinger, Andrew K ^a   Bachmeier, A Scott ^c   Lindstrom, Scott S ^c   Terborg, Amanda ^c   Feltz, Joleen ^c   Bah, Kaba ^c   Rudlosky, Scott ^d   Lindsey, Daniel T ^d   Rabin, Robert M ^e   Schmidt, Christopher C ^c  

^a Center for Satellite Applications and Research (STAR)   (United States)

^b OFFICE OF RESEARCH AND APPLICATIONS   (United States)

^c UNIVERSITY OF WISCONSIN MADISON   (United States)

^d NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

^e NATIONAL SEVERE STORMS LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EARTH ATMOSPHERE; STORMS;

DERIVED PRODUCTS; ENVIRONMENTAL PHENOMENA; HIGH TEMPORAL RESOLUTION; HUMAN ACTIVITIES; MULTI-SPECTRAL IMAGERY; RAPID SCAN; SEVERE STORMS; TROPICAL CYCLONE;

GEOSTATIONARY SATELLITES;

EID: 84930422146     PISSN: 00030007     EISSN: None     Source Type: Journal    
DOI: 10.1175/BAMS-D-13-00210.1     Document Type: Article

References (33)

1. Adler, R. F., and D. D. Fenn, 1979: Thunderstorm intensity as determined from satellite data. J. Appl. Meteor., 18, 502-517, doi:10.1175/1520-0450(1979)0182.0.CO;2.
2. American Meteorological Society, cited 2014: Derecho. Glossary of Meteorology. [Available online at http://glossary.ametsoc.org/wiki/derecho.]
3. Bedka, K. M., J. Brunner, R. Dworak, W. Feltz, J. Otkin, and T. Greenwald, 2010: Objective satellite-based overshooting top detection using infrared window channel brightness temperature gradients. J. Appl. Meteor. Climatol., 49, 181-202, doi:10.1175/2009JAMC2286.1.
4. -, C. Wang, R. Rogers, L. D. Carey, W. Feltz, and J. Kanak, 2015: Examining deep convective cloud evolution using total lightning, WSR-88D, and GOES-14 super rapid scan datasets. Wea. Forecasting, doi:10.1175/WAF-D-14-00062.1, in press.
5. Butler, A., cited 2013: GOES control problem could be due to micrometeroid collision. Aviation Week. [Available online at www.aviationweek.com/Article.aspx?id=/article-xml/asd-05-30-2013-p03-01-583298.xml.].
6. Cintineo, J. L., M. J. Pavolonis, J. M. Sieglaff, and A. K. Heidinger, 2013: Evolution of severe and nonsevere convection inferred from GOES-derived cloud properties. J. Appl. Meteor. Climatol., 52, 2009-2023, doi:10.1175/JAMC-D-12-0330.1.
7. -, -, -, and D. T. Lindsey, 2014: An empirical model for assessing the severe weather potential of developing convection. Wea. Forecasting, 29, 639-653, doi:10.1175/WAF-D-13-00113.1.
8. Davenport, J. C., and R. J. Kuligowski, 2008: An improved GOES parallax correction scheme for rainfall estimation. 22nd Conf. on Hydrology, New Orleans, LA, Amer. Meteor. Soc., 9.4. [Available online at https://ams.confex.com/ams/pdfpapers/134462.pdf.]
9. Davis, G., 2007: History of the NOAA satellite program. J. Appl. Remote Sens., 1, 012504, doi:10.1117/1.2642347.
10. Dworak, R., K. Bedka, J. Brunner, and W. Feltz, 2012: Comparison between GOES-12 overshooting-top detections, WSR-88D radar reflectivity, and severe storm reports. Wea. Forecasting, 27, 684-699, doi:10.1175/WAF-D-11-00070.1.
11. Fromm, M., D. T. Lindsey, R. Servranckx, G. Yue, T. Trickl, R. Sica, P. Doucet, and S. Godin-Beekmann, 2010: The untold story of pyrocumulonimbus. Bull. Amer. Meteor. Soc., 91, 1193-1209, doi:10.1175/2010BAMS3004.1.
12. Gatlin, P. N., and S. J. Goodman, 2010: A total lightning trending algorithm to identify severe thunderstorms. J. Atmos. Oceanic Technol., 27, 3-22, doi:10.1175/2009JTECHA1286.1.
13. Goodman, S. J., D. E. Buechler, P. D. Wright, and W. D. Rust, 1988: Lightning and precipitation history of a microburst producing storm. Geophys. Res. Lett., 15, 1185-1188, doi:10.1029/GL015i011p01185.
14. -, and Coauthors, 2012: The GOES-R proving ground: accelerating user readiness for the next-generation geostationary environmental satellite system. Bull. Amer. Meteor. Soc., 93, 1029-1040, doi:10.1175/BAMS-D-11-00175.1.
15. -, and Coauthors, 2013: The GOES-R Geostationary Lightning Mapper (GLM). Atmos. Res., 125-126, 34-49, doi:10.1016/j.atmosres.2013.01.006.
16. Heidinger, A. K., and M. J. Pavolonis, 2009: Gazing at cirrus clouds for 25 years through a split window. Part I: Methodology. J. Appl. Meteor. Climatol., 48, 1100-1116, doi:10.1175/2008JAMC1882.1.
17. Martin, E. R., and R. H. Johnson, 2008: An observational and modeling study of an atmospheric internal bore during NAME 2004. Mon. Wea. Rev., 136, 4150-4167, doi:10.1175/2008MWR2486.1.
18. Miller, S. D., C. C. Schmidt, T. J. Schmit, and D. W. Hillger, 2012: A case for natural colour imagery from geostationary satellites, and an approximation for the GOES-R ABI. Int. J. Remote Sens., 33, 3999-4028, doi:10.1080/01431161.2011.637529.
19. Prins, E. M., 1996: The GOES-8 automated biomass burning algorithm (ABBA) introducing new capabilities for monitoring diurnal fire activity in the Western Hemisphere. Int. For. Fire News, 15, 49-52.
20. Purdom, J. F. W., 1976: Some uses of high-resolution GOES imagery in the mesoscale forecasting of convection and its behavior. Mon. Wea. Rev., 104, 1474-1483, doi:10.1175/1520-0493(1976)1042.0.CO;2.
21. Ralph, F. M., and Coauthors, 2013: The emergence of weather-related test beds linking research and forecasting operations. Bull. Amer. Meteor. Soc., 94, 1187-1211, doi:10.1175/BAMS-D-12-00080.1.
22. Schmit, T. J., M. M. Gunshor, W. P. Menzel, J. Li, S. Bachmeier, and J. J. Gurka, 2005: Introducing the next-generation advanced baseline imager on GOES-R. Bull. Amer. Meteor. Soc., 86, 1079-1096, doi:10.1175/BAMS-86-8-1079.
23. -, and Coauthors, 2013: Geostationary Operational Environmental Satellite (GOES)-14 super rapid scan operations to prepare for GOES-R. J. Appl. Remote Sens., 7, 073462, doi:10.1117/1.JRS.7.073462.
24. Schroeder, W., M. Ruminski, I. Csiszar, L. Giglio, E. Prins, C. Schmidt, and J. Morisette, 2008: Validation analyses of an operational fire monitoring product: The hazard mapping system. Int. J. Remote Sens., 29, 6059-6066, doi:10.1080/01431160802235845.
25. Schultz, C. J., W. A. Petersen, and L. D. Carey, 2009: Preliminary development and evaluation of lightning jump algorithms for the real-time detection of severe weather. J. Appl. Meteor. Climatol., 48, 2543-2563, doi:10.1175/2009JAMC2237.1.
26. -, -, and -, 2011: Lightning and severe weather: A comparison between total and cloud-to-ground lightning trends. Wea. Forecasting, 26, 744-755, doi:10.1175/WAF-D-10-05026.1.
27. Setvák, M., K. Bedka, D. T. Lindsey, A. Sokol, Z. Charvát, J. Štástka, and P. K. Wang, 2013: A-Train observations of deep convective storm tops. Atmos. Res., 123, 229-248, doi:10.1016/j.atmosres.2012.06.020.
28. Shapiro, M., and A. Thorpe, 2004: The Observing System Research and Predictability Experiment (THORPEX): International science plan. WMO Tech. Doc. WMO/TD-1246, 57 pp. [Available online at http://library.wmo.int/pmb-ged/WMO-TD1246e.pdf.]
29. Sieglaff, J. M., D. C. Hartung, W. F. Feltz, L. M. Cronce, and L. Valliappa, 2013: A satellite-based convective cloud object tracking and multipurpose data fusion tool with application to developing convection. J. Atmos. Oceanic Technol., 30, 510-525, doi:10.1175/JTECH-D-12-00114.1.
30. -, L. M. Cronce, and W. F. Feltz, 2014: Improving satellite-based convective cloud growth monitoring with visible optical depth retrievals. J. Appl. Meteor. Climatol., 53, 506-520, doi:10.1175/JAMC-D-13-0139.1.
31. Stano, G. T., C. J. Schultz, L. D. Carey, D. R. MacGorman, and K. M. Calhoun, 2014: Total lightning observations and tools for the 20 May 2013 Moore, Oklahoma, tornadic supercell. J. Oper. Meteor., 2, 71-88, doi:10.15191/nwajom.2014.0207.
32. Weaver, J. F., and D. T. Lindsey, 2004: Some frequently overlooked visual severe thunderstorm characteristics observed on GOES imagery: A topic for future research. Mon. Wea. Rev., 132, 1529-1533, doi:10.1175/1520-0493(2004)1322.0.CO;2.
33. Zhang, J., and Coauthors, 2011: National mosaic and multi-sensor QPE (NMQ) system: Description, results, and future plans. Bull. Amer. Meteor. Soc., 92, 1321-1338, doi:10.1175/2011BAMS-D-11-00047.1.