2001. Pavolonis, Michael and Calvert, Corey. GOES-R AWG Aviation Team: Fog/low cloud detection. Greenbelt, MD, NASA, Goddard Space Flight Center, GOES-R Program Office, 2010, PowerPoint presentation. 

2002. Pavolonis, Michael and Heidinger, A. K.. The retrieval of cloud height and emissivity from passive measurements: Comparison of techniques. Boston, MA, American Meteorological Society, 2006, Abstract P4.6. 

2003. Pavolonis, Michael and Parker, Andrew. GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for SO2 detection. Version 1.0. Madison, WI, University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2010. Call Number: UW SSEC Publication No.10.09.P3. 
 Link to PDF

2004. Pavolonis, Michael and Sieglaff, Justin. Using the GOES-R AWG volcanic ash algorithm to track Eyjafjallajokull volcanic ash: Impacts on operations and research. Greenbelt, MD, NASA, Goddard Space Flight Center, GOES-R Program Office, 2010, PowerPoint presentation. 

2005. Pavolonis, Michael and Sieglaff, Justin. GOES-R AWG Aviation Team: Volcanic ash - detection and height. Greenbelt, MD, NASA, Goddard Space Flight Center, GOES-R Program Office, 2010, PowerPoint presentation. 

2006. Pavolonis, Michael and Sieglaff, Justin. GOES-R Advanced Baseline Imager (ABI) Algorithm Theoretical Basis Document for volcanic ash (detection and height). Version 2.0. NOAA, NESDIS, Center for Satellite Applications and Research, 2010. Call Number: UW SSEC Publication No.10.09.P1. 
 Link to PDF

2007. Pavolonis, Michael and Sieglaff, Justin. New automated methods for detecting volcanic ash and determining mass loading from infrared radiances: Looking towards the GOES-R era. Madison, WI, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2008, Abstract 1. 
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2008. Pavolonis, Michael J.. ProbSevere a new tool for NWS servere weather warning operations. National Oceanic and Atmospheric Administration (NOAA), 2015, PowerPoint presentation. 

2009. Pavolonis, Michael J.. From 'Big Data' to information: Volcanic, convective, and ceiling/visibility applications for OCONUS operations. National Oceanic and Atmospheric Administration (NOAA), 2016, PowerPoint presentation. 

2010. Pavolonis, Michael J.. New automated methods for detecting volcanic ash and determining mass loading from infrared radiances: Looking towards the NPOESS and GOES-R era's. Boston, MA, American Meteorological Society, 2008, Abstract P3.12. 

2011. Pavolonis, Michael J.. Advances in extracting cloud composition information from spaceborne infrared radiances - A robust alternative to brightness temperatures, part 1: Theory. Journal of Applied Meteorology and Climatology, Volume: 49, Issue: 9, 2010, pp.1992-2012. Reprint # 6348. 
 Link to PDF

2012. Pavolonis, Michael J.. Antarctic cloud radiative forcing at the surface estimated from the ISCCP D1 and AVHRR polar pathfinder dtaa sets, 1985-1993. Madison, WI, University of Wisconsin-Madison, Department of Atmospheric and Oceanic Sciences, 2002. Call Number: UW MET Publication No.02.05.P1. 

2013. Pavolonis, Michael J.. Cloud phase determination using infrared absorption optical depth ratios. Madison, WI, University of Wisconsin-Madison, Space Science and Engineering Center, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2011, abstract. 

2014. Pavolonis, Michael J.. GOES-R user testimonials: Research perspective. Greenbelt, MD, Goddard Space Flight Center, GOES-R Series Program Office, 2017, PowerPoint presentation. 
 Link to PDF

2015. Pavolonis, Michael J. and Heidinger, Andrew K.. Preliminary global cloud comparisons from the AVHRR, MODIS, and GLAS: Cloud amount and cloud overlap. Bellingham, WA, SPIE-International Society for Optical Engineering, 2005, pp.235-244. Reprint # 4195. 

2016. Pavolonis, Michael J. and Heidinger, Andrew K.. Advancements in identifying cirrus and multilayered cloud systems from operational satellite imagers at night. Bellingham, WA, SPIE-International Society for Optical Engineering, 2005, pp.225-234. Reprint # 4196. 

2017. Pavolonis, Michael J. and Heidinger, Andrew K.. Daytime cloud overlap detection from AVHRR and VIIRS. Journal of Applied Meteorology, Volume: 43, Issue: 5, 2004, pp.762-778. Reprint # 3752. 
 Link to PDF

2018. Pavolonis, Michael J. and Heidinger, Andrew K.. A comparison of HIRS cloud top pressure and AVHRR-derived cloud overlap. Melbourne, Australia, Bureau of Meteorology Research Centre, 2003, poster presentation. 1p. 
 Link to PDF

2019. Pavolonis, Michael J. and Heidinger, Andrew K.. Cloud overlap detection for HIRS and AVHRR. Melbourne, Australia, Bureau of Meteorology Research Centre, 2003, pp.648-653. Reprint # 4479. 
 Link to PDF

2020. Pavolonis, Michael J. and Heidinger, Andrew K.. Cloud overlap detection and analysis in the PATMOS-x dataset. Madison, WI, University of Wisconsin, Space Science and Engineering Center, Cooperative Institute for Meteorological Satellite Studies (CIMSS), 2005. PowerPoint presentation. 

2021. Pavolonis, Michael J. and Heidinger, Andrew K.. A comparison of AVHRR and HIRS global cloud types. Madison, WI, University of Wisconsin-Madison, 2004, pp.109. abstract. 
 Link to PDF

2022. Pavolonis, Michael J. and Key, J. R.. Simulation of the Antarctic climate using the Arctic Region Climate System Model (ARCSYM) and the AVHRR Polar Pathfinder (APP) data set. Boston, MA, American Meteorological Society, 2003, Abstract P1.5. 

2023. Pavolonis, Michael J. and Key, Jeffrey R.. Antarctic cloud radiative forcing at the surface estimated from the AVHRR Polar Pathfinder and ISCCP D1 datasets, 1985-93. Journal of Applied Meteorology, Volume: 42, Issue: 6, 2003, pp.827-840. Reprint # 3448. 
 Link to PDF

2024. Pavolonis, Michael J. and Key, Jeffrey R.. The influence of Antarctic cloud and surface properties on cloud radiative forcing at the surface. Boston, MA, American Meteorological Society, 2001, pp.172-175. Reprint # 2963. 

2025. Pavolonis, Michael J. and Sieglaff, J.. Advances in volcanic cloud satellite remote sensing. Boston, MA, American Meteorological Society, 2010, Abstract 8.6.