1. Elsberry, Russell L.; Feldmeier, Joel W.; Hway-Jen, Chen and Velden, Christopher S. High Temporal Resolution Analyses with GOES-16 Atmospheric Motion Vectors of Mesovortex Rapid Intensification in Subtropical Cyclone Henri (2021). Weather and Forecasting, Volume 38, Issue 7, 2023, 1173–1194. Reprint #8974.
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2. Griffin, Sarah M.; Wimmers, Anthony and Velden, Christopher S. Predicting rapid intensification in North Atlantic and eastern North Pacific tropical cyclones using a convolutional neural network. Weather and Forecasting, Volume 37, Issue 8, 2022, pp.1333-1355. Reprint # 8844.
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3. Lewis, William E.; Olander, Timothy L.; Velden, Christopher S.; Rozoff, Christopher and Alessandrini, Stefano. Analog ensemble methods for improving satellite-based intensity estimates of tropical cyclones. Atmosphere, Volume 12, Issue 7, 2021, pp.830. Reprint # 8711.
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4. Ryglicki, David R.; Velden, Christopher S.; Reasor, Paul D.; Hodyss, Daniel and Doyle, James D. Observations of atypical rapid intensification characteristics in Hurricane Dorian (2019). Monthly Weather Review, Volume 149, Issue 7, 2021, pp.2131-2150. Reprint # 8720.
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5. Olander, Timothy; Wimmers, Anthony; Velden, Christopher and Kossin, James P. Investigation of machine learning using satellite-based advanced Dvorak technique analysis parameters to estimate tropical cyclone intensity. Weather and Forecasting, Volume 36, Issue 6, 2021, 2161–2186. Reprint # 8748.
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6. Courtney, J.; Burton, A.; Olander, T.; Ritchie, E.; Velden, C. and Stark, C. Towards an objective historical tropical cyclone dataset for the Australian region. Tropical Cyclone Research and Review, Volume 8, Issue 4, 2020. Reprint # 8475.
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7. Li, Jinlong; Li, Jun; Velden, Christopher; Wang, Pei; Schmit, Timothy J. and Sippel, Jason. Impact of Rapid-Scan-Based Dynamical Information From GOES-16 on HWRF Hurricane Forecasts. Journal of Geophysical Research-Atmospheres, Volume 125, Issue 3, 2020, e2019JD031647. Reprint # 8511.
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8. Elsberry, Russell L.; Buholzer, Natasha; Velden, Christopher S. and Jordan, Mary S. Satellite-based observations of nonlinear relationships between vertical wind shear and intensity changes during the life cycle of Hurricane Joaquin (2015). Weather and Forecasting, Volume 35, Issue 3, 2020, pp.939-958. Reprint # 8531.
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9. Lewis, William E.; Velden, Christopher S. and Stettner, David. Strategies for assimilating high-density atmospheric motion vectors into a regional tropical cyclone forecast model (HWRF). Atmosphere, Volume 11, Issue 6, 2020, pp.673. Reprint # 8569.
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10. Kossin, James P.; Knapp, Kenneth R.; Olander, Timothy L. and Velden, Christopher S. Global increase in major tropical cyclone exceedance probability over the past four decades. Proceedings of the National Academy of Sciences of the United States of America, Volume 117, Issue 22, 2020, pp.11975-11980. Reprint # 8535.
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11. Velden, Christopher S. and Herndon, Derrick. A consensus approach for estimating tropical cyclone intensity from meteorological satellites: SATCON. Weather and Forecasting, Volume 35, Issue 4, 2020, pp.1645-1662. Reprint # 8611.
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12. Hoover, Brett T and Velden, Chris S. Adjoint-derived impact of assimilated observations on tropical cyclone intensity forecasts of Hurricane Joaquin (2015) and Hurricane Matthew (2016). Journal of Atmospheric and Oceanic Technology, Volume 37, Issue 8, 2020, pp.1333-1352. Reprint # 8574.
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13. Stettner, David; Velden, Christopher; Rabin, Robert; Wanzong, Steve; Daniels, Jaime and Bresky, Wayne. Development of enhanced vortex-scale atmospheric motion vectors for hurricane applications. Remote Sensing, Volume 11, Issue 17, 2019. Reprint # 8459.
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14. Anthes, Richard A.; Maier, Mark W.; Ackerman, Steve; Atlas, Robert; Callahan, Lisa W.; Dittberner, Gerald; Edwing, Richard; Emch, Pamela G.; Ford, Michael; Gail, William B.; Goldberg, Mitch; Goodman, Steve; Kummerow, Christian; Onsager, Terrance; Schrab, Kevin; Velden, Chris; Vonderhaar, Thomas and Yoe, James G. Developing priority observational requirements from space using multi-attribute utility theory. Bulletin of the American Meteorological Society, Volume 100, Issue 9, 2019, pp.1753-1773. Reprint # 8462.
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15. Posselt, Derek J.; Wu, Longtao; Mueller, Kevin; Huang, Lei; Irion, Fredrick W.; Brown, Shannon; Su, Hui; Santek, David and Velden, Christopher S. Quantitative assessment of state-dependent atmospheric motion vector uncertainties. Journal of Applied Meteorology and Climatology, Volume 58, Issue 11, 2019, pp.2479-2495. Reprint # 8473.
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16. Griffin, Sarah M. and Velden, Christopher S. Hazard avoidance products for convectively-induced turbulence in support of high-altitude Global Hawk aircraft missions. Pure and Applied Geophysics, Volume 176, Issue 5, 2019, pp.2045-2055. Reprint # 8375.
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| 17. Leslie, R. V.; Blackwell, W. J.; Braun, S. A.; Bennartz, R.; Chirokova, G.; DeMaria, M.; Greenwald, T.; Gumley, L. E.; Herndon, D. C.; Kidd, C.; Matsui, T. and Velden, C. S. NASA Tropics Earth Venture Mission: Payload Characteristics and Data Products. 2019 Joint Satellite Conference, 2nd and 3rd, Boston, MA, 28 September – 04 October 2019. American Meteorological Society, Boston, MA, 2019, Poster 148. |
18. Wimmers, Anthony; Velden, Christopher and Cossuth, Joshua H. Using deep learning to estimate tropical cyclone intensity from satellite passive microwave imagery. Monthly Weather Review, Volume 147, Issue 6, 2019, pp.2261-2282. Reprint # 8393.
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19. Olander, Timothy L. and Velden, Christopher S. The Advanced Dvorak Technique (ADT) for estimating tropical cyclone intensity: update and new capabilities. Weather and Forecasting, Volume 34, Issue 4, 2019, pp.905-922. Reprint # 8401.
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| 20. Daniels, Jaime M.; Bresky, W.; Bailey, A.; Allegrino, A.; Wanzong, S. and Velden, C. S. Introducing Atmospheric Motion Vectors derived from the GOES-16 Advanced Baseline Imager (ABI). Annual Symposium on New Generation Operational Environmental Satellite Systems, 14th, Houston, TX, 7-11 January 2018. American Meteorological Society, Boston, MA, 2018, Abstract 11A.3. |
21. Daniels, Jaime; Bresky, Wayne; Bailey, Andrwe; Allegrino, Americo; Wanzong, Steve and Velden, Chris. Introducing Atmospheric Motion Vectors derived from the GOES-16 Advanced Baseline Imager (ABI). International Winds Workshop, 14th, Jeju City, South Korea, 23-27 April 2018. University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies (CIMSS), Madison, WI, 2018, PowerPoint presentation. 35 slides,
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22. Bailey, Andrwe; Bresky, Wayne; Daniels, Jaime; Allegrino, Americo; Wanzong, Steve and Velden, Chris. Error characterization and validaton of Atmospheric Motion Vectors from the GOES-16 Advanced Baseline Imager (ABI). International Winds Workshop, 14th, Jeju City, South Korea, 23-27 April 2018. University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies (CIMSS), Madison, WI, 2018, poster presentation. 1p,
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23. Stettner, David; Velden, Christopher; Wanzong, Steve; Daniels, Jaime; Bresky, Wayne; Rabin, Robert and Apke, Jason. Telescoping in to the convective scales: Development of AMV processing strategies and applications. International Winds Workshop, 14th, Jeju City, South Korea, 23-27 April 2018. University of Wisconsin-Madison, Cooperative Institute for Meteorological Satellite Studies (CIMSS), Madison, WI, 2018, PowerPoint presentation. 30 slides,
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| 24. Blackwell, William J.; Braun, S. A.; Velden, C. S.; DeMaria, M.; Atlas, R.; Dunion, J. P.; Marks, F. D. Jr.; Rogers, R. and Annane, B. The NASA TROPICS CubeSat constellation observatory. Conference on Earth Observation SmallSats, Houston, TX, 7-11 January 2018. American Meteorological Society, Boston, MA, 2018, Abstract J32.2. |
| 25. Wimmers, Anthony and Velden, C. Advances in visualization of global total precipitable water with morphological compositing: Innovations in 'MIMIC-TPW2'. Conference on Satellite Meteorology and Oceanography, 22nd, Houston, TX, 7-11 January 2018. American Meteorological Society, Boston, MA, 2018, Abstract 644. |