Andrew Geiss Headshot


PhD Atmospheric Sciences -- University of Washington (2020)
MS Applied Mathematics -- University of Washington (2019)
MS Atmospheric Sciences -- University of Washington (2016)
BS Applied Computational Mathematics in Science -- University of Washington (2012)
BS Atmospheric Sciences, Atmospheric Chemistry -- University of Washington (2012)


2022-Present: Data Scientist, PNNL, Richland, Washington
2020-2021: Postdoctoral Research Associate, PNNL, Richland, Washington
2013-2020: Research Assistant, University of Washington, Seattle, Washington
2007-2013: Research Assistant, NorthWest Research Associates, Redmond, Washington

Peer Reviewed Publications

Geiss, A., Ma, P.-L., Singh, B., and Hardin, J. C.: Emulating Aerosol Optics with Randomly Generated Neural Networks, EGUsphere, (preprint - in review),, 2022.
Geiss, A., Silva, S., and Hardin, J.: Downscaling Atmospheric Chemistry Simulations with Physically Consistent Deep Learning, Geosci. Model Dev. Discuss., (preprint - accepted),, 2022.
Geiss, A. and Hardin, J. C.: Inpainting radar missing data regions with deep learning, Atmos. Meas. Tech., 14, 7729–7747,, 2021.
Geiss, A. and Hardin, J. C. (2020) Strict Enforcement of Conservation Laws and Invertibility in CNN-Based Super Resolution for Scientific Datasets arXiv, (preprint - in review),
Geiss, A. and Hardin, J. C. (2020) Radar Super Resolution using a Deep Convolutional Neural Network. Journal of Atmospheric and Oceanic Technology, 37-12: 2197-2207,
Geiss, A., Marchand, R., and Thompson, L. (2020) The Influence of Sea Surface Temperature Reemergence on Marine Stratiform Cloud. Geophysical Research Letters,
Geiss, A. and Marchand, R. (2019) Cloud responses to climate variability over the extratropical oceans as observed by MISR and MODIS. Atmospheric Chemistry and Physics,
Geiss, A., and Mahrt, L. (2015) Decomposition of Spatial Structure of Nocturnal Flow over Gentle Terrain. Boundary Layer Meteorology, 156-3: 337-347,
Geiss, A., and Levy, G. (2012) The use of automated feature extraction for diagnosing double inter-tropical convergence zones. Computers & Geosciences, 46:73-76,
Levy, G., Geiss, A., Kumar, M-R. (2011) Near-Equatorial Convective Regimes over the Indian Ocean as Revealed by Synergistic Analysis of Satellite Observations. Advances in Geosciences, 22: 101-114,


Geiss, A., Hardin, J. C., Silva, S., Gustafson, W. I., Varble, A., and Fan, J. (2020) Deep Learning for Ensemble Forecasting. (DOE White Paper),
Geiss, A., and Hardin J. C. (2021) Papers of Note: Radar Super Resolution with Deep Learning. (Paper Highlight), Bulletin of the American Meteorological Society, 102-2: 100-101
Geiss, A. (2020) Observed and Modeled Cloud Responses to Climate Variability. (PhD Thesis), University of Washington, University of Washington Libraries
Geiss, A. (2016) Multi-year Trends in MODIS and MISR Observed Cloud Fraction over the Extratropical Oceans. (M.S. Thesis), University of Washington, University of Washington Libraries