Articles, Preprints, and Conference Papers
Articles, Preprints, and Conference Papers
| 2024 |
Discovering How Ice Crystals Grow Using Neural Ordinary Differential Equations and Symbolic Regression [preprint] K.D. Lamb and J.Y. Harrington Machine Learning for the Physical Sciences Workshop 2024 Conference on Neural Information Processing Systems |
| Spatio-Temporal Machine Learning Models for Emulation of Global Atmospheric Composition M. Erfani, K.D. Lamb, S.E. Bauer, K. Tsigaridis, M. van Lier-Walqui, G. Schmidt Tackling Climate Change with Machine Learning Workshop 2024 Conference on Neural Information Processing Systems |
|
| Simulating the Air Quality Impacts of Prescribed Fires Using Graph Neural Network‐Based PM2.5 Forecasts [preprint] K. Liao, J. Buch, K.D. Lamb, P. Gentine Under Review, Environmental Data Science (2024) |
|
| Representation of iron aerosol size distribution is critical in evaluating atmospheric soluble iron input to the ocean [link] M. Liu, H. Matsui, D. Hamilton, S. Rathod, K.D. Lamb, N. Mahowald. Atmospheric Chemistry and Physics, 24, 13115-13127 (2024) |
|
| Reduced Order Modeling for Linearized Representations of Microphysical Process Rates [link] K.D. Lamb, M. van Lier Walqui, S.P. Santos, H. Morrison. Journal of Advances in Modeling Earth Systems, 16, 7 (2024) |
|
| 2023 |
Zero‐Shot Learning of Aerosol Optical Properties Using Graph Neural Networks [link] K.D. Lamb, P. Gentine. Scientific Reports 13, 18777 (2023) |
| Simulating the Air Quality Impacts of Prescribed Fires Using a Graph Neural Network‐Based PM2.5 Forecasting System [link] K. Liao, J. Buch, K.D. Lamb, P. Gentine Tackling Climate Change with Machine Learning Workshop 2023 Conference on Neural Information Processing Systems |
|
| Understanding and Visualizing Droplet Distributions in Simulations of Shallow Clouds with Variational Autoencoders [link] J. Will, A. Jenney, K.D. Lamb, M.S. Pritchard, C. Kaul, P-L Ma, K. Pressel, J. Shpund, M. van Lier Walqui, S. Mandt Machine Learning and the Physical Sciences Workshop 2023 Conference on Neural Information Processing Systems |
|
| Pyrocumulonimbus affect average stratospheric aerosol composition [link] J.M Katich, E. Apel, I. Bourgeois, C. Brock, T.P. Bui, P. Campuzano-Jost, R. Commane, B. Daube, M. Dollner, M. Fromm, K.D. Froyd, A.J. Hills, R.S. Hornbrook, J. Jimenez, A. Kupc, K.D. Lamb, K. McKain, F. Moore, D.M. Murphy, B.A. Nault, J. Peischl, D.A. Peterson, E.A. Ray, K.H. Rosenlof, T. Ryerson, G.P. Schill, J.C. Schroder, B. Weinzierl, C. Thompson, C.J. Williamson, S. Wofsy, P. Yu, J.P. Schwarz. Science, 379, 6634 (2023) |
|
| Implicit Learning of Convective Organization Explains Precipitation Stochasticity [link] S. Shamekh, K.D. Lamb, Y. Huang, P. Gentine. Proceedings of the National Academy of Sciences, 120(20)e2216158120 (2023) |
|
| Re-evaluating cloud chamber constraints on depositional ice growth in cirrus clouds-- Part 1: Model description and sensitivity tests [link] K.D. Lamb, J. Harrington, B.W. Clouser, E.J. Moyer, L. Sarkozy, V. Ebert, O. Möhler, H. Saathoff. Atmospheric Chemistry and Physics, 23, 6043-6064 (2023) |
|
| Airborne Bioaerosol Observations Imply a Strong Terrestrial Source in the Summertime Arctic [link] A. Perring, B. Mediavilla, G. Wilbanks, J. Churnside, R. Marchbanks, K.D. Lamb, R. Gao. Journal of Geophysical Research: Atmospheres , 128, e2023JD039165 (2023) |
|
| 2022 |
Identifying the Causes of Pyrocumulonimbus (PyroCb) [link] E. Diaz Salas‐Porras, K. Tazi, A. Braude, D. Okoh, K.D. Lamb, D. Watson‐Parris, P. Harder, N. Meinert Workshop on Causality for Real‐world Impact (CML4Impact 2022) 2022 Conference on Neural Information Processing Systems |
| Pyrocast: a Machine Learning Pipeline to Forecast Pyrocumulonimbus (PyroCb) clouds [link] K. Tazi, E. Diaz Salas‐Porras, A. Braude, D. Okoh, K.D. Lamb, D. Watson‐Parris, P. Harder, N. Meinert Tackling Climate Change with Machine Learning Workshop 2022 Conference on Neural Information Processing Systems |
|
| The under‐appreciated role of anthropogenic sources in atmospheric soluble iron flux to the Southern Ocean. [link] M. Liu, H. Matsui, D.S. Hamilton, K.D. Lamb, S.D. Rathod, J.P. Schwarz, N.M. Mahowald. npj Climate and Atmospheric Science 5, 28 (2022) |
|
| 2021 |
Complex refractive indices in the ultraviolet and visible spectral region for highly absorbing non‐spherical biomass burning aerosol [link] C.C. Womack, K.M. Manfred, N.L. Wagner, G. Adler, A. Franchin, K.D. Lamb, A.M. Middlebrook, J.P. Schwarz, C.A. Brock, S.S. Brown, R.A. Washenfelder. Atmospheric Chemistry and Physics, 21, 7235-7252 (2021) |
| Temporal and spatial variations of aerosol optical properties over the Korean peninsula during KORUS‐AQ [link] C.Y. Choi, Y.S. Ghim, M. Segal‐Rozenhaimer, J. Redemann, S.E. LeBlanc, Y. Lee, T. Lee, T. Park, J.P. Schwarz, K.D. Lamb, C.J. Flynn, R.J. Johnson, A.E. Perring Atmospheric Environment, 118301, ISSN 1352‐2310 (2021) |
|
| Global‐scale constraints on light‐absorbing anthropogenic iron oxide aerosols [link] K.D. Lamb, H. Matsui, J. Katich, A.P. Perring, J.R. Spackman, B. Weinzerl, M. Dollner, J.P.Schwarz npj Climate and Atmospheric Science, 4, 15 (2021) |
|
| Light‐absorption enhancement of black carbon in the Asian outflow: Airborne SP2 observations during KORUS‐AQ [link] C. Cho, J.P. Schwarz, A.E. Perring, K.D. Lamb, Y. Kondo, J.U. Park, D.H. Park, K. Shim, J.S. Park, R.J. Park, M. Lee, C.K. Song, S.W. Kim Science of the Total Environment, Jun 15, Vol. 773, 145531 (2021) |
|
| 2020 |
Investigation of Factors Controlling PM2.5 Variability across the South Korean peninsula during KORUS‐AQ [link] C.E. Jordan, J.H. Crawford, A.J. Beyersdorf, T.F. Eck, H.S. Halliday, B.A. Nault, L.‐S. Chang, R. Park, G. Lee, H. Kim, S. Cho, H.J. Shin, J.H. Lee, J. Jung, D.S. Kim, M. Lee, T. Lee, A. Whitehall, J. Szykman, M.K. Schueneman, P. Campuzano‐Jost, J.L. Jimenez, J.P. DiGangi, G.S. Diskin, B.E. Anderson, R.H. Moore, L.D. Ziemba, M.A. Fenn, J.W. Hair, R.E. Kuehn, R.E. Holz, G. Chen, K. Travis, M. Shook, D.A. Peterson, K.D. Lamb, J.P. Schwarz Elementa: Science of the Anthropocene, 8 (2020) |
| The Lab Chicago Water Isotope Spectrometer: a tunable diode laser spectrometer for chamber‐based measurements of water vapor isotopic evolution during cirrus formation
[link] L. Sarkozy, B.W. Clouser, K.D. Lamb, E. Stutz, H. Saathoff,O. Möhler, S.Wagner, V. Ebert, B. Kühnreich, E.J. Moyer Review of Scientific Instruments, 91, 4 (2020) |
|
| Understanding and improving model representation of aerosol optical properties for a Chinese haze event measured during KORUS‐AQ [link] P.E. Saide, M. Gao, Z. Lu, D. Goldberg, D.G. Streets, J.‐H. Woo, A. Beyersdorf, C. Corr, K.L. Thornhill, B. Anderson, J.W. Hair, A.R. Nehrir, G.S. Diskin, J.L. Jimenez, B.A. Nault, P. Campuzano‐Jost, J. Dibb, E. Heim, K.D. Lamb, J.P. Schwarz, A.E. Perring, J. Kim, M. Choi, B. Holben, G. Pfister, A. Hodzic, G.R. Carmichael, L. Emmons, J.H. Crawford Atmospheric Chemistry and Physics, 20, 11, 6455‐6478 (2020) |
|
| No anomalous supersaturation in ultracold cirrus laboratory experiments [link] B. Clouser, K.D. Lamb, L. Sarkozy, A. Nisenoff, J. Habig, V. Ebert, H. Saathoff, O. Möhler, E.J. Moyer Atmospheric Chemistry and Physics, 20, 2, 1089‐1103 (2020) |
|
| 2019 |
A deep learning approach for classifying black carbon aerosol morphology K.D. Lamb Tackling Climate Change with Machine Learning Workshop 2019 Conference on Neural Information Processing Systems |
| Prediction of GNSS Phase Scintillations: A Machine Learning Approach [link] K.D. Lamb*, G. Malhotra*, A. Vlontzos*, E. Wagstaff*, A.G. Baydin, A. Bhiwandiwalla, Y. Gal, A. Kalaitzis, A.Reina, A. Bhatt (*equal contributions) Machine Learning and the Physical Sciences Workshop 2019 Conference on Neural Information Processing Systems |
|
| Correlation of Auroral Dynamics and GNSS Scintillation with an Auto‐encoder [link] K.D. Lamb*, G. Malhotra*, A. Vlontzos*, E. Wagstaff*, A.G. Baydin, A. Bhiwandiwalla, Y. Gal, A. Kalaitzis, A.Reina, A. Bhatt (*equal contributions) Machine Learning and the Physical Sciences Workshop 2019 Conference on Neural Information Processing Systems |
|
| Classification of iron oxide aerosols with a single particle soot photometer using supervised machine learning [link] K.D. Lamb Atmospheric Measurement Techniques, 12, 3885‐3906 (2019) |
|
| Evidence in biomass burning smoke for light‐absorbing aerosol with properties intermediate between black and brown carbon [link] G. Adler, N. Wagner, K.D. Lamb, K. Manfred, J.P. Schwarz, A. Franchin, A. Middlebrook, R. Washenfelder, C. Womak, R. Yokelson, D. Murphy Aerosol Science and Technology, p. 976‐989 (2019) |
|
| Inter‐comparison of black carbon measurement methods for simulated open biomass burning emissions [link] H. Li, K.D. Lamb, J. Schwarz, V. Selimovic, R. Yokelson, G. McMeeking, A. May Atmospheric Environment, Vol. 206, p.156‐169 (2019) |
|
| 2018 |
Secondary organic aerosol production from local emissions dominates the organic aerosol budget over Seoul, South Korea, during KORUS‐AQ [link] B. Nault, P. Campuzano‐Jost, D. Day, J. Schroder, B. Anderson, A. Beyersdorf, D. Blake, W. Brune, Y. Choi,C. Corr, J. de Gouw, J. Dibb, J. DiGangi, G. Diskin, A. Fried, L.G. Huey, M. Kim, C. Knote, K.D. Lamb, T. Lee, T. Park, S. Pusede, E. Scheuer, K. Thornhill, J.‐H. Woo, and J. Jimenez Atmospheric Chemistry and Physics, 18, 24, 17769-17800 (2018) |
| Estimating Source Region Influences on Black Carbon Abundance, Microphysics, and Radiative Effect Observed Over South Korea [link] K.D .Lamb, A. Perring, B. Samset, D. Peterson, S. Davis, B. Anderson, A. Beyersdorf, D. Blake, P. Campuzano‐Jost, C. Corr, G. Diskin, Y. Kondo, N. Moteki, B. Nault, J. Oh, M. Park, S. Pudede, I. Simpson, K. Thornhill, A. Wisthaler, J.P. Schwarz Journal of Geophysical Research: Atmospheres, 123(23): 13527‐13548 (2018) |
|
| Investigating biomass burning aerosol morphology using a laser imaging nephelometer [link] K.M. Manfred, R.A. Washenfelder, N.L. Wagner, G. Adler, F. Erdesz, C.C. Womack, K.D. Lamb, J.P. Schwarz, A. Franchin, and V. Selimovic Atmospheric Chemistry and Physics, 18, 3, 1879-1894 (2018) |
|
| 2017 |
Laboratory measurements of HDO/H2O isotopic fractionation during ice deposition in simulated cirrus clouds [link] K.D. Lamb, B.W. Clouser, M. Bolot, L. Sarkozy, V. Ebert, H. Saathoff, O. Möhler, E.J. Moyer Proceedings of the National Academy of Sciences, 114(22):5612–5617 (2017) |
| earlier |
Unitary and nonunitary approaches in quantum field theory [link] K.D. Lamb, C.C. Gerry, Q. Su, R. Grobe Physical Review A, 75(1):013425 (2007) |
| Non‐perturbative retrieval of the scattering strength in one‐dimensional media [link] K.D. Lamb, S. Menon, Q. Su, R. Grobe Physical Review E, 74(6):061903 (2006) |
Media and Press
We’re finally solving the puzzle of how clouds will affect our climate, New Scientist, September (2024) [link]
How AI Could Power the Climate Breakthroughs the World Needs, CNN, November (2023) [link]
Towering Wildfire Clouds Are Affecting the Stratosphere, and the Climate, State of the Planet, February (2023) [link]
Can Climate Models Aid Adaptation Efforts with Help from A.I.?, Sustain What? Webcast, December (2022) [link]
How Studying the Clouds Can Improve Climate Models, State of the Planet, November (2022) [link]
DOE Awards $14 Million to Improve Climate Change Predictions (2022) [link]
Human‐made iron inputs to the Southern Ocean ten times higher than previously estimated. EurekaAlert! AAAS, May (2022) [link]
Aerosols and their Role in Climate (2021) [link]
New spectrometer measures water vapor isotopic evolution in cirrus clouds. AIP SciLight (2020) [link]
NASA flies low over South Korea to measure polluted air, CNN, June (2016) [link]
On board NASA’s flying lab over South Korea, CNN, June (2016) [link]