Publications & Conferences

Preprints & submitted articles

Wan, Z. Y., Lopez-Gomez, I., Carver, R., Schneider, T., Anderson, J., Sha, F., Zepeda-Núñez, L. (2024) Statistical downscaling via high-dimensional distribution matching with generative models. doi

Lopez-Gomez, I., Wan, Z. Y., Zepeda-Núñez, L., Schneider, T., Anderson, J., Sha, F. (2024) Dynamical-generative downscaling of climate model ensembles, under review. doi

Guan, Y., Hassanzadeh, P., Schneider, T., Dunbar, O., Huang, D.Z., Wu, J., Lopez-Gomez, I. (2024) Online learning of eddy-viscosity and backscattering closures for geophysical turbulence using ensemble Kalman inversion, under review. doi

Barthel Sorensen, B., Zepeda-Núñez, L., Lopez-Gomez, I., Wan, Z. Y., Carver, R., Sha, F., Sapsis, T. (2024) A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data, under review. doi

Peer-reviewed articles

Christopoulos, C., Lopez-Gomez, I., Beucler, T., Cohen, Y., Kawczynski, C., Dunbar, O. R. A., Schneider, T. (2024) Online learning of entrainment closures in a hybrid machine learning parameterization, Journal of Advances in Modeling Earth Systems, 16, e2024MS004485. doi

Eyring, V., Collins, W., …, Lopez-Gomez, I., … Zanna. L. (2024) Pushing the frontiers in climate modelling and analysis with machine learning, Nature Climate Change, 14, 916-928. doi pdf

Li, L., Carver^*, R., Lopez-Gomez^*, I., Sha, F., Anderson, J. (2024) Generative emulation of weather forecast ensembles with diffusion models, Science Advances, 10, eadk4489. doi

Lopez-Gomez, I., McGovern, A., Agrawal, S., Hickey, J. (2023) Global extreme heat forecasting using neural weather models, Artificial Intelligence for the Earth Systems, 2, e220035. doi

Dunbar^*, O. R. A., Lopez-Gomez^*, I., Garbuno-Iñigo, A., Huang, D. Z., Bach, E., Wu, J. (2022) EnsembleKalmanProcesses.jl: Derivative-free ensemble-based model calibration, Journal of Open Source Software, 7, 4869. doi

Lopez-Gomez, I., Christopoulos, C., Langeland Ervik, H. L., Dunbar, O. R. A., Cohen, Y., Schneider, T. (2022) Training physics-based machine-learning parameterizations with gradient-free ensemble Kalman methods, Journal of Advances in Modeling Earth Systems, 14, e2022MS003105. doi pdf

Chure, G., Banks, R. A., Flamholz, A. I., Sarai, N. S., Kamb, M., Lopez-Gomez, I., Bar-On, Y. M., Milo, R., Phillips, R. (2022) Anthroponumbers.org: A quantitative database of human impacts on planet Earth, Patterns, 3, 100552. doi pdf

Singer, C.E., Lopez-Gomez, I., Zhang, X., Schneider, T. (2021) Top-of-atmosphere albedo bias from neglecting three-dimensional cloud radiative effects, Journal of the Atmospheric Sciences, 78, 4053-4069. doi pdf

Lopez-Gomez, I., Cohen, Y., He, J., Jaruga, A., Schneider, T. (2020) A generalized mixing length closure for eddy-diffusivity mass-flux schemes of turbulence and convection. Journal of Advances in Modeling Earth Systems, 12, e2020MS002161. doi pdf

Cohen, Y., Lopez-Gomez, I., Jaruga, A., He, J., Kaul, C., and Schneider, T. (2020) Unified entrainment and detrainment closures for extended eddy-diffusivity mass-flux schemes. Journal of Advances in Modeling Earth Systems, 12, e2020MS002162. doi pdf

del Pozo, D., Lopez-Gomez, I., Romero, I. (2019) A robust asymmetrical contact algorithm for explicit solid dynamics. Computational Mechanics, 65, 15-32. doi pdf

Conference presentations & talks

Hybrid dynamical-generative downscaling of climate model ensembles. American Geophysical Union, Fall Meeting 2024, 9-13 December 2024, Washington, D.C. Abstract

Generative emulation of weather forecast ensembles with diffusion models. LEAP-STC, Columbia University, 25 April 2024, New York City, NY. Recording

Emulation of Weather Forecast Ensembles with Diffusion Models. American Geophysical Union, Fall Meeting 2023, 11-15 December 2023, San Francisco, CA. Abstract

Panel Discussion: How do we find new opportunities at the intersection of AI and climate tipping point research? AI Climate Tipping-Point Discovery Symposium, Association for the Advancement of Artificial Intelligence SSS-23, 27-29 March 2023, San Francisco, CA. Website

Learning to represent the physics of climate transitions as an inverse problem. AI Climate Tipping-Point Discovery Symposium, Association for the Advancement of Artificial Intelligence SSS-23, 27-29 March 2023, San Francisco, CA. Website

Enhanced Deep Learning-Based Forecasting of Extreme Heat Through Custom Exponential Losses. 22nd Conference on Artificial Intelligence for Environmental Science, American Meteorological Society Annual Meeting 2023, 8-12 January 2023, Denver, CO. Abstract

A Net-Dissipation Parameterization of Turbulence in the Atmospheric Boundary Layer. 24th AMS Symposium on Boundary Layers and Turbulence, American Meteorological Society Annual Meeting 2023, 8-12 January 2023, Denver, CO. Abstract

Unifying Turbulence and Convection Parameterizations: The Extended Eddy-Diffusivity Mass-Flux Scheme. Akio Arakawa Symposium: Modeling Convection, Clouds and Climate Systems, 17-18 October 2022, UCLA, Los Angeles, CA. Recording

Training Physics-Based Machine-Learning Parameterizations with Ensemble Kalman Methods. SIAM Mathematics of Planet Earth 2022, July 13-15 2022, Pittsburgh, PA. Website

Machine Learning Parameterizations as an Inverse Problem. Exploring the Frontiers in Earth System Modeling with Machine Learning and Big Data, Aspen Global Change Institute, June 5-10 2022, Aspen, CO. Website

Panelist at event Climate Change: Los Angeles Youth in Action, organized by the Los Angeles World Affairs Council & Town Hall (LAWACTH), Earth Day 2022, Los Angeles, CA.

Global Extreme Heat Forecasting on Subseasonal Time Scales Using Deep Learning. 21st Conference on Artificial Intelligence for Environmental Science, American Meteorological Society Annual Meeting 2022, 23–27 January 2022, Houston, TX. Website

Calibrating parameterizations with ensemble Kalman methods and high-resolution data. American Geophysical Union, Fall Meeting 2021, 13-17 December 2021, New Orleans, LA. Abstract

Predicting Extreme Heat using Physics-based AI. 3rd NOAA Workshop on Leveraging AI in Environmental Sciences, September 2021, Virtual Session. Website

Machine Learning-Based Calibration of a Unified Parameterization of Turbulence and Convection for Climate Models. SIAM Mathematics of Planet Earth 2020, Virtual Session. Abstract

Machine Learning-Based Calibration of a Unified Parameterization of Turbulence and Convection for Climate Models. ARM/ASR Machine Learning Workshop 2020, Virtual Session. Website

A Generalized Mixing Length for Eddy-Diffusivity Mass-Flux Models of Boundary Layer Turbulence and Convection. American Geophysical Union, Fall Meeting 2019, San Francisco, CA. Abstract

A Generalized Mixing Length for Eddy-Diffusivity Mass-Flux Models of Boundary Layer Turbulence and Convection. Waves, Instabilities and Turbulence in Geophysical and Astrophysical Flows (WITGAF) 2019, Cargèse, France. Website