Lopez-Gomez, I., McGovern, A., Agrawal, S., Hickey, J. (2022) Global Extreme Heat Forecasting Using Neural Weather Models, submitted. arXiv
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, under review, Journal of Advances in Modeling Earth Systems. preprint
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, in press, Patterns. bioRxiv
He, J., Cohen, Y., Lopez-Gomez, I., Jaruga, A., Schneider, T. (2021) An improved perturbation pressure closure for eddy-diffusivity mass-flux schemes. preprint
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
A Net-Dissipation Parameterization of Turbulence in the Atmospheric Boundary Layer (Upcoming). 24th AMS Conference on Boundary Layers and Turbulence, 8–12 January 2023, Denver, CO.
Training Physics-Based Machine-Learning Parameterizations with Ensemble Kalman Methods (Upcoming). 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. American Meteorological Society Annual Meeting 2022, Houston, TX.
Calibrating parameterizations with ensemble Kalman methods and high-resolution data. American Geophysical Union, Fall Meeting 2021, New Orleans, LA.
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