Comment on egusphere-2025-6266

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Authors: Ellen Davenport, J. Varan Madan, Rebecca Gjini, Jared Brzenski, Nick Ho, Tien‐Yiao Hsu, Yueshan Liang, Zhixing Liu, Veeramakali Manivannan, Eric Pham, Rohith Vutukuru, Williams, Andrew I. L.
+5 more Zhiqi Yang, Rose Yu, Nicholas J. Lutsko, Stephan Hoyer, Duncan Watson‐Parris
Cited by: 0

Abstract

Abstract. In this paper we present version 1.0 of the JAX Circulation Model (JCM). JCM is an open-source, differentiable atmospheric model built in Python using the JAX numerical library. Earth system modeling is rapidly evolving, particularly through hybrid approaches that combine known dynamics with data-driven components. However, the training and validation of hybrid methods in traditional models remain difficult due to the absence of gradients and the complexity of legacy code. Differentiable models written in modern frameworks offer a path forward. JCM couples physics parameterizations to the Dinosaur dynamical core through a flexible interface that makes substitution of other schemes easy. The default parameterization scheme uses the SPEEDY (Simplified Parameterizations, primitivE-Equation DYnamics) intermediate-complexity physics scheme. This modularity supports benchmarking across physical and machine-learned schemes, with direct access to gradients for sensitivity analysis, calibration, and online learning. We show validation of JCM against the original Fortran SPEEDY code at T31 resolution. We also highlight JCM's differentiability and efficiency and outline plans for extending the framework to a differentiable Earth system model. JCM provides a lightweight yet expressive platform for accelerating research in climate modeling.

Fields of Study & Subjects

Meteorological Phenomena and Simulations Climate variability and models Oceanographic and Atmospheric Processes

Publication details

Publication date
6 February 2026