Back to square one (again and again): Finding a bug in a complex global atmospheric model

In atmospheric sciences, a central tool to test hypotheses are numerical models, which aim to represent (part of) our environment. One such model is the weather and climate model ICON [1], which solves the Navier-Stokes equation for capturing the dynamics and parameterizes subgrid-scale processes, such as radiation, cloud microphysics, and aerosol processes. Specifically, for the latter exists the so-called Hamburg Aerosol Module (HAM [2]), which is coupled to ICON [3] and predicts the evolution of aerosol populations using two moments (mass mixing ratio and number concentration). The high complexity of aerosols is reflected in the number of aerosol species (total of 5), number of modes (total of 4), and their mixing state and solubility. The module calculates aerosol composition and number concentration, their optical properties, their sources and sinks, and their interactions with clouds via microphysical processes. Aerosol emissions are sector-specific and based on global emission inventories or dynamically computed.

Within our work, we stumbled upon an interesting pattern occurrence in our simulations upon changing/turning off single emission sectors. If we, e.g., removed black carbon from aircraft emissions, the strongest changes emerged over the African continent, which is not the region where we were expecting to see the strongest response. Further investigations revealed that this pattern emerges independently of the emission sector as well as species, confirming our suspicion that we are facing a bug within HAM. Here, we want to present how we approached the challenge of identifying and tackling a bug within a complex module with several thousand lines of code.

 

[1] G. Zängl, D. Reinert, P. Ripodas, and M. Baldauf, “The ICON (ICOsahedral Non-hydrostatic) modelling framework of DWD and MPI-M: Description of the non-hydrostatic dynamical core,” Quarterly Journal of the Royal Meteorological Society, vol. 141, no. 687, pp. 563–579, 2015, ISSN: 1477-870X. DOI: 10.1002/qj.2378

[2] P. Stier, J. Feichter, S. Kinne, S. Kloster, E. Vignati, J. Wilson, L. Ganzeveld, I. Tegen, M. Werner, Y. Balkanski, M. Schulz, O. Boucher, A. Minikin, and A. Petzold, “The aerosol-climate model ECHAM5-HAM,” Atmospheric Chemistry and Physics, 2005. DOI: 10.5194/acp-5-1125-2005

[3] M. Salzmann, S. Ferrachat, C. Tully, S. M¨ unch, D. Watson-Parris, D. Neubauer, C. Siegenthaler-Le Drian, S. Rast, B. Heinold, T. Crueger, R. Brokopf, J. Mülmenstädt, J. Quaas, H. Wan, K. Zhang, U. Lohmann, P. Stier, and I. Tegen, “The Global Atmosphere-aerosol Model ICON-A-HAM2.3–Initial Model Evaluation and Effects of Radiation Balance Tuning on Aerosol Optical Thickness,” Journal of Advances in Modeling Earth Systems, vol. 14, no. 4,e2021MS002699, 2022, ISSN: 1942-2466. DOI: 10.1029/2021MS002699