BibTeX
@ARTICLE{
         Hieronymus2025Stc,
       title = "Spatio-temporal consistency of cloud-microphysical parameter sensitivity in a
         warm-conveyor belt",
       journal = "Journal of Computational Science",
       volume = "89",
       pages = "102614",
       year = "2025",
       issn = "1877-7503",
       doi = "10.1016/j.jocs.2025.102614",
       author = "Maicon Hieronymus and Annika Oertel and Annette K. Miltenberger and
         Andr{\'e} Brinkmann",
       keywords = "Sensitivity analysis, Warm conveyor belt, Cloud microphysics",
       abstract = "A good representation of clouds and precipitation processes is essential in
         numerical weather and climate models. Subgrid-scale processes, such as cloud physics, are
         parameterized and inherently introduce uncertainty into models. Traditionally, the sensitivities of
         the model state to specific uncertain parameters are quantified through perturbations to a few
         selected parameters, limited by computational resources. Algorithmic Differentiation (AD) enables
         the efficient and simultaneous estimation of sensitivities for a large number of parameters, thereby
         overcoming the previous limitations and significantly enhancing the efficiency of the analysis. This
         framework provides an objective way to identify processes where more precise representations have
         the largest impact on model accuracy. AD-estimated sensitivities can also address the
         underdispersiveness of perturbed ensemble simulations by guiding the parameter selection or the
         perturbation itself. In our study, we applied AD to 169 uncertain parameters identified in the
         two-moment microphysics scheme of the numerical weather prediction (NWP) model ICON of the German
         Weather Service. This application of AD allowed us to evaluate the sensitivities of specific
         humidity, latent heating, and latent cooling along several thousand warm conveyor belt trajectories.
         This coherent, strongly ascending Lagrangian flow feature is crucial for the cloud and precipitation
         structure and the evolution of extratropical cyclones. The quantification of individual parameter
         sensitivities shows that only 38 parameters are of primary importance for the investigated model
         state variables. These parameters are associated with rain evaporation, hydrometeor diameter-mass
         relations, and fall velocities. Moreover, the parameter sensitivities systematically vary with
         different microphysical regimes, ascent behavior, and ascent stages of the WCB airstream. Finally,
         several parameters impact an extended region in the extratropical cyclone, illustrating the
         spatiotemporal consistency of cloud microphysical parameter uncertainty in the applied NWP model and
         microphysics scheme.",
       ad_area = "Climate Modeling",
       ad_tools = "CoDiPack"
}