SDM meets Isotopes
Modelling isotopic signatures in precipitation using particle-based cloud microphysics
We model the evolution of isotopic composition of water droplets and ambient vapour. Our focus is on stable water isotopologues: H2O, HDO, H218O, H217O. Among considered processes are the diffusional and collisional growth/breakage of droplets and the concurrent isotopic kinetic fractionation.
We use the Lagrangian particle-based approach for modelling cloud microphysics. Particle-resolved formulation, using the so-called super-droplet Monte-Carlo method, offers a uniquely suitable framework for simulating the isotopic fractionation in clouds and precipitation. This is due to the ability to represent, with high fidelity, the dynamics of particles in a multidimensional space of attributes.
Among the attributes of super-particles are such extensive quantities as mass of water per droplet, and the multiplicity, i.e. the number of real-world particles represented by a computational super-particle. In this project, the set of attributes is extended to include: moles of deuterium (D), oxygen-17 (17O), and oxygen-18 (18O). The evolution in time of a droplet water isotopic composition is driven by kinetically limited diffusion processes (condensation, evaporation, deposition, sublimation), and is further modulated by collision-triggered coalescence and breakage.
Defining and prototyping a new model of the above phenomena, we use PySDM - a Python particle-based cloud microphysics package developed and maintained in our group.
Our objective is to create a novel tool enabling:
- usage of isotopic composition data to constrain the unknown aspects of cloud microphysical processes such as evolution of supersaturation, turbulent mixing, and formation of hydrometeors;
- improvements in methods for inferring atmospheric thermodynamic state from meteoric water isotopic composition data (e.g., from ice cores).
🎓 Student project opportunities
- Extending PySDM to explicitly resolve droplet heat budget and thus capture non-equilibrium drop temperature (as an alternative to the current equilibrium approximation).
Acknowledgement
This project received support from Polish National Science Centre (SONATA grant no. 2020/39/D/ST10/01220) and the Excellence Initiative – Research University programme at the AGH University of Krakow (priority research area: Water-Energy-Climate).
Contributors from our team
Agnieszka Żaba
