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I am a Young Investigator Fellow at the Karlsruhe Institute of Technology, studying the radiative effects of tropical cirrus in the Asian monsoon region with Aiko Voigt. We are using high-resolution modeling (the ICON model) both for idealized and Lagrangian trajectory studies.

In the past few years, I have also used geostationary satellite data to study tropical organized convection and associated precipitation differentiated by El Niño phase. And I completed my thesis on multi-scale modeling of cloud ice formation, both thermodynamic nucleation and secondary production processes.


In a series of ICON model storm-resolving simulations over the Asian monsoon region, we investigated the effect of ice microphysical “switches” on the cloud-radiative heating rates and outgoing longwave radiation with results recently published in Communications Earth & Environment. We wrote a blog post for Nature Communities about the study here, and KIT and the University of Vienna wrote press releases here and here.

S. C. Sullivan and A. Voigt (2021). Ice microphysical processes exert a strong control on the simulated radiative energy budget in the tropics Comm. Earth & Env. 2 (137) doi: 10.1038/s43247-021-00206-7.

Satellite climatologies of organized convection

I have collocated ISCCP convective tracking data between 1983 and 2008 with a precipitation product (MSWEP) and synoptic conditions (ERA-Interim). From these datasets, we generated climatologies of organized convective structure, their associated precipitation, and environmental conditions in the warm and cold phases of El Niño (MCS collocation scripts). We used simple information entropy metrics to quantify proximity of convective occurrence (Entropy algorithm) and most recently used the surface energy and vertical momentum budgets to explain warm-cold phase differences in the distribution of precipitation intensities.


S. C. Sullivan, K. A. Schiro, J. Yin, and P. Gentine (2020). Change in tropical precipitation intensity with El Niño warming Geophys. Res. Lett. 47 (14) e2020GL087663.

K. A. Schiro, S. C. Sullivan, Y.-H. Kuo, H. Su, P. Gentine, G. S. Elsaesser, J. H. Jiang, and J. David Neelin (2020). Environmental controls on tropical mesoscale convective system precipitation intensity J. Atmos. Sci. doi: 10.1175/JAS-D-20-0111.1

S. C. Sullivan, K. A. Schiro, C. A. Stubenrauch, and P. Gentine (2019). The response of tropical organized convection to El Niño Warming J. Geophys. Res. 124 (15) pp. 8481–8500.

Parcel and mesoscale modeling of secondary ice production

I built a mixed-phase microphysics parcel model to describe secondary ice production processes like collisional breakup and rime splintering (SIM codes). With this idealized model, I generated estimates of the ice crystal number enhancement from secondary processes, as well as the impact of hydrometeor non-sphericity and updraft fluctuations. I later developed more sophisticated parameterizations of these processes for the COSMO metoeorological model of the German Weather Service and contributed to a review article on observations and modeling of these secondary processes.


G. Sotiropoulou, S. C. Sullivan, J. Savre, G. Lloyd, T. Lachlan-Cope, A. Ekman, and A. Nenes (2020). The impact of secondary ice production on Arctic stratocumulus. Atmos. Chem. Phys. 20 pp. 1301-1316.

S. C. Sullivan, C. Barthlott, J. Crosier, I. Zhukov, A. Nenes, and C. Hoose (2018). The effect of secondary ice production parameterization on the simulation of a cold frontal rainband Atmos. Chem. Phys. 18 pp. 16461–16480.

S. C. Sullivan, C. Hoose, A. Kiselev, T. Leisner, and A. Nenes (2018). Initiation of secondary ice production in clouds Atmos. Chem. Phys. 18 pp. 1593–1610.

P. R. Field et al. (2017). Secondary ice production: Current state of the science and recommendations for the future Meteor. Monogr. 58: 7.1-7.20.

S. C. Sullivan, C. Hoose, and A. Nenes (2017). Investigating the contribution of secondary ice production to in‐cloud ice crystal numbers J. Geophys. Res. 122 (17) pp. 9391–9412.

Sensitivity and attribution analyses for ice nucleation

Computationally efficient sensitivity and attribution analyses can be performed with automatic differentiation of parameterization codes in large-scale models. The resultant adjoint model obviates the need for finite differencing, as an output perturbation is back-propagated through to various input perturbations. I have built adjoints from the ice nucleation codes in the Community Atmosphere Model and the Goddard Earth-Observing model and used these to indentify nucleation regime shifts, quantify aerosol nucleation efficiencies, and define temporal attribution metrics.


S. Bacer, S. Sullivan, H. Tost, J. Lelieveld, and A. Pozzer (2021). Cold cloud microphysical process rates in a global chemistry-climate model Atmos. Chem. Phys. 21 pp. 1485–1505.

S. Bacer, S. Sullivan, V. A. Karydis, D. Barahona, A. Nenes, H. Tost, A. P. Tsimpidi, J. Lelieveld, and A. Pozzer (2018). Implementation of a comprehensive ice crystal formation parameterization into the EMAC model Geosci. Model Devel. 11 pp. 4021–4041.

S. C. Sullivan, D. Lee, L. Oreopoulos, and A. Nenes (2016). Role of updraft velocity in temporal variability of global cloud hydrometeor number Proc. Nat. Acad. Sci. 113 (21) pp. 5791–5796.

S. C. Sullivan, R. Morales, D. Barahona, and A. Nenes (2016). Understanding cirrus ice crystal number variability for different heterogeneous ice nucleation spectra Atmos. Chem. Phys. 16 pp.2611–2629.

B. A. Sheyko, S. C. Sullivan, R. Morales, S. L. Capps, D. Barahona, X. Shi., X. Liu, and A. Nenes (2015). Quantifying sensitivities of ice crystal number and sources of ice crystal number variability in CAM 5.1 using the adjoint of a physically based cirrus formation parameterization J. Geophys. Res. 120 (7) pp. 2834–2854.