Clouds, circulation and climate variability

Under this theme, in this round of admissions I am actively looking for motivated candidates to pursue research in - 

In climate science, climate sensitivity remains a critical metric for understanding and projecting future climate change. Since its early assessment by Charney et al. (1979), efforts to narrow its uncertainty have revealed that limitations in our understanding of clouds, circulation, and internal variability (e.g. ENSO, AMOC) are major contributors to these uncertainties. Recent advances—including our work on the global warming hiatus (Modak & Mauritsen, 2021), forcing efficacy of CH4, Black carbon aerosols, HFCs in modulating cloud feedbacks (Modak et al. 2016, Modak & Bala, 2019)—demonstrate that even subtle variations in cloud processes and circulation patterns can have profound impacts on the planet’s energy balance and hence on climate change and how it impacts us.

The scientific community has increasingly focused on constraining climate sensitivity through diverse lines of evidence such as feedback process understanding, instrumental records, paleo-climates, and emergent constraints. The latest IPCC AR6 assessment (IPCC, 2021) reflects a narrower likely range, yet the very likely range remains unchanged, underscoring the need for further research. 

In our group, we leverage instrumental records, emergent constraints, process-level studies, climate modelling and AI/ML —primarily targeting cloud feedbacks, internal variability (ENSO, AMOC, PDO, IPO, IOD etc.) and circulation dynamics—to reduce uncertainties in climate sensitivity, and improve future climate predictions and projections.

Relevant papers:

  • Huusko L, A Modak , & T. Mauritsen (2022): Stronger Response to the Aerosol Indirect Effect due to Cooling in Remote Regions, Geophysical Research Letters, https://doi.org/10.1029/2022GL101184 
  • Modak A, & T. Mauritsen (2021): The 2000–2012 global warming hiatus more likely with a low climate sensitivity. Geophysical Research Letters, https://doi.org/10.1029/2020GL091779 
  • Andrews et al. (2022): On the effect of historical SST patterns on radiative feedback, JGR Atmospheres, https://doi.org/10.1029/2022JD036675 
  • Modak, A. and Mauritsen, T. (2023): Better-constrained climate sensitivity when accounting for dataset dependency on pattern effect estimates, Atmospheric Chemistry and Physics, 23, 7535–7549, https://doi.org/10.5194/acp-23-7535-2023