Invariance in convective storms with warming: A Lagrangian view

Changes in tropical precipitation, particularly extremes, are closely linked to mesoscale deep convective systems (DCSs). While previous work has largely focused on precipitation characteristics, much less is known about how the DCSs which produce extreme rainfall respond to warming. Recent studies showed that the Lagrangian perspective offered by storm tracking in satellite imaging was promising. Here, we exploit two models (SAM and MesoNH) of idealised tropical convection from the RCEMIP project, on which the TOOCAN DCS tracking algorithm has been applied, to study DCSs life cycles in an idealised setup. Focusing on their onset rate, lifetime, area and precipitation intensity, we show that despite the relatively small increase in domain-mean precipitation (+2.5 %/K), the characteristics of DCSs change much more with warming, but their respective responses mostly compensate. Mean DCS precipitation intensity increases in both SAM (+10 %/K) and MesoNH (+2.3 %/K). However, the two models predict strong but opposite responses in DCS area and onset rate—increased area (+8.0 %/K) and lower onset rate (–13 %/K) in SAM, the opposite in MesoNH (–4.2 %/K and +7.4 %/K, respectively). This may be related to their different organisation response to warming. Yet, we find that the probability density functions (PDFs) of DCS lifetime, area and precipitation intensity normalised by their respective ensemble average over all DCSs, are climate and model invariant: the PDF of each of these variables is identical in both the colder and the warmer simulation, in both SAM and MesoNH. If confirmed, such a climate invariance could fuel further research about the physical mechanisms of extreme storms response to warming.