This research team will formulate and apply a simplified numerical model to explore conditions favoring the self-aggregation of moist atmospheric convection. Aggregation of cumulus convection into clumps containing many individual convective cells is prominent in nature and in full-physics numerical atmospheric simulations alike. The researchers have performed preliminary analyses using the System for Atmospheric Modeling (SAM) numerical model, and will expand upon these simulations in order to address the hypothesis that self-aggregation of convection will lead to a systematic decline in the surface temperature, and that such decline may in-turn lead to disaggregation of convection and restorative re-warming of the surface. As such, the system would naturally be attracted to the phase transition between aggregated and disaggregated states and would constitute an example of a self-organized critical system. The objectives of the proposed work are to: (1) understand the physics of self-aggregation, (2) determine how much hysteresis there is in the system, (3) determine whether radiative-convective equilibrium systems with surface energy balance are subject to self-organized criticality, and (4) understand the implications of these aforementioned factors upon climates predicated on idealized radiative-convective states as well as more real-world conditions.
The intellectual merit of the work derives from improved basic understanding of mechanisms influencing moist atmospheric convection, which is a critical but nonetheless not fully understood component of the climate system. A confirmation of the hypothesis that tropical climate tends toward a state of self-organized criticality could substantially advance the understanding of the interrelationship between convection and climate.
The broader impacts of the study include the education and training of a graduate student at each of two collaborative institutions. The work also has potential to lead to improved representations of convection via improved parameterizations suitable for incorporation into coupled climate models, which could in turn contribute to improved climate forecasts.
The Earth’s climate is strongly affected by water vapor, which is a greenhouse gas and which also controls the activity of clouds, which reflect sunlight to space and which also act as greenhouse agents, absorbing infrared radiation and re-emitting some of it back to the surface. We know from observations that the distribution of water vapor is very complex, and also varies greatly in time. The source of water vapor is the earth’s surface: oceans, lakes, and wet land surfaces. Turbulence in the atmosphere carries water vapor up a few thousand feet. But water vapor is transported much higher up into the atmosphere by deep cumulus clouds, such as thunderstorms, and the physics of those clouds controls how much water is put into the atmosphere versus coming back down as rain or snow. Since the real earth is very complicated, we try first to understand idealized climate states, one of which is called "radiative-convective equilibrium", or "RCE". This is just a hypothetical climate over an ocean of infinite horizontal extent, above which only radiation (both solar and terrestrial) and convection (cumulus clouds) are the only processes that transport energy through the atmosphere, and convection is the only process that transports water. In recent decades, we have been able to simulate such states over small chunks of the ocean using very powerful computers. When we first started doing this, we saw pretty much what we expected to see… random cumulus clouds developing and decaying, a bit like watching boiling water. But about ten years ago, during one such simulation, all the convection grouped together into one massive clump, which stayed around for as long as the simulation was run. Since then, other researchers have replicated this process, which has become known as "self-aggregation". My colleague Marat Khairoutdinov and I discovered that whether this happens or not depends, among other things, on how warm the underlying sea surface is. This NSF grant enabled us finally to unlock the key physical processes that lead to self-aggregation, and we explained clearly why the process depends on the sea surface temperature. We think that aggregation of convection also occurs in nature, and because it dries out the atmosphere profoundly, it might act as a tropical climate regulator. A drier atmosphere has a weaker greenhouse effect, so it cools. Along the way, we decided to see what happens if we repeated the experiments but this time on a rotating planet. (The earlier work was done on a nonrotating planet.) The aggregation, in this case, takes the form of hurricanes, and we were able to discover what precisely controls their size, their spacing, and their peak wind speeds. This may yield clues to how and why hurricanes form in nature, and how they might depend on the state of the climate.
