Precipitation-buoyancy Relationships

Figure showing tropical precipitation conditionally averaged by a measure of lower-tropospheric buoyancy (B_L). The sharp increase of precipitation as a function of B_Lis seen. The probability density function (PDF) of B_L also sharply peaks on the boundary of the precipitating regime. Figure adapted from Ahmed and Neelin 2018.

Precipitation is a variable of enormous societal interest. It is also a measure of the cumulative impact of clouds in a given area, and therefore of physical and modeling interest. However, precipitation is a noisy field, discontinuous in time and space. Climate modelers have therefore looked to relate precipitation to smoother fields such as temperature and moisture.

In recent years, our group has found that combining moisture and temperature fields into a single buoyancy measure sharpens the relationship between precipitation statistics and environmental thermodynamics (Ahmed and Neelin 2018).

This precipitation-buoyancy relationship has served as an empirical parameterization of convection in intermediate complexity models (Ahmed et al. 2020, Ahmed 2021) and has been used to evaluate the thermodynamic sensitivities of convection in climate models (Ahmed and Neelin 2021).

Ongoing work in this area investigates the physical origins of the precipitation-buoyancy relationship, scale dependence and the relative impact of non-thermodynamic factors (such as wind shear) on precipitation.