THE EFFECTS OF GREENHOUSE GASES AND ABSORBING AEROSOLS ON TROPICAL PRECIPITATION

Abstract

Greenhouse gases and absorbing aerosols warm the climate system by absorbing radiation. At the same time, aerosol particles also have the potential to significantly alter cloud microphysics. This thesis explores the hydrological implications of the radiative and

microphysical perturbations using cloud-resolving model (CRM) and global

climate model (GCM) simulations.

Absorption from greenhouse gases and absorbing aerosols heats the atmosphere on the fast time scales of days to months, thereby reducing mean precipitation. It is identified using CRM simulations in radiative-convective equilibrium (RCE) that the reduction mainly comes from weak, rather than strong, precipitation events. The intensity of strong events is maintained by a compensation between an increase in boundary layer moisture and a reduction in updraft frequency.

An often-cited hypothesis in aerosol-cloud interactions is that increased cloud droplet number

concentrations allows more cloud water to be lofted above the freezing

level, releasing additional latent heat that invigorates convection. Our

RCE experiments show that ice processes are not necessary for convective

invigoration, with the evaporation of cloud droplets playing a more

important role.

To address the effects of spatial inhomogenity of aerosol

distributions on extreme events, we investigate the effect of different

spatial distributions of black carbon aerosols on tropical cyclone (TC)

statistics on fast time scales using the Geophysical Fluid Dynamics

Laboratory (GFDL) GCM HiRAM. Free-tropospheric

black carbon is much more effective than boundary layer black carbon in

altering TC statistics. The atmospheric heating of BC leads to larger

reductions in TC intensity as compared to carbon dioxide.

In boreal winter, the cold surges associated with the movements of the

Siberian high contribute significantly to mean and extreme precipitation

over the Maritime Continent. Using simulations from the GFDL AM4, we

predict increases in surge precipitation under surface warming. The increase in

surge precipitation is amplified under a more realistic spatial

pattern of warming.

The physical understanding obtained by the combination of theory and models in this thesis serve as a guide for policymakers in planning for rainfall under a changing climate.