Publication: THE EFFECTS OF GREENHOUSE GASES AND ABSORBING AEROSOLS ON TROPICAL PRECIPITATION
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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.