referred to as the solar albedo effect (SAE), results in a cooling component of the
earth-atmosphere system. At the same time, clouds trap thermal radiation emitted
to space, referred to as the greenhouse effect (GE). The competition of SAE and GE
with respect to earth’s climate system is regulated by cloud cover, vertical position
of different cloud types, thermodynamic phases, liquid/ice water content, and particle
size distribution. Low, middle, and vertically convective clouds are primarily
controlled by SAE; however, the role of high and thin clouds is not well understood
due to observational limitations from the ground, the air, and space. Thus, I should
largely confine my talk to ice clouds and radiative interactions for applications to
climate models. Due to computational requirements, interactions of radiation and ice
cloud macro- and micro-physics must be parameterized. Exact solutions for both
radiative transfer and cloud physics based on first principle could be accomplished
offline to complement ice-cloud model development. I will provide a number of
examples within the context of parameterization. Notwithstanding to complicate the
presentation, I will also discuss additional examples to illustrate the importance of
aerosol-ice interactions with respect to the formation of high-level clouds in climate
models for radiative forcing and feedback studies. Subsequently, I will show recent
progress using existing A-train datasets for ice clouds and climate research. Despite
this progress, new satellite observations for the vertical profile of ice-crystal size
distribution and related precipitation appear necessary to make a quantum advance
in the climate model performance in terms of validation and calibration to resolve the
role of ice clouds and aerosols in radiation fields as well as to reduce uncertainties in
climate simulations.
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