Tamas Varnai

University of Maryland-JCET

Some of the largest uncertainties in understanding human impacts on climate arise from difficulties in quantifying the effects of atmospheric aerosols on solar radiation and clouds. A better understanding of these effects will require accurate calculations of solar heating and accurate measurements of aerosol and cloud properties. The three-dimensional (3D) nature of radiative processes can create challenges such as accommodating computational demands and specifying necessary inputs—and as a result, both climate simulations and satellite data interpretation methods use one-dimensional (1D) radiation models that treat each atmospheric column separately, without considering their interactions.

The presentation will first discuss solar heating calculations for a multiyear dataset of clouds observed at three Department of Energy sites. These calculations indicate that horizontal radiative interactions cause 1D radiation models to underestimate average solar heating by a few W/m2. The talk will next present CALIOP and MODIS satellite data in examining atmospheric particles and 3D radiative processes near clouds. The results indicate that clouds are surrounded by a wide transition zone of increased particle size, enhanced light scattering, and significant 3D radiative interactions. The talk will also outline some possibilities for considering 3D radiative interactions in remote sensing applications.