Large uncertainties in the effects of changing atmospheric aerosols are among the major factors currently limiting our understanding of and ability to predict global climate changes. Among major aerosol types, mineral dust is of special interest because it causes diverse impacts on the Earth�s environment and climate that remain poorly quantified. The recent IPCC (2001) report revealed that the magnitude and even the sign of the top-of-the atmosphere direct radiative forcing caused by dust remain uncertain, whereas dust-cloud interactions were completely overlooked in the assessment of indirect radiative forcing. The urgent need to improve predictions of direct and indirect radiative forcing of atmospheric dust provides motivation for this proposal. The main goal is to gain a better understanding of the properties and spatio-temporal distribution of atmospheric dust required for improved predictions of dust radiative forcing on climate by capitalizing on the new data to be provided by the CALIPSO, CloudSat, and solar and IR passive satellite sensors of the A-Train mission. Our strategy is to perform an in-depth sensitivity study to explore the potential of the CALIPSO lidar and infrared imager in characterizing atmospheric dust and to develop a novel capability for integrating passive and active remote sensing observations of the A-Train mission in the dust-laden conditions enabling studies of dust radiative impacts as well as dust-cloud interactions. To address the goal of this proposal, we will conduct the following:
- Develop new regional dust models by incorporating recent data on the morphology (shape) and size-resolved composition (especially the new data on the iron oxide content obtained in our group) into optical modeling based on the Discrete Dipole Approximation, T-Matrix, and Mie theory approaches. A new type of regional dust models that will predict dust optical properties at both the solar and IR wavelength in a consistent fashion will be constructed.
- Perform extensive forward modeling to investigate the effects of dust particles on the scattering phase function, aerosol extinction-to-backscattering ratio, and lidar depolarization at the 532 and 1064 nm CALIPSO lidar wavelengths. Incorporate the regional dust models into the CALIPSO research retrieval algorithm and assist in the development and testing of the CALIPSO operational algorithm in the dust-laden atmospheric conditions;
- Develop a methodological framework for merging the CALIPSO lidar and infrared imager data for discrimination of dust from clouds and retrieval of the effective dust particle size; begin the analysis of dust-cloud-precipitation interactions by using CALIPSO and CloudSat observations;
- Investigate how the distinct regional properties and vertical distribution of atmospheric dust affect its radiative impacts (such as top-of-the-atmosphere and surface radiative forcing, and radiative heating and cooling rates in cloud-free and cloudy atmospheric conditions) by analyzing CALIPSO lidar and infrared imager observations in conjunction with the MM5 model coupled with the dust module, DuMo, and selected data provided by the A-Train sensors. The study will be focused on analyzing and contrasting Asian vs. Saharan dust.
Overall, our proposed research will provide deeper insights into links between the dust properties and related radiative effects and dust-cloud interaction that are critical to both remote sensing applications and climate change studies. Our research directly addresses the goals identified by the NASA NRA (ROSES NRA NNH05ZDA001N-CCST). Furthermore, our proposal contributes to the overall goals of NASA and its vision on �To understand and protect our home planet.�
