ALBERT

Description: 3D aerosol-cloud interaction is examined by analyzing two images containing cumulus clouds in biomass burning regions in Brazil. The research consists of two parts. The first part focuses on identifying 3D clo ud impacts on the reflectance of pixel selected for the MODIS aerosol retrieval based purely on observations. The second part of the resea rch combines the observations with radiative transfer computations to identify key parameters in 3D aerosol-cloud interaction. We found that 3D cloud-induced enhancement depends on optical properties of nearb y clouds as well as wavelength. The enhancement is too large to be ig nored. Associated biased error in 1D aerosol optical thickness retrie val ranges from 50% to 140% depending on wavelength and optical prope rties of nearby clouds as well as aerosol optical thickness. We caution the community to be prudent when applying 1D approximations in comp uting solar radiation in dear regions adjacent to clouds or when usin g traditional retrieved aerosol optical thickness in aerosol indirect effect research.

Description: The key issue in retrieving aerosol optical thickness over land from shortwave satellite radiances is to identify and separate the signal due to scattering by a largely transparent aerosol layer from the noise due to reflection by the background surface, where the signal is relatively uniform compared to the highly inhomogeneous surface contribution. Sensitivity studies in aerosol optical thickness retrievals reveal that the apparent reflectance at the top of the atmosphere is very susceptible to the surface reflectance, especially when aerosol optical thickness is small. Uncertainties associated with surface reflectance estimation can greatly amplify the error of the aerosol optical thickness retrieval. To reduce these uncertainties, we have developed a "path radiance" method to retrieve aerosol optical thickness over land by extending the traditional technique that uses the "dark object" approach to extract the aerosol signal. This method uses the signature of the correlation of visible and mid-IR reflectance at the surface, and couples the correlation with the atmospheric effect. We have applied this method to a TM (Landsat Thematic Mapper) image acquired over the Oklahoma Southern Great Plains (SGP) site of DoE's ARM (Atmospheric Radiation Measurement) program on September 27, 1997, a very clear day during the first Landsat IOP (Intensive Observation Period). The retrieved mean aerosol optical thickness for TM band 1 at 0.49 micrometers and band 3 at 0.66 micrometers agree very well with the ground-based sun-photometer measurements at the ARM site. The ability to retrieve small aerosol optical thickness (such as 0.07 at 0.5 micrometers as in the example considered here) makes this path radiance technique promising. More importantly, the path radiance is relatively insensitive to surface inhomogeneity. The retrieved mean path radiances in reflectance units have very small standard deviations for both TM blue and red bands. This small variability of path radiance further supports the current aerosol retrieval method.

Description: Over the last two centuries, the impact of the Human System has grown dramatically, becoming strongly dominant within the Earth System in many different ways. Consumption, inequality, and population have increased extremely fast, especially since about 1950, threatening to overwhelm the many critical functions and ecosystems of the Earth System. Changes in the Earth System, in turn, have important feedback effects on the Human System, with costly and potentially serious consequences. However, current models do not incorporate these critical feedbacks. We argue that in order to understand the dynamics of either system, Earth System Models must be coupled with Human System Models through bidirectional couplings representing the positive, negative, and delayed feedbacks that exist in the real systems. In particular, key Human System variables, such as demographics, inequality, economic growth, and migration, are not coupled with the Earth System but are instead driven by exogenous estimates, such as UN population projections. This makes current models likely to miss important feedbacks in the real Earth-Human system, especially those that may result in unexpected or counterintuitive outcomes, and thus requiring different policy interventions from current models. The importance and imminence of sustainability challenges, the dominant role of the Human System in the Earth System, and the essential roles the Earth System plays for the Human System, all call for collaboration of natural scientists, social scientists, and engineers in multidisciplinary research and modeling to develop coupled Earth-Human system models for devising effective science-based policies and measures to benefit current and future generations.