Showing papers by "Andrew A. Lacis published in 2010"

Atmospheric CO2: Principal Control Knob Governing Earth’s Temperature

Abstract: Ample physical evidence shows that carbon dioxide (CO(2)) is the single most important climate-relevant greenhouse gas in Earth's atmosphere. This is because CO(2), like ozone, N(2)O, CH(4), and chlorofluorocarbons, does not condense and precipitate from the atmosphere at current climate temperatures, whereas water vapor can and does. Noncondensing greenhouse gases, which account for 25% of the total terrestrial greenhouse effect, thus serve to provide the stable temperature structure that sustains the current levels of atmospheric water vapor and clouds via feedback processes that account for the remaining 75% of the greenhouse effect. Without the radiative forcing supplied by CO(2) and the other noncondensing greenhouse gases, the terrestrial greenhouse would collapse, plunging the global climate into an icebound Earth state.

Attribution of the present-day total greenhouse effect

Abstract: [1] The relative contributions of atmospheric long-wave absorbers to the present-day global greenhouse effect are among the most misquoted statistics in public discussions of climate change. Much of the interest in these values is however due to an implicit assumption that these contributions are directly relevant for the question of climate sensitivity. Motivated by the need for a clear reference for this issue, we review the existing literature and use the Goddard Institute for Space Studies ModelE radiation module to provide an overview of the role of each absorber at the present-day and under doubled CO2. With a straightforward scheme for allocating overlaps, we find that water vapor is the dominant contributor (∼50% of the effect), followed by clouds (∼25%) and then CO2 with ∼20%. All other absorbers play only minor roles. In a doubled CO2 scenario, this allocation is essentially unchanged, even though the magnitude of the total greenhouse effect is significantly larger than the initial radiative forcing, underscoring the importance of feedbacks from water vapor and clouds to climate sensitivity.

Toward unified satellite climatology of aerosol properties.: 3. MODIS versus MISR versus AERONET

Abstract: We use the full duration of collocated pixel-level MODIS-Terra and MISR aerosol optical thickness (AOT) retrievals and level 2 cloud-screened quality-assured AERONET measurements to evaluate the likely individual MODIS and MISR retrieval accuracies globally over oceans and land. We show that the use of quality-assured MODIS AOTs as opposed to the use of all MODIS AOTs has little effect on the resulting accuracy. The MODIS and MISR relative standard deviations (RSTDs) with respect to AERONET are remarkably stable over the entire measurement record and reveal nearly identical overall AOT performances of MODIS and MISR over the entire suite of AERONET sites. This result is used to evaluate the likely pixel-level MODIS and MISR performances on the global basis with respect to the (unknown) actual AOTs. For this purpose, we use only fully compatible MISR and MODIS aerosol pixels. We conclude that the likely RSTDs for this subset of MODIS and MISR AOTs are ∼73% over land and ∼30% over oceans. The average RSTDs for the combined [AOT(MODIS)+AOT(MISR)]/2 pixel-level product are close to 66% and 27%, respectively, which allows us to recommend this simple blend as a better alternative to the original MODIS and MISR data. These accuracy estimates still do not represent the totality of MISR and quality-assured MODIS pixel-level AOTs since an unaccounted for and potentially significant source of errors is imperfect cloud screening. Furthermore, many collocated pixels for which one of the datasets reports a retrieval, whereas the other one does not may also be problematic.

An optimal fitting approach to improve the GISS ModelE aerosol optical property parameterization using AERONET data

Abstract: [1] We improve the updated 2000 Goddard Institute for Space Studies, New York, ModelE aerosol optical property parameterization using an optimal fitting approach with AERONET ground measurements. The model aerosol optical properties, such as optical depth, are calculated using the aerosol mass density field from a chemical transport model, Mie scattering parameters, a prescribed dry size for each aerosol species assuming external mixing, and a hygroscopicity parameterization. A comparison between the model- and AERONET-measured optical depth (AOD) and Angstrom exponent (AE) indicates that the general circulation model (GCM) aerosol parameterization has a flatter AOD spectral dependence, thus a very low biased AE, which suggests that the aerosol sizes used in the model are too large. The seasonal variation of GCM AE also disagrees with that of AERONET data. On the basis of these results, we identify GCM aerosol size as the most poorly constrained parameter and develop an optimal fitting technique to adjust the GCM aerosol dry size by minimizing the total mean square error between the GCM and AERONET AOD at the six AERONET wavelengths. After adjusting the aerosol's dry size, the agreement between the GCM AE with AERONET data is improved. The fitted AOD at the six wavelengths closely matches AERONET data over most biomass burning, dust, and rural regions. The results are also greatly improved for the other aerosol types. The global distribution of the optimally fitted sizes displays regionally uniform characteristics, which allows the generation of a geographically varying size data set. Model uncertainty caused by other factors is also represented by an uncertainty parameter, which is mainly attributed to errors from aerosol mass concentration, Mie scattering parameters, relative humidity, and AERONET measurements. The relative contribution of each of these errors sources depends on the relevant aerosol type. Further comparison between the absorption optical depth and AE spectral dependence provides additional information on absorbing aerosols and GCM fine-to-coarse mode ratio, which will be addressed in future research.