Presentday Status

Over the last decade, atmospheric research began to concentrate on aerosols, because they were identified as a key regulator of atmospheric change, including clouds. From a modeling perspective, increased computing capacities permitted better characterization of aerosols in global models. Elaborate aerosol submodules now process emissions from different aerosol components (e.g., sulfate, organic matter, black carbon, dust, and sea salt). Particle size is resolved into several size classes; at the very least, there is an accumulation mode and one or several coarse modes for dust and sea salt. Some aerosol modules even allow added complexities of component mixtures. Notwithstanding the limitations to evaluation data (often component-integrated data with non-negligible uncertainty, such as satellite AOD), there is now a great deal of freedom in modeling within the aerosol module. For example, the AeroCom aerosol module exercise demonstrated signifi cant model diversity in compositional attribution (Kinne et al. 2006). This diversity was partly related to prewired assumptions in aerosol processing (e.g., wet deposition), as most model biases remained even though the emission input to all models had been harmonized (Textor et al. 2006).

From the perspective of measurements, ground-monitoring networks were established in parallel with the launching of new aerosol-dedicated satellite sensors. This included multispectral sensors such as MODIS (Tanre et al. 1997; Kaufman et al. 1997), multidirectional sensors such as MISR (Kahn et al. 1998; Martonchik et al. 1998), and even sensors with detection of polarized signals such as POLDER (Deuze et al. 1999; Deuze et al. 2001). Onboard calibrations, more detailed retrieval models, and simultaneous sampling with supporting sensors on the same or consecutive platforms (e.g., A-Train; Anderson et al. 2005) provide better detail of aerosol properties than had been previously available. Currently, satellite sensors can supply AOD maps over land (even over bright desert regions). In addition, active remote sensing by the CALIPSO lidar (Winker et al. 2004) and CloudSat radar (Stephens and Kummerow 2007) supplies samples of aerosol vertical distribution and altitude placement for clouds (i.e., essential information for more accurate aerosol direct forcing estimates). Accuracy issues remain, however, with respect to retrieval assumptions (e.g., surface properties, predefined aerosol types) and subpixel contamination (e.g., clouds, snow). Data from ground-based monitoring networks are expected to serve as quality reference. The most important networks for columnar aerosol optical properties are AERONET and SKY-NET; their sun/sky photometers derive all particle properties simultaneously: amount, size, absorption, and shape. Additional sun photometer networks (e.g., GAW) increase the data volume on particle amount and size. In parallel, lidar sampling (for vertical profiling) has organized itself into regional networks, as EARLINET for Europe or NIES for Eastern Asia. Especially attractive are sites with complementary instrumentation: lidar deployments by MPL-Net at AERONET sun/sky photometer sites or sun photometer deployments at lidar sites. Since ground remote sensing establishes a needed reference in the characterization of aerosols, an overview of some of the major networks follows.

0 0

Post a comment