Statistics from sky/sunphotometers at AERONET sites throughout the world provided the background for a comparison of monthly or seasonally averaged aerosol optical depths. The comparisons involved aerosol retrievals by operational satellites and representations of aerosol in global models.

Aerosol optical depths retrievals from five different satellites were compared. Critical issues are instrument calibration, the ability to remove scenes with clouds, assumptions on aerosol properties and contributions from background reflectance. Most retrievals are confined to ocean scenes, due to difficulties in representing background reflectance at high accuracy over land. Quantitatively accurate satellite retrievals over land remain a challenge and current efforts are often at an experimental stage. Still, these attempts provide data on spatial distribution, although initial applications to identify biases of (AERONET-) sites data in comparisons to regions (of models) remained inconclusive.

Aerosol optical depths representations of five global models were compared. Monthly averages among models vary and are usually smaller than AERONET averages. All models distinguish in optical depth contributions by carbon, sulfate, sea-salt and dust. Such component treatment promises better simulations for aerosol concentration and aerosol absorption, which are critical for accurate simulations of aerosol climatic impacts. A component treatment, however, complicates modeling and introduces new sources for errors. To identify model deficiencies and to circumvent offsetting errors, comparisons were conducted on a component basis for mass and optical depth. Critical in a derivation of a component optical depth is the conversion from mass into optical depth. Necessary assumptions for aerosol size and humidification were compared. Many poor assumptions were identified and several models are already represented by improved versions. The overall agreement among models has improved, but there are still many discrepancies that are better explored in more focused comparisons.

Co-location in time and space, are vital for more useful comparisons. Co-location in time for modeling means the use of identical data-sets for emission and assimilated meteorology. Co-location in time for comparisons to AERONET or satellite data means the application of data-screens that accommodate the less frequently sampled data-set. The regional representation of local measurements remains a problem. Sub-grid modeling is essential for the representation of non-linear processes in modeling (e.g. ambient relative humidity and its impact on aerosol size). Satellite data hold the key in connecting local (AERONET) data to regional averages (of models). New satellites with multi-angle viewing capabilities, finer resolution spatial and spectrally, and better calibration should provide more accurate retrievals.

Nonetheless, the need for in-situ data and data from field experiments remains in order to address assumptions for aerosol size and aerosol composition (including humidification). A better understanding of aerosol properties should also lead to a re-evaluation and possible combination of twenty year long data-sets from AVHRR and TOMS, which provide a global and seasonal framework in which model-output can be tested. As future remote sensing from space will be providing a more detailed characterization of the earth and its atmospheres, as simultaneous monitoring of the atmosphere from the ground is spreading, and as global communication and data-processing is accelerating, modelers are challenged to test their models, with simulations in a 'nowcast' mode.

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