A comparison of seasonal and interannual variability of soil dust aerosolsover the Atlantic Ocean as inferred by the TOMS AI and AVHRR AOT retrievals

The seasonal cycle and interannual variability of two estimates of soil (or "mineral") dust aerosols axe compared: advanced very high resolution radio meter (AVHRR) aerosol optical thickness (AOT) and Total Ozone Mapping Spect rometer (TOMS) aerosol index (Al). Both data sets, comprising more than a d ecade of global, daily images, axe commonly; used to evaluate aerosol trans port models. The present comparison is based on monthly averages, construct ed from daily images of each data set for the period between 1984 and 1990, a period that excludes contamination from volcanic eruptions. The comparis on focuses on the Northern Hemisphere subtropical Atlantic Ocean, where soi l dust aerosols make the largest contribution to the aerosol load, and are assumed to dominate the variability of each data set. While each retrieval is sensitive, to a different aerosol radiative property (absorption for the TOMS Al versus reflectance for the AVHRR AOT), the seasonal cycles of dust loading implied by each retrieval are consistent, if seasonal variations i n the height of the aerosol layer are taken into account when interpreting the TOMS Al. On interannual timescales, the correlation is low at most loca tions. It is suggested that the poor interannual correlation is at least pa rtly a consequence of data availability. When the monthly averages axe cons tructed using only days common to both data sets, the correlation is substa ntially increased: this consistency suggests that both TOMS and AVHRR accur ately measure the aerosol load in any given scene. However, the two retriev als have only a few days in common per month, so these restricted monthly a verages have a large uncertainty. Calculations suggest that at least 7 to 1 .0 daily images are needed to estimate reliably the average dust load durin g any particular month, a threshold that is rarely satisfied by the AVHRR A OT due to the presence of clouds in the domain. By rebinning each data set onto a coarser grid, the availability of the AVHRR AOT is increased during any particular month, along with its interannual correlation with the TOMS AL The latter easily exceeds the sampling threshold due to its greater abil ity to infer the aerosol load in the presence of clouds. Whether the TOMS A l should be regarded as a more reliable indicator of interannual variabilit y depends on the extent of contamination by subpixel clouds.