Atmospheric correction for satellite‐based volcanic ash mapping and retrievals using “split window” IR data from GOES and AVHRR

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Abstract
Volcanic ash in volcanic clouds can be mapped in two dimensions using two‐band thermal infrared data available from meteorological satellites. Wen and Rose [1994] developed an algorithm that allows retrieval of the effective particle size, the optical depth of the volcanic cloud, and the mass of fine ash in the cloud. Both the mapping and the retrieval scheme are less accurate in the humid tropical atmosphere. In this study we devised and tested a scheme for atmospheric correction of volcanic ash mapping and retrievals. The scheme utilizes infrared (IR) brightness temperature (BT) information in two infrared channels (both between 10 and 12.5 μm) and the brightness temperature differences (BTD) to estimate the amount of BTD shift caused by lower tropospheric water vapor. It is supported by the moderate resolution transmission (MODTRAN) analysis. The discrimination of volcanic clouds in the new scheme also uses both BT and BTD data but corrects for the effects of the water vapor. The new scheme is demonstrated and compared with the old scheme using two well‐documented examples: (1) the 18 August 1992 volcanic cloud of Crater Peak, Mount Spurr, Alaska, and (2) the 26 December 1997 volcanic cloud from Soufriere Hills, Montserrat. The Spurr example represents a relatively “dry” subarctic atmospheric condition. The new scheme sees a volcanic cloud that is about 50% larger than the old. The mean optical depth and effective radii of cloud particles are lower by 22% and 9%, and the fine ash mass in the cloud is 14% higher. The Montserrat cloud is much smaller than Spurr and is more sensitive to atmospheric moisture. It also was located in a moist tropical atmosphere. For the Montserrat example the new scheme shows larger differences, with the area of the volcanic cloud being about 5.5 times larger, the optical depth and effective radii of particles lower by 56% and 28%, and the total fine particle mass in the cloud increased by 53%. The new scheme can be automated and can contribute to more accurate remote volcanic ash detection. More tests are needed to find the best way to estimate the water vapor effects in real time.