Automated retrievals of volcanic ash and dust cloud properties from upwelling infrared measurements

Abstract

AbstractA fully automated, globally applicable algorithm to retrieve ash and dust cloud properties from infrared satellite measurements is presented. The algorithm, which will serve as the official operational algorithm of the next generation Geostationary Operational Environmental Satellite (GOES‐R), utilizes an optimal estimation framework that allows uncertainties in the measurements and forward model to be taken into account and uncertainty estimates for each of the retrieved parameters to be determined. The retrieval approach is globally applicable because background atmospheric water vapor, surface temperature, and surface emissivity are explicitly accounted for on a pixel‐by‐pixel basis. The retrieval is demonstrated using the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on‐board the Second Generation Meteosat. Ash clouds from the 2010 eruption of Eyjafjallajökull in Iceland and the 2010 eruption of Soufriere Hills in the eastern Caribbean and a Saharan dust cloud were analyzed, and the accuracy of the retrieval was evaluated using spaceborne lidar measurements. The validation analysis shows that the retrieved ash/dust cloud height, cloud emissivity, and effective particle radius generally agrees well with lidar measurements, especially when volcanic ash clouds are assumed to be composed of andesite and dust clouds composed of kaolinite.