Browsing UAF Graduate School by Author "Madden, James Michael"
Using WRF/Chem, in-situ observations, and Calipso data to simulate smoke plume signatures on high-latitude pixelsMadden, James Michael; Mölders, Nicole; Sassen, Kenneth; Prakash, Anupma; Grell, Georg (2014-05)The transport of wildfire aerosols provides concerns to people at or near downwind propagation. Concerns include the health effects of inhalation by inhabitants of surrounding communities and fire crews, the environmental effects of the wet and dry deposition of acids and particles, and the effects on the atmosphere through the scattering and absorption of solar radiation. Therefore, as the population density increases in Arctic and sub-Arctic areas, improving wildfire detection increasingly becomes necessary. Efforts to improve wildfire detection and forecasting would be helped if additional focus was directed toward the distortion of pixel geometry that occurs near the boundaries of a geostationary satellite's field of view. At higher latitudes, resolution becomes coarse due to the curvature of the Earth, and pixels toward the boundaries of the field of view become difficult to analyze. To assess whether it is possible to detect smoke plumes in pixels at the edge of a geostationary satellite's field of view, several analyses were performed. First, a realistic, fourdimensional dataset was created from Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) output. WRF/Chem output was statistically compared to ground observations through the use of skill scores. Output was also qualitatively compared to vertical backscatter and depolarization products from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. After the quantitative and qualitative examinations deemed the model output to be realistic, synthetic pixels were constructed, appropriately sized, and used with the realistic dataset to examine the characteristic signatures of a wildfire plume. After establishing a threshold value, the synthetic pixels could distinguish between clean and smoke-polluted areas. Thus, specialized retrieval algorithms could be developed for smoke detection in strongly distorted pixels at the edge of a geostationary satellite's field of view.