Author/Authors :
ai, yufei peking university - school of physics, laboratory for climate and ocean-atmosphere studies - department of atmospheric and oceanic sciences, Beijing, China , ai, yufei university of wisconsin-madison - cooperative institute for meteorological satellite studies, Wisconsin, USA , li, jun university of wisconsin-madison - cooperative institute for meteorological satellite studies, Wisconsin, USA , shi, wenjing university of wisconsin-madison - cooperative institute for meteorological satellite studies, Wisconsin, USA , shi, wenjing chinese academy of sciences - institute of atmospheric physics - state key laboratory of numerical modeling for atmospheric sciences and geophysical fluid dynamics, Beijing, China , schmit, timothy j. center for satellite applications and research, nesdis/noaa, Maryland, USA , cao, changyong center for satellite applications and research, nesdis/noaa, Maryland, USA , li, wanbiao peking university - school of physics - department of atmospheric and oceanic sciences, laboratory for climate and ocean-atmosphere studies, Beijing, China
Abstract :
Deep convective storms have contributed to airplane accidents, making them a threat to aviation safety. The most common method to identify deep convective clouds (DCCs) is using the brightness temperature difference (BTD) between the atmospheric infrared (IR) window band and the water vapor (WV) absorption band. The effectiveness of the BTD method for DCC detection is highly related to the spectral resolution and signal-to-noise ratio (SNR) of the WV band. In order to understand the sensitivity of BTD to spectral resolution and SNR for DCC detection, a BTD to noise ratio method using the difference between the WV and IR window radiances is developed to assess the uncertainty of DCC identification for different instruments. We examined the case of AirAsia Flight QZ8501. The brightness temperatures (Tbs) over DCCs from this case are simulated for BTD sensitivity studies by a fast forward radiative transfer model with an opaque cloud assumption for both broadband imager (e.g., Multifunction Transport Satellite imager, MTSAT-2 imager) and hyperspectral IR sounder (e.g., Atmospheric Infrared Sounder) instruments; we also examined the relationship between the simulated Tb and the cloud top height. Results show that despite the coarser spatial resolution, BTDs measured by a hyperspectral IR sounder are much more sensitive to high cloud tops than broadband BTDs. As demonstrated in this study, a hyperspectral IR sounder can identify DCCs with better accuracy.
Keywords :
Deep convective , airplane accidents , infrared sounder , BTD method
