Thursday, 14 January 2016: 8:30 AM
Room 356 ( New Orleans Ernest N. Morial Convention Center)
Lightning flashes heat the air to temperatures exceeding 20,000 K dissociating molecular oxygen and nitrogen, which then combine to create nitric oxide (NO), which quickly reacts with molecular oxygen to form nitrogen dioxide (NO2), a strong absorber in the visible that is measured from space by the Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite. Recently, we developed an algorithm to retrieve the lightning NOx (LNOx) signal from OMI. The algorithm in its general form takes the total slant column NO2 from OMI and removes the stratospheric contribution and tropospheric background (NO2 from sources other than lightning) and includes an air mass factor appropriate for the profile of lightning NOX to convert the slant column LNO2 to a vertical column of LNOx. However, since estimation of the tropospheric background is difficult, we initially applied the algorithm over the Gulf of Mexico at locations where the OMI cloud radiance fraction exceeded 90% suggestive of active convection. Retrieved NO2 at these locations is likely to originate from recent lightning and the background contribution can be assumed to be minimal. The use of this algorithm to estimate LNOx columns and NO production per flash over the Gulf of Mexico is described in an AMS presentation by K. Pickering. In this presentation, we will compare and contrast LNOx columns over the Amazon Basin, western Africa, and central Africa during the May-July and September-November time periods. Flashes are scarce in the Amazon Basin during May-July but plentiful during September-November. Flashes are plentiful in Africa during both periods with western African flashes peaking in May-July and central African flashes peaking in September-November. We will examine whether periods and locations with enhanced OMI LNOx have experienced recent lightning flashes using raw- and detection-efficiency adjusted data from the ground-based World Wide Lightning Location Network (WWLLN) and Vaisala Global Lightning Data 360 (GLD360) networks. We will also evaluate the contribution of biomass burning to the tropospheric background and whether it is possible to neglect the tropospheric background in these regions. Finally, we will examine uncertainties in the OMI LNOx and flash rates and discuss the feasibility of estimating NO production per flash in these regions using these data sets.
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