Estimates of lightning NOx production based on OMI NO2 observations over the Gulf of Mexico. Issue 14 (19th July 2016) - Pickering, Kenneth E.; Bucsela, Eric; Allen, Dale; Ring, Allison; Holzworth, Robert; Krotkov, Nickolay
Abstract: We evaluate nitrogen oxide (NO x  = NO + NO2 ) production from lightning over the Gulf of Mexico region using data from the Ozone Monitoring Instrument (OMI) aboard NASA's Aura satellite along with detection efficiency‐adjusted lightning data from the World Wide Lightning Location Network (WWLLN). A special algorithm was developed to retrieve the lightning NO x (LNO x ) 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 and includes an air mass factor appropriate for the profile of lightning NO x to convert the slant column LNO2 to a vertical column of LNO x . WWLLN flashes are totaled over a period of 3 h prior to OMI overpass, which is the time an air parcel is expected to remain in a 1° × 1° grid box. The analysis is conducted for grid cells containing flash counts greater than a threshold value of 3000 flashes that yields an expected LNO x signal greater than the background. Pixels with cloud radiance fraction greater than a criterion value (0.9) indicative of highly reflective clouds are used. Results for the summer seasons during 2007–2011 yield mean LNO x production of ~80 ± 45 mol per flash over the region for the two analysis methods after accounting for biases and uncertainties in the estimation method. These results are consistent with literature estimates and more robust than many prior estimates due to the large number of storms considered but are sensitive to several substantial sources of uncertainty. Key Points: Realistic seasonal mean values of lightning NO x (LNO x ) production can be obtained from OMI data Mean LNO x production over the Gulf of Mexico for five summers is 80 ± 45 mol per flash when adjusted for biases and uncertainties Biases and uncertainties in LNO x estimates stemming from OMI data, elements of the algorithm, and flash data are quantified