Evaluation of JPSS Aerosol Detection Algorithm with eMAS Measurements during Firex-AQ Field Campaign

Abstract:

NOAA JPSS Aerosol Detection Product (ADP) algorithm detects smoke/dust over both land and water. Besides spectral differencing tests the ADP algorithm uses to determine the presence of smoke and dust, spatial uniformity tests are also crucial to screen for residual cloud contamination. During the fire season in 2019, NASA Firex-AQ field campaign carried out intensive measurement operation with both ground-based and Airborne instruments over wild fire events with some flights targeted for Suomi NPP and NOAA-20 satellite overpasses. The acquired measurements from the enhanced MODIS Airborne Simulator (eMAS), which has similar spectral coverage as Visible Infrared Imaging Radiometer Suite (VIIRS), provided unique opportunities to examine the impact of sub-pixel variability over smoke plumes on the uniformity tests in JPSS ADP algorithm. In this study, we applied JPSS ADP algorithm on eMAS L1B measurements for over 160 flight-tracks, and also collocated with NOAA/SNPP VIIRS granules when they are available. First, we evaluated the smoke detection results from ADP on eMAS measurements with those from VIIRS ADP. Secondly, the uniformity tests, i.e., the standard deviation of 0.64 um in a box containing 3 by 3 VIIRS pixels are compared with those calculated with the collocated eMAS measurements to evaluate the adequacy of the uniformity test applied in current JPSS ADP algorithm. It is found that the JPSS ADP algorithm applied to eMAS measurements is able to detect thick smoke plume. However, it failed to pick up thin smoke plumes. Sub-pixel variability, in terms of standard deviation at 0.64 um, affects smoke detection largely for thin smoke. For Thick smoke plumes, current uniformity test in JPSS ADP is adequate enough for picking up the smoke detection.