Performance and sensitivity of column-wise and pixel-wise methane retrievals for imaging spectrometers

Abstract

Abstract. Strong methane point source emissions generate large atmospheric concentrations that can be detected and quantified with infrared remote sensing and retrieval algorithms. Two standard and widely used retrieval algorithms for one class of observing platform, imaging spectrometers, include pixel-wise and column-wise approaches. In this study, we assess the performance of both approaches using the airborne imaging spectrometer (Global Airborne Observatory) observations of two extensive controlled-release experiments. We find that the column-wise retrieval algorithm is sensitive to the flight line length and can have a systematic low bias with short flight lines, which is not present in the pixel-wise retrieval algorithm. However, the pixel-wise retrieval is very computationally expensive, and the column-wise retrieval algorithms can produce good results when the flight line length is sufficiently long. Lastly, this study examines the methane plume detection performance of the Global Airborne Observatory with a column-wise retrieval algorithm and finds minimum detection limits of between 9 of 10 kg h−1 and 90 % probability of detection between 10 and 45 kg h−1. These results present a framework of rules for guiding proper concentration retrieval selection given conditions at the time of observation in order to ensure robust detection and quantification.