Probability of Detection\nand Multi-Sensor Persistence\nof Methane Emissions from Coincident Airborne and Satellite Observations

Satellites are becoming a widely used measurement tool\nfor methane\ndetection and quantification. The landscape of satellite instruments\nwith some methane point-source quantification capabilities is growing.\nCombining information across available sensor platforms could be pivotal\nfor understanding trends and uncertainties in source-level emissions.\nHowever, to effectively combine information across sensors of varying\nperformance levels, the probability of detection (POD) for all instruments\nmust be well characterized, which is time-consuming and costly, especially\nfor satellites. In August 2023, we timed methane-sensing aerial surveys\nfrom the Global Airborne Observatory (GAO) to overlap with observations\nfrom the NASA Earth Surface Mineral Dust Source Investigation (EMIT).\nWe show how these coincident observations can be used to determine\nand verify the detection limits of EMIT and to develop and test a\nmultisensor persistence framework. Under favorable conditions, the\n90% POD at 3 for EMIT is 1060. We further derive a Bayesian model\nto infer probabilistically whether nondetected emissions were truly\noff, and we validate and show how this model can be used to assess\nthe intermittency of emissions with GAO and EMIT. Time-averaged emission\nrates from persistent sources can be underestimated if POD is not\ncharacterized and if differences in POD across multisensor frameworks\nare not properly accounted for.