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The MethaneSAT satellite instrument and its aircraft precursor, MethaneAIR, are imaging spectrometers designed to measure methane concentrations with wide spatial coverage, fine spatial resolution, and high precision compared to currently deployed remote sensing instruments. At 12 960 m cruise altitude above ground (13 850 m above sea level), MethaneAIR datasets have a 4.5 km swath gridded to 10 m × 10 m pixels with 17-20 ppb standard deviation on a flat scene. MethaneAIR was deployed in the summer of 2021 in the Permian Basin to test the accuracy of the retrieved methane concentrations and emission rates using the algorithms developed for MethaneSAT. We report here point source emissions obtained during a single-blind volume-controlled release experiment, using two methods. (1) The modified integrated mass enhancement (mIME) method estimates emission rates using the total mass enhancement of methane in an observed plume combined with winds obtained from Weather Research Forecast driven by High-Resolution Rapid Refresh meteorological data in Large Eddy Simulations mode (WRF-LES-HRRR). WRF-LES-HRRR simulates winds in stochastic eddy-scale (100-1000 m) variability, which is particularly important for low-wind conditions and informing the error budget. The mIME can estimate emission rates of plumes of any size that are detectable by MethaneAIR. (2) The divergence integral (DI) method applies Gauss's theorem to estimate the flux divergence fields through a series of closed surfaces enclosing the sources. The set of boxes grows from the upwind side of the plume through the core of each plume and downwind. No selection of inflow concentration, as used in the mIME, is required. The DI approach can efï¬ ciently determine ï¬ uxes from large sources and clusters of sources but cannot resolve small point emissions. These methods account for the effects of eddy-scale variation in different ways: The DI averages across many eddies, whereas the mIME re-samples many eddies from the LES simulation. The DI directly uses HRRR winds, while mIME uses WRF-LES-HRRR wind products. Emissions estimates from both the mIME and DI methods agreed closely with the single-blind volume-controlled experiments (N Combining double low line 21). The York regression between the estimated emissions and the released emissions has a slope of 0.96 [0.84, 1.08], R Combining double low line 0.83 and N Combining double low line 21, with 30 % mean percentage error for the whole dataset, which indicates that MethaneAIR can quantify point sources emitting more than 200 kg h-1 for the mIME and 500 kg h-1 for the DI method. The two methods also agreed on methane emission estimates from various uncontrolled sources in the Permian Basin. The experiment thus demonstrates the powerful potential of the MethaneAIR instrument and suggests that the quantification method should be transferable to MethaneSAT if it meets the design specifications.

Reducing methane (CH 4) emissions from the oil and gas (O&G) sector is crucial for mitigating climate change in the near term. MethaneSAT is an upcoming satellite mission designed to monitor basin-wide O&G emissions globally, providing estimates of emission rates and helping identify the underlying processes leading to methane release in the atmosphere. MethaneSAT data will support advocacy and policy efforts by helping to track methane reduction commitments and targets set by countries and industries. Here, we introduce a CH 4 retrieval algorithm for MethaneSAT based on the CO 2 proxy method. We apply the algorithm to observations from the maiden campaign of MethaneAIR, an airborne precursor to the satellite that has similar instrument specifications. The campaign was conducted during winter 2019 and summer 2021 over three major US oil and gas basins. Analysis of MethaneAIR data shows that measurement precision is typically better than 2 % at a 20×20 m 2 pixel resolution, exhibiting no strong dependence on geophysical variables, e.g., surface reflectance. We show that detector focus drifts over the course of each flight, likely due to thermal gradients that develop across the optical bench. The impacts of this drift on retrieved CH 4 can mostly be mitigated by including a parameter that squeezes the laboratory-derived, tabulated instrument spectral response function (ISRF) in the spectral fit. Validation against coincident EM27/SUN retrievals shows that MethaneAIR values are generally within 1 % of the retrievals. MethaneAIR retrievals were also intercompared with retrievals from the TROPOspheric Monitoring Instrument (TROPOMI). We estimate that the mean bias between the instruments is 2.5 ppb, and the latitudinal gradients for the two data sets are in good agreement. We evaluate the accuracy of MethaneAIR estimates of point-source emissions using observations recorded over the Permian Basin, an O&G basin, based on the integrated-mass-enhancement approach coupled with a plume-masking algorithm that uses total variational denoising. We estimate that the median point-source detection threshold is 100–150 kg h -1 at the aircraft's nominal above-surface observation altitude of 12 km. This estimate is based on an ensemble of Weather Research and Forecasting (WRF) large-eddy simulations used to mimic the campaign's conditions, with the threshold for quantification set at approximately twice the detection threshold. Retrievals from repeated basin surveys indicate the presence of both persistent and intermittent sources, and we highlight an example from each case. For the persistent source, we infer emissions from a large O&G processing facility and estimate a leak rate between 1.6 % and 2.1 %, higher than any previously reported emission levels from a facility of its size. We also identify a ruptured pipeline that could increase total basin emissions by 2 % if left unrepaired; this pipeline was discovered 2 weeks before it was found by its operator, highlighting the importance of regular monitoring by future satellite missions. The results showcase MethaneAIR's capability to make highly accurate, precise measurements of methane dry-air mole fractions in the atmosphere, with a fine spatial resolution (∼ 20×20 m 2) mapped over large swaths (∼ 100×100 km 2) in a single flight. The results provide confidence that MethaneSAT can make such measurements at unprecedentedly fine scales from space (∼ 130×400 m 2 pixel size over a target area measuring ∼ 200×200 km 2), thereby delivering quantitative data on basin-wide methane emissions. [ABSTRACT FROM AUTHOR]

This work presents the development of the MethaneAIR Level0–Level1B processor, which converts raw L0 data to calibrated and georeferenced L1B data. MethaneAIR is the airborne simulator for MethaneSAT, a new satellite under development by MethaneSAT LLC, a subsidiary of the Environmental Defense Fund (EDF). MethaneSAT's goals are to precisely map over 80 % of the production sources of methane from oil and gas fields across the globe to an accuracy of 2–4 ppb on a 2 km 2 scale. Efficient algorithms have been developed to perform dark corrections, estimate the noise, radiometrically calibrate data, and correct stray light. A forward model integrated into the L0–L1B processor is demonstrated to retrieve wavelength shifts during flight accurately. It is also shown to characterize the instrument spectral response function (ISRF) changes occurring at each sampled spatial footprint. We demonstrate fast and accurate orthorectification of MethaneAIR data in a three-step process: (i) initial orthorectification of all observations using aircraft avionics, a simple camera model, and a medium-resolution digital elevation map; (ii) registration of oxygen (O 2) channel grayscale images to reference Multispectral Instrument (MSI) band 11 imagery via Accelerated-KAZE (A-KAZE) feature extraction and linear transformation, with similar co-registration of methane (CH 4) channel grayscale images to the registered O 2 channel images; and finally (iii) optimization of the aircraft position and attitude to the registered imagery and calculation of viewing geometry. This co-registration technique accurately orthorectifies each channel to the referenced MSI imagery. However, in the pixel domain, radiance data for each channel are offset by almost 150–200 across-track pixels (rows) and need to be aligned for the full-physics or proxy retrievals where both channels are simultaneously used. We leveraged our orthorectification tool to identify tie points with similar geographic locations in both CH 4 and O 2 images in order to produce shift parameters in the across-track and along-track dimensions. These algorithms described in this article will be implemented into the MethaneSAT L0–L1B processor. [ABSTRACT FROM AUTHOR]

Reducing methane (CH4) emissions from the oil and gas (O&G) sector is key to mitigating climate change in the near-term. MethaneSAT is an upcoming satellite mission designed to monitor basin-wide O&G emissions globally, providing estimates of emission rates and helping identify the underlying processes leading to methane release to the atmosphere. MethaneSAT data will help advocacy and policy efforts to help track methane reduction commitments and targets made by countries and industry. Here we introduce the CH4 retrieval algorithm for MethaneSAT based on the CO2 proxy method. We apply the algorithm to observations from the maiden campaign of MethaneAIR, an airborne precursor to the satellite with similar instrument specifications. The campaign was conducted during winter 2019 and summer 2021 over three major US oil and gas basins. Analysis of the MethaneAIR data shows that measurement precision is typically better than 2 % for 20 × 20 m2 pixel resolution, with no strong dependence on geophysical variables such as surface reflectance. We show that detector focus drifts over the course of each flight likely due to thermal gradients that develop across the optical bench. The impacts of this drift on retrieved CH4 can mostly be mitigated by including a parameter that squeezes the laboratory tabulated instrument spectral response function in the spectral fit. Validation against coincident EM27/SUN retrievals shows that MethaneAIR values are generally within 1 %. MethaneAIR retrievals were also intercompared with those of TROPOMI; the latitudinal gradients for the two datasets are in good agreement, with a 2.5 ppb mean bias between instruments. We evaluate the accuracy of MethaneAIR estimates of point source emissions using observations made over the Permian O&G basin, based on the integrated mass enhancement approach coupled with a plume-masking algorithm based on total variational denoising. We estimate that the median point source detection threshold is 100–150 kg h−1 at the aircraft's nominal 12 km above-surface observation altitude, based on an ensemble WRF large eddy simulations used to mimic the campaign conditions with the threshold for quantification about 2× the detection threshold. Retrievals from repeated basin surveys indicate the presence of both persistent and intermittent sources, and we highlight an example from each case. For the persistent source we infer emissions from a large O&G processing facility, and estimate a leak rate between 1.6 and 2.1 %, higher than any previously-reported emission from a facility of its size. We also identify a ruptured pipeline that alone would constitute 2 % of estimated basin emissions, two weeks before it was found by its operator, highlighting the importance of regular monitoring from the future satellite mission. The results showcase the capability of MethaneAIR to make highly accurate, precise measurements of methane dry-air mole fractions in the atmosphere, with fine spatial resolution over large swaths on the ground. The results provide confidence that MethaneSAT can make such measurements at unprecedentedly fine scales from space (∼ 130 × 400 m2), thereby delivering quantitative data on basin-wide methane emissions. [ABSTRACT FROM AUTHOR]

Accurate predictions of harmful space weather effects are mandatory for the protection of astronauts and other assets in space, whether in Earth or lunar orbit, in transit between solar system objects, or on the surface of other planetary bodies. Because the corona is multithermal (i.e., structured not only in space but also in temperature), wavelength-separated data provide crucial information that is not available to imaging methods that integrate over temperature. The extreme ultraviolet (EUV) wavelengths enable us to focus directly on high temperature coronal plasma associated with solar flares, coronal mass ejections (CMEs), and shocked material without being overwhelmed by intensity from the solar disk. Both wide-field imaging and spectroscopic observations of the solar corona taken from a variety of orbits (e.g., Earth, L1, or L5) using suitably-chosen EUV instrumentation offer the possibility of addressing two major goals to enhance our space weather prediction capability, namely: (1) Improve our understanding of the coronal conditions that control the opening and closing of the corona to the heliosphere and consequent solar wind streams, and (2) Improve our understanding of the physical processes that control the early evolution of CMEs and the formation of shocks, from the solar surface out into the extended corona.