Ship- and aircraft-based XCH4 over oceans as new tool for satellite validation
Abstract. Satellite based estimations of dry-air column-average mixing ratios of methane (XCH4) contribute to a better understanding of changes in CH4 emission sources and variations in its atmospheric growth rates. High accuracy of the satellite measurements is required, and therefore, extensive validation is performed, mainly against the Total Carbon Column Observing Network (TCCON). However, validation opportunities at open ocean areas outside the coastal regions are sparse. We propose a new approach to assess the accuracy of satellite derived XCH4 trends and variations. We combine various ship and aircraft observations with the help of atmospheric chemistry models, mainly used for the stratospheric column, to derive observation-based XCH4 (obs. XCH4). Based on our previously developed approach for the application to XCO2, we investigated 3 different advancements from a simple to more elaborate approaches (approach 1, 2, and 3) to account for the higher tropospheric and stratospheric variability of CH4 as compared to CO2. Between 2014–2018, at 20–40° N of the western Pacific, we discuss the uncertainties of the approaches and the derived obs. XCH4 within 10° by 20° latitude–longitude boxes. Uncertainties were 22 ppb for approach 1, and 17 ppb for approach 2 and 3. We analysed the consistency with the nearest TCCON stations and found agreement of approach 3 with Saga of 1 ± 12 ppb, and −1 ± 11 ppb with Tsukuba for the northern and southern latitude box, respectively. Furthermore, we discuss the impact of the modelled stratospheric column on the derived obs. XCH4 by applying 3 different models in our approaches. Depending on the models, the difference can be more than 0.5 %, showing the importance for the appropriate choice. We show that our obs. XCH4 dataset accurately captures seasonal variations of CH4 over the ocean. Using different retrievals of the Greenhouse gases Observing Satellite (GOSAT) from the National Institute for Environmental Studies (NIES), the RemoTeC full-physics retrieval operated at the Netherlands Institute for Space Research (SRON), and the full-physics retrieval of the University of Leicester (UoL-OCFP), we demonstrate the applicability of the dataset for satellite evaluation. The comparison with results of approach 3 revealed that NIES showed a difference of −0.04 ± 13 ppb and strong scatter at 20–30° N, while RemoTeC and OCFP have rather systematic negative bias of −12.1 ± 8.1 ppb and −10.3 ± 9.6 ppb. Our new approach to derive XCH4 reference datasets over the ocean can contribute to the validation of existing and upcoming satellite missions in future.
